Case 1:15-cv-00262-SLR Document 1-1 Filed 03/25/15 Page 2 of 10 PageID #: 13
`111111
`1111111111111111111111111111111111111111111111111111111111111
`US00660410IBI
`
`(12) United States Patent
`Chan et ai.
`
`(10) Patent No.:
`(45) Date of Patent:
`
`US 6,604,101 Bl
`Aug. 5, 2003
`
`(54)
`
`METHOD AND SYSTEM FOR
`TRANS LINGUAL TRANSLATION OF QUERY
`AND SEARCH AND RETRIEVAL OF
`MULTILINGUAL INFORMATION ON A
`COMPUTER NETWORK
`
`(75)
`
`Inventors: Ning-Ping Chan, EI Cerrito, CA (US);
`Xiong Zhenghui, Baixiang (CN); Liu
`Zhuo, Shekeyuan Sushe (CN); Xiwen
`Ma, Redwood City, CA (US)
`
`(73) Assignee: qNaturally Systems, Inc., EI Cerritos,
`CA(US)
`
`( *) Notice:
`
`Subject to any disclaimer, the term of this
`patent is extended or adjusted under 35
`U.S.c. 154(b) by 201 days.
`
`(21) Appl. No.: 09/606,655
`
`(22) Filed:
`
`Jun. 28, 2000
`
`Int. CI? ................................................ G06F 17/30
`(51)
`(52) U.S. CI. ................................................ 707/4; 704/2
`(58) Field of Search ................... 707/4, 10, 5; 709/231;
`704/8, 2; 711/118
`
`(56)
`
`References Cited
`
`U.S. PATENT DOCUMENTS
`
`..... 364/419.03
`1/1995 Stentiford et al.
`5,384,701 A
`12/1995 Takeda et al.
`......... 364/419.02
`5,477,450 A
`10/1997 Carbonell et al.
`..... 364/419.02
`5,677,835 A
`12/1997 Hobson et al.
`............. 395/336
`5,694,559 A
`2/1999 Liddy et al. ................... 704/9
`5,873,056 A
`4/1999 Chen .......................... 707/535
`5,893,133 A
`5,956,740 A * 9/1999 Nosohara .................... 715/536
`5,963,940 A
`10/1999 Liddy et al. ................... 707/5
`5,987,402 A
`11/1999 Murata et al.
`................. 704/2
`5,995,934 A
`11/1999 Tang .......................... 704/270
`5,999,951 A * 12/1999 Shibuya ...................... 715/536
`12/1999 Tou ... ... ... ..... ... ... ... ..... ... 704/2
`6,002,997 A
`6,006,221 A * 12/1999 Liddy et al. ................... 707/5
`6,024,571 A * 2/2000 Renegar ..................... 434/157
`6,055,528 A
`4/2000 Evans
`........................... 707/3
`6,064,951 A * 5/2000 Park et al. ..................... 704/8
`
`6/2000
`6/2000
`7/2000
`9/2000
`10/2000
`* 10/2000
`12/2000
`1/2001
`2/2002
`
`......... 715/513
`Nishikawa et al.
`de Hita et al. .................. 704/9
`Kurachi et al. ................ 704/3
`Kobayakawa et al. ... ... ... 704/3
`Slutz ............................. 707/2
`Carbonell et al.
`............. 704/2
`Goldberg et al.
`... ..... ... ... 704/3
`Levin et al.
`................... 707/5
`Redpath ...................... 707/10
`
`6,073,143 A *
`6,081,774 A
`6,092,035 A
`6,119,078 A
`6,138,112 A
`6,139,201 A
`6,161,082 A
`6,173,279 B1 *
`6,347,316 B1 *
`* cited by examiner
`Primary Examiner~afet Metjahic
`Assistant Examiner~ana AI-Hashemi
`(74) Attorney, Agent, or Firm-Oppenheimer Wollf &
`Donnelly LLP
`
`(57)
`
`ABSTRACT
`
`A method for translating a query input by the user in the
`source language into the target language and searching and
`retrieving web documents in the target language and trans(cid:173)
`lating the web documents into the source language. In this
`invention, the user first inputs a query in a source language
`through a unit such as the keyboard. This query is then
`processed by the server at the backend to extract content
`word from the input query. The next step takes place at the
`dialectal controller, which is present on the server and
`performs the function of dialectally standardizing the con(cid:173)
`tent word/words so extracted. During this process the user
`may be prompted for some more so as to refine the search
`by the user or in case dialectal standardization could not be
`performed using the initial input query. This is followed by
`the process of pre-search translation, which comprises of
`translating the dialectally standardized word into a target
`language through a translator. This process of translation is
`followed by inputting the translated word into a search
`engine in the target language. Such an input yields search
`results in the target language corresponding to the translated
`word. The results so obtained are then displayed in the form
`of site names (URL) which satisfy the search criteria. All the
`results thus obtained in the target language are then dis(cid:173)
`played on the user screen. According to the user's needs
`such results may then be translated back either in whole or
`in part into the source language.
`
`28 Claims, 3 Drawing Sheets
`
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`Case 1:15-cv-00262-SLR Document 1-1 Filed 03/25/15 Page 3 of 10 PageID #: 14
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`u.s. Patent
`
`Aug. 5, 2003
`
`Sheet 1 of 3
`
`US 6,604,101 Bl
`
`104
`
`Dialectal
`Controller
`
`Query Prompter
`
`Translator
`
`112
`
`Search Engine
`
`Internet
`
`FIG. 1
`
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`Case 1:15-cv-00262-SLR Document 1-1 Filed 03/25/15 Page 4 of 10 PageID #: 15
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`u.s. Patent
`
`Aug. 5, 2003
`
`Sheet 2 of 3
`
`US 6,604,101 Bl
`
`User
`
`Translated output in
`target language
`
`Query input in source
`language
`
`Input to search engine
`in target language
`
`Keyword identification
`
`Output of search result
`
`Dialectal
`standardization
`
`( 124
`
`Dialectally standardized
`output for identified
`keyword
`
`Query prompter
`prompts user for
`input/to sharpen
`query
`
`( 126
`
`Input of dialectally
`standardized output to
`translator
`
`Translation of search
`results to source
`language
`
`W ell-translated sites
`
`Machine translation
`with reading aids
`
`Translated search
`results in source
`language
`
`FIG. 2
`
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`Case 1:15-cv-00262-SLR Document 1-1 Filed 03/25/15 Page 5 of 10 PageID #: 16
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`u.s. Patent
`
`Aug. 5, 2003
`
`Sheet 3 of 3
`
`US 6,604,101 Bl
`
`Dialectal controller
`uses logic to identify
`keyword
`
`154
`
`Apply dialectal
`standardization logic to
`standardize keyword
`
`eed machine(cid:173)
`translated site
`with reading ai
`?
`
`No
`
`172
`
`176
`
`Machine translate
`all or one site to
`source language
`
`Select a site and browse
`in source language
`
`162
`
`Obtain search results in
`target language
`
`I---------~
`
`Translate standardized
`keyword to target
`language
`
`160
`
`Use translated output to
`perform search in target I----~
`language
`
`Select any site and
`browse ill target
`language
`
`FIG. 3
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`Case 1:15-cv-00262-SLR Document 1-1 Filed 03/25/15 Page 6 of 10 PageID #: 17
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`US 6,604,101 B1
`
`1
`METHOD AND SYSTEM FOR
`TRANS LINGUAL TRANSLATION OF QUERY
`AND SEARCH AND RETRIEVAL OF
`MULTILINGUAL INFORMATION ON A
`COMPUTER NETWORK
`
`BACKGROUND OF THE INVENTION
`1. Field of the Invention
`This invention relates generally to translation of query
`and retrieval of multilingual information on the web and
`more particularly to a method and system for conducting a
`translingual search on the Internet and accessing multilin(cid:173)
`gual web sites through dialectal standardization, pre-search
`translation and post-search translation.
`2. Description of Prior Art
`The World Wide Web is a fast expanding terrain of
`information available via the Internet. The sheer volume of
`documents available on different sites on the World Wide
`Web ("Web") warrants that there be efficient search tools for
`quick search and retrieval of relevant information. In this
`context, search engines assume great significance because of
`their utility as search tools that help the users to search and
`retrieve specific information from the Web by using
`keywords, phrases or queries.
`A whole array of search tools is available these days for 25
`users to choose from in conducting their search. However,
`search tools are not all the same. They differ from one
`another primarily in the manner they index information or
`web sites in their respective databases using a particular
`algorithm peculiar to that search tool. It is important to know 30
`the difference between the various search tools because
`while each search tool does perform the common task of
`searching and retrieving information, each one accomplishes
`the task differently. Hence, the difference in search results
`from different search engines even though the same phrases/ 35
`queries are inputted.
`Search tools of different kinds fall broadly into five
`categories, which are as follows:
`1. directories;
`2. search engines;
`3. super engines;
`4. meta search engines; and
`5. special search engines.
`Search tools like Yahoo, Magellan and Look Smart 45
`qualify as web directories. Each of these web directories has
`developed its own database comprising of selected