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`(43) International Pnb|i.:a1inn Date
`14 February 2002 (14.02.2002)
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`PCT
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`(I9) lI1temationalPubIicalion Number
`wo 02/12932 A2
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`luterulalimial Palenl Classification’:
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`G06?
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`Illlenlaliollal Applicalioil Number:
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`PC'lTl]S(}1.f3503(i
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`International Filing Date:
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`3 m1gu.~‘t2Dfll [U3.|.'i3.'200i!
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`Filing Language:
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`P“b|i(-ntion Language:
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`Iinglish
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`Priority Data:
`U9.I'fi34.|[l?§
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`8 August 2I)(J(}l[l8.l]8.2ll0U}
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`US
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`Applicant: OBJECT SERVICES A ND CONSULTING.
`INC. |USIUS|: ‘.‘T.‘5 Deep Valley '[‘r:u'1, I’luno_. TX 75203
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`WO02/12982A2
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`(57) Abslracl: A Iriclilud ul‘ guialcd nuluru] language ititcrfacc includus inputling lo :2 thin ciicnl 1| query. cuniliiullicalling Iu an in-
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`MICROSOFT CORP. ET AL.
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`EXHIBIT 1014
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`GUIDED NATURAL LANGUAGE INTERFACE SYSTEM AND METHOD
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`Background of the Invention
`The present invention generally relates to computers and computing and, more
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`particularly, to natural language interfaces (NLI) for user interfacing with computing devices to
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`interact with computer applications, for example, database programs, on such devices or
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`5
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`interconnected devices, by inputting stated questions or commands in natural language, such as
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`English language and grammar, to which the devices and applications respond.
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`Computational linguistics and natural language processing are rather specialized
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`computing disciplines
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`that relate to the computer user and his ability and mode of
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`communication with computing devices. In the sub-area of natural language processing, more
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`10
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`specific areas of research and development include information retrieval from text (for example,
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`using keywords as in conventional search engines, such as Google™); question answering from
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`databases, knowledgebases, or text (for example, linguistically motivatec;l techniques using
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`grammars and lexicons but also pattern-based techniques); natural language generation; natural
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`language translation; text-to-speech; speaker recognition; ontologies (such as, for example,
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`15 Wordnet™), and conversational analysis. A natural language interface (NLI), as the name
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`implies, is a particular mode or method of user interaction with a computing device or devices in
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`which the user employs natural language, such as the English language and grammar, to
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`communicate inputs, for example, queries and commands, to the devices and applications of the
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`devices. NLis can often be desired modes for communicating with computing devices, software
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`20
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`applications, and related hardware and software components, depending on the particular
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`application or discipline for the devices and in the case of experienced as well as less(cid:173)
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`sophisticated users.
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`Certain types of natural language interfaces are conventional. In the conventional NLls,
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`the user types or speaks unconstrained commands (including queries) with the expectation that
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`25
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`the system will understand the speech acts and take the desired action (e.g., return an answer).
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`As can be understood, there are limitations to the capabilities of the conventional NLis. For
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`example, computing power and features have not previously been adequate to encompass all
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`possible variations and uses of language and grammar. Moreover, the tremendously large
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`numbers and variables of words, contexts, and meanings with any natural language are nearly
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`30
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`impossible to accurately process under all applicable language rules and variations.
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`Because of the limitations of computing and NLis in the past, computing users who
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`interface using NLis have typically not fully understood the limited scope and capabilities, or
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`"coverage", of the particular NLis (such as, in terms of the subset of natural language a system
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`understands, typically delimited by lexical, semantic, grammatical, and domain coverage
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`boundaries). Consequently, NLI commands and language are often not fully or properly
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`interpreted or understood by the NLI or computing system having such interface, and the user
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`likely will not have sufficient command of the natural language subset and limitations of the NLI
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`5
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`and extensive training or learning can be required in order to make appropriate and desired use
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`of capabilities of the NLI and related system. The NLis have not necessarily made interfacing
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`more inherently understandable or easier to the user. In other words, the typical user of natural
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`language commands and NLls for interfacing with computing devices can risk overshooting or
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`undershooting the underlying application system's capabilities, because of the limitations of
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`10
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`those capabilities with the present states of computing capacity and technologies and because of
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`the limits of the user's knowledge and understanding.
`In addition to the implications to computing users who interface via NLis, computer and
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`software developers of NLis for applications have the overwhelming and virtually impossible
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`task of defining a large number of all possible words, grammar rules, and domain translations
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`15
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`necessary in efforts to increase NLI coverage. Because of the magnitude of the efforts in such
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`development, NLI creation is an expensive process, even to retarget from one database to
`another. All conventional NLis have limited and mismatch of coverage problems. In the past,
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`this has often caused users who experience the coverage problems to grow frustrated, and fail to
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`make full use or entirely discontinue use of conventional NLis.
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`20
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`Previously, NLis have generally been delivered with a set of limited form or "canned"
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`example queries. Users of the NLis have been encouraged to use these examples or only slight
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`variations thereof to obtain satisfactory results. Nonetheless, these example queries, even if only
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`slightly varied, often tend to interfacing failures or unexpected or incorrect results. Several
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`conventional NLI products include: Microsoft Easy Query™, ELF™, and iPhrase™. No doubt,
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`25
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`there are other conventional NLis and other NLI products. All such known NLI technologies
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`have been limited, however, in acceptability to few useful applications and to very narrow and
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`simple applications in any event, and none have become pervasively used or available in the
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`industry. This is the result of the problems of the conventional NLis.
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`Of particular note in the early 1980's, Texas fustruments developed the so-called
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`"NLMenu" system, a natural language interface technology that sought to address certain of the
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`foregoing problems of NLis. NLMenu employed substantially the same grammar, lexicon, and
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`parsing found in all other NLI systems at the time and even those conventional to date. One
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`nuance at the time of the NLMenu system was that the typical parser was modified in the system
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`to parse a partial sentence and, then, predictively find all next legal completions (i.e., the
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`acceptable next words or phrases under the NLMenu interface lexicon and grammar) and display
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`these legal completions in a constellation menu (i.e., a menu displayed to the user that lists all
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`next lexical choices organized by grammatical category). The user was then able to select from
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`the constellation menu a next word or phrase in the menu, which word or phrase was an
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`5
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`appropriate legal completion of the particular natural language input sentence, query, command
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`or other sequence. The NLMenu system is described in U.S. Patent No. 4,829,423, and certain
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`additional aspects are described in U.S. Patents Nos. 4,688,195 and 5,083,268.
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`As with the other conventional NLls, the NLMenu system presented many of the
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`problems previously described. Moreover, the NLMenu system is quite limited in that it is a
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`10
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`single-user system in which constellation menus are displayed on the user's computing device
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`and interact with a single, complex full-featured parser. The constellation menus show a single
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`screen-shot of the user's display of the entire lexicon useable by the user to interface in the
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`natural language, but this is a disadvantage because the menus occupy considerable screen area
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`of the user's display and often obscure other entities or features displayed on the screen that can
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`15
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`be the subject of the user's efforts in lodging a natural language query. Switching among and
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`moving features around on the screen of the display can be inconvenient for the user.
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`Furthermore, the parser of the NLMenu system is full-featured and so useful for various
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`situations, but in many instances the parser is excessive in features and cumbersome (i.e.,
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`overkill) where alternative and simpler kinds of parsers are more useful and practical.
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`In
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`20
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`general, the NLMenu system has been useable for certain applications, but not others.
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`Particularly, the system is not particularly effective for use in present computing environments,
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`in which scalability, multi-user capability, wide area and remote geographic networking, and
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`reduced or "thin client" hardware and software is desired.
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`The present invention overcomes these and other problems of the prior technology.
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`25
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`Summary of the Invention
`Embodiments of the present invention include systems and methods for
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`light-weight
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`guided NLI client interfaces and supporting parser farms on servers, available concurrently and
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`in real time to a plurality of users, over disperse and geographically disparate networks, such as
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`the Internet.
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`30
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`An embodiment is a system for a natural language interface. The system includes a client
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`device, a server device, and a communications network interconnecting the client device and the
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`server device.
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`Another embodiment is a system for a natural language interface. The system includes a
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`thin client, a parser farm, a parser, a first communications network for communicatively
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`connecting the thin client and the parser farm, and a second communications network for
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`communicatively connecting another element selected from the group consisting of the parser
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`farm and the parser.
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`Yet another embodiment is a system for a natural language interface. The system
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`5
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`includes a thin client, an interface intermediary, a first communications network connecting the
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`thin client and the interface intermediary, an interface descriptor data source, a second
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`communications network connecting the interface descriptor data source and the interface
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`intermediary, a command intermediary, a third communications network connecting the
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`command intermediary and the interface intermediary, a parser farm, a fourth communications
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`10
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`network connecting the parser farm and the interface intermediary, a parser, a fifth
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`communications network communicatively connecting the parser to the parser farm, and a sixth
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`communications network for communicatively connecting the parser and the interface
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`intermediary.
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`Another embodiment of the system is a method of a natural language interface. The
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`15 method includes inputting to a thin client a query, requesting an appropriate parser for the query,
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`assigning an appropriate parser, parsing the query, and retmning a parsed translation.
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`Yet another embodiment is a method of parsing. The method includes inputting a query
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`at a first location and parsing the query at a second location.
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`Another embodiment is a method of a natural language interface. The method includes
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`20
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`inputting to a thin client a query, communicating to an interface intermediary, communicating to
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`an interface descriptor data source, generating an interface descriptor, communicating the
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`interface descriptor to the interface intermediary, communicating the interface descriptor to a
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`parser farm, requesting an appropriate parser corresponding to the interface descriptor, assigning
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`an appropriate parser, parsing, communicating a translation from the step of parsing, to the
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`25
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`interface intem1ediary, and communicating the translation to the thin client.
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`Brief Description of the Drawing
`The present invention may be better understood, and its numerous objects, features, and
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`advantages made apparent to those skilled in the art by referencing the accompanying drawings.
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`Fig 1 illustrates embodiments of a client-server system, including a client device and a
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`30
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`server device, communicatively connected by a network, such as the futemet, for serving as a
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`natural language interface system.
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`Fig. 2 illustrates embodiments of a method of operation of the clientwserver system of
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`Fig. 1, providing a multi-user, multi-device, geographically disparate communications system
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`having a natural language interface.
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`Fig. 3 illustrates embodiments of a system for a natural language interface over a network
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`5
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`of multiple and geographically disparate users and devices, such as the Internet.
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`Fig. 4 illustrates embodiments of a method of a natural language interface over a network
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`of multiple and geographically disparate users and devices, such as the Internet.
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`Fig. 5 illustrates embodiments of a natural language interface system, as found in one
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`such exemplary system referred to as the LingoLogic (LL) system.
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`10
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`Fig. 6 illustrates embodiments of a distinctive avatar employed to initiate a query or
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`command of the natural language interface system of Fig. 5.
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`Fig. 7 illustrates embodiments of a sequence of web-links and a popup menu used to
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`specify a query or command of the natural language interface system of Fig. 5.
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`Fig. 8 illustrates embodiments of a cascading menu used to specify a query or command
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`15
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`of the natural language interface system of Fig. 5.
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`Fig. 9 illustrates embodiments of phrase buttons used to specify a query or command of
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`the natural language interface system of Fig. 5.
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`Fig. 10 illustrates embodiments of a type-in display used to specify a query or command
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`of the natural language interface system of Fig. 5.
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`20
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`Fig. 11 illustrates embodiments of a drop down menu used to specify a query or
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`command of the natural language interface system of Fig. 5.
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`Fig. 12 illustrates embodiments of inputs and outputs of a Portable Specification Editor.
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`Fig. 13 illustrates embodiments of methods of importing an ODBC database schema into
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`the Portable Specification Editor.
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`25
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`Fig. 14 illustrates embodiments of a screen-shot of the Portable Specification Editor,
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`illustrating how an interface designer can create a portable specification from a database schema
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`that can then be used to auto-generate a guided natural language interface.
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`Fig. 15 illustrates embodiments of a simple expert used to specify a value in a query or
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`command of a natural language interface system.
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`Fig. 16 illustrates embodiments of a data source expert used to specify a value in a query
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`or command of a natural language interface system, wherein the value is shown during and after
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`invocation of the expert.
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`Fig. 17 illustrates embodiments of a translation of a sample query into SQL, in
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`5
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`accordance with a natural language interface system, such as the LingoLogic system.
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`Fig. 18 illustrates embodiments of execution results of a sample query in a tabular format
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`for a natural language interface system, such as the LingoLogic system.
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`The use of the same reference symbols in different drawings indicates similar or identical
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`items.
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`10
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`Detailed Description
`In computing, communications and processing devices, embodiments provide guided
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`interfaces to such devices and their applications, which guided interfaces are operable as
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`distributed parts of a guided language processor to client devices and server devices, such as in a
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`computer or communications network. Particularly, completion-based interfaces, such as
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`15
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`grammar-driven menu-based restricted language interfaces (or so-called "natural language
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`interfaces" (NLI)), and also other interfaces such as guided navigation of categories, path
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`expressions, and languages other than natural languages, as well as speech interfaces to such
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`guided interfaces, are operable distributed among client and server elements. This distribution
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`enables predictive parsing, as well as translation and execution, concurrently and in real time,
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`20
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`supporting pluralities of users to simultaneously specify pluralities of queries or commands
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`interfaced to pluralities of devices and applications, including over a network or other distributed
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`computing environment. The embodiments are operable, for example, on the Internet and World
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`Wide Web network. Additionally, embodiments are operable in local area networks and even on
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`a single computer or device.
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`25
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`Referring to Fig. 1, a system 100 for a communicative network includes a server element
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`102 and a client eleme:qt 104. The client element 104 is communicatively connected . to the
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`server element 102 by a communicative connector 106. The server element 102 is any of a wide
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`variety of processing or communications devices, such as, for example, a computer, a processor,
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`a circuit, memory or other element within a processor or processing device, or any device
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`30
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`including any such matter, which server element 102 is capable of functioning to receive a
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`communicated request and appropriately respond. The client element 104 is also any of a wide
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`variety of processing or communications devices, such as, for example, those previously
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`mentioned, which client element 104 is capable of sending or causing the sending of a request
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`and receiving a communicated response. The communicative connector 106 is any of a wide
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`variety of communication channels and elements therefor, including, for example, a wire, a
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`circuit, a bus, a cable, a wired or wireless communications network, or any other device or
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`component that allows for communications, electrical or otherwise, between elements
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`5
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`functioning to communicate in a client-server manner. For purposes hereof, a client-server
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`system or function is to be broadly construed to include any and all communicative arrangements
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`in which elements, devices, or components intercommunicate, directly or through intermediary
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`systems, by generation of a request, receipt of the request, generation of a response, and
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`occurrence of the response. The client-server system and function, as so construed, includes
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`10
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`client-server operations over a network, such as the Internet or World Wide Web, another wide
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`area network, a local area network, and even within a device among elements, components, or
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`peripherals of the device, such as within a single computer or other processing device.
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`In operation, the system 100 operates, at least in part, in a client-server manner, such that
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`the client element 104 delivers a request over the communicative connector 106 to the server
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`15
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`element 102. The server element 102 receives the request and directly or indirectly processes it.
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`The server element 102 then appropriately responds to
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`the request, for example, by
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`communicating a response signal back to the client element 104 over the communicative
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`connector 106. Although the communicative connector 106 is illustrated in Fig. 1 as a simple
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`line connection between the client element 104 and the server element 102, it is to be understood
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`20
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`that the communicative connector 106 can be any of a wide variety of communicating
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`intermediate devices, connections, and elements of a network or system
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`that are
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`communicatively connected to enable inter-communications in the client-server manner just
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`described. For example, the communicative connector 104 in certain embodiments is the
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`Internet and each of the client element 104 and the server element 102 is a separate, disparate
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`25
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`processing device connected to the Internet. Of course, as has been more fully described, all
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`other network or interconnection of devices or components is possible and included within the
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`scope of the embodiments.
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`Referring to Fig. 2, a method 200 operable on the system 100 of Fig. 1 includes a step
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`202 of inputting a query or command to a client. In the step 202, for example, a human user
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`30
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`inputs, via input components such as a keyboard to a computing device as the client, a database
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`or other application query in a natural language, such as English grammar and lexicon, through a
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`natural language interface (NLI). In a step 204, a request is made, such as via the client to
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`another device, for example, a server, for an appropriate parser for parsing the particular NLI
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`input of the step 202.
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`Referring to Figs. 1 and 2, in conjunction, if, for example, the method 200 operates on a
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`system 100 that includes the Internet as the communicative connector 106 between a client
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`element 104 and the server element 102, the step 202 of inputting is performed at the client
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`element 104 and the step 204 of requesting an appropriate parser is communicated over the
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`5
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`communicative connector 106 to the server element 102. The server element 102 can maintain
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`or make accessible a selection of parser from among one or more parsers of a so-called "parser
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`farm". In this manner, an appropriate parser for the particular input from the client element 104
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`is useable, and the parser need not (although it may be) available in or at the client element 104
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`itself. In the trade, the term "thin client" is sometimes used to refer to a client in a client-server
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`10
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`system which does not itself have substantial processing or operative capability within the client,
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`and such thin client relies on other units, such as a server, for processing and operative
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`capabilities available on the client's request. The method 200 is particularly applicable to such
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`thin client environments, as those skilled in the art will understand and appreciate.
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`Continuing to refer to Fig. 2, a step 206 of the method 200 assigns the appropriate parser
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`15
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`for parsing the input of the step 202. The appropriate parser, in any instance, will depend on
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`several variables, including, for example, the numbers and types of parsers available for the
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`application and the particular system 100 and method 200 capabilities and operations. Selection
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`of parsers among several choices is subject to many possibilities. On selection of the parser in
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`the step 206, the parser in a step 208 performs a parse of the query or command input in the step
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`20
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`202. The step 208 is repeated until a well formed grammar constituent is specified. Once the
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`parse in the step 208 is completed, a step 210 returns a translation from the parser of the parsed
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`query or command.
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`Referring to Figs. 1 and 2, in conjunction, in a possible example in which the method 200
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`operates on a system 100 that includes the Internet as the communicative connector 106 as
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`smart phone, a set top box, a Palm™ device,· a toy controller, a remote control and any other
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`device having functions of input and request communication. The user of the thin client 302 is
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`most likely a human user, however, it can alternatively be a software or hardware agent which
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`interacts with the thin client 302 to input and receive responses.
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`5
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`Maintained on the thin client 302 can be a host application (not shown), such as a
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`software program, embedded program, or hardware functional unit, which initiates a
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`communicative interaction by the thin client 302 with other elements of the implementation 300.
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`Examples of host applications are a web browser, Microsoft Word™, or a specialized or other
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`stand-alone application.
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`10
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`In addition, the thin client 302 can include a target application (not shown) that receives a
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`translation (as hereafter described) of a query or command con-esponding to the input to the thin
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`client 302 and returns results (as hereafter described), including status messages, for example,
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`for display on the thin client 302. The target application can be included in or the same as, or
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`different or distinct from, the host application of the thin client 302. Several exemplary types of
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`15
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`target applications include database management system (DBMS) systems, word processors,
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`game programs, robots with sensors and feedback, toys, video cassette recorders (VCRs),
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`military equipment, and other machines and devices with software interfaces.
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`The thin client 302 can include various elements, including, for example, an input/output
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`display that the user can use to construct queries and commands and view results. The thin client
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`302 can be any of a variety of presently available and even future applications and devices, for
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`example, as simple as a web page with no onboard processing, where the query or command
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`then-input by the user plus choices for next inputs are displayed, or the thin client 302 can be
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`implemented using compiled, interpreted, or scripted languages such as CIC++, Java, or
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`Javascript. The thin client 302 can even be generated on-the-fly, such as by an interface
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`25
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`intermediary 312 hereafter discussed. Moreover, depending on the particulars of the
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`implementation 300, the thin client 302 can run or operate as an independent process or within
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`another environment (not shown), such as a web browser, or as a plug-in or extension within
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`another application (not shown).
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`The implementation 300 also includes an interface descriptor data source 304. The
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`30
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`interface descriptor data source is software or hardware that performs logical operations and
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`memory for locating and accessing one or more interface descriptors 306. Each interface
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`descriptor 306 is a data structure that describes a guided interface, such as a NLI, of the
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`implementation 300. For example, the interface descriptor for the particular guided interface can
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`have the format:
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`<LL properties, grammar, lexicon, portable specification, experts, translations>.
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`Of course, other formats are possible to achieve the same objective of describing the particular
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`5
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`guided interface .that is appropriate to the implementation 300, for the particular user and thin
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`client 302.
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`In operation of the implementation 300, the interface descriptor 306 (or a reference,
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`direct or indirect, to the interface descriptor) is found, located, derived, or otherwise presented or
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`obtained by the interface descriptor data source 304. For example, the interface descriptor data
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`10
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`source 304 can obtain the interface descriptor 306 on a web page or possibly from the interface
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`descriptor data source 304, itself. The interface descriptor data source 304, upon locating or
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`otherwise obtaining the relevant interface descriptor 306 makes the interface descriptor 306
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`available to the implementation 300, such as by sending the interface descriptor 306 (or a
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`reference or handle to it) to a parser farm 308 in order to initialize an appropriate parser 310, as
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`15
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`hereinafter further detailed. Exemplary types of the interface descriptor data source include
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`traders, databases, search engines, and other logical operators and applications.
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`An interface intermediary 312 also is included in the implementation 300. The interface
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`intermediary 312 interacts with the thin client 302, the interface descriptor data source 304, and
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`the parser farm 308 and parser 310. The interface intermediary 312 functions to directly interact
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`20 with the parser 310, including by receiving next items to display as dictated by the parser 310
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`and preparing displays dictated by the parser 310 for the thin client 302. The interface
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`intermediary also receives selections from the thin client 302 based on input thereto and
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`generations by the thin client 302, and delivers or returns these to the parser 310. The interface
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`intermediary 312 can be part of or inherent in the thin client 302 and its operations or,
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`25
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`alternatively, separate from the thin client 302 at the location of the thin client 302 (such as a
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`peripheral or application to the thin client 302), on a separate, disparate server device, or
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`otherwise. Location of the interface intermediary separate and distinct from the thin client 302
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`lessens download burdens and processing requirements of the thin client 302.
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`The parser farm 308 of the implementation 300 serves to manage one or more of the
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`30
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`parsers 310 available to the thin client 302 via the interface descriptor data source 304 and
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`interface intermediary 312. Th~ parser fam1 308 manages the parsers 310 as a database or other
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`access source, either by assigning or dictating use of an existing parser 310 of or available to the
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`parser farm 308 or by creating or generating a new parser 310 and assigning or dictating use of
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`the new parser 310 for the implementation 300 and its operation. The parser farm 308 can, for
`
`example, make available for use the new parser 310, by returning to the implementation 300 an
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`applicable handle or other locater for the parser 310.
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`The parser 310 of the implementation is a program or other sequence of steps or logical
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`5
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`operations that receives input in the form of sequential source program instructions, interactive
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`online commands, markup tags, or some other defined interface and breaks them into parts (for
`
`example, the nouns (objects), verbs (methods), and their attributes or options) that can then be
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`managed by other programming or elements (for example, other components of an application or
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`device). The parser 310 can also check to see that all input has been provided that is necessary.
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`10
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`fu the implementation 300, the parser 310 is initialized based on the interface descriptor 306
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`from the interface descriptor data source 304. Once the parser 310 is so initialized, the parser
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`310 generates a choice list, accepts a choice, and iterates. The parser 310 can, but need not
`
`necessarily, operate by creating a parse tree, as is common. fu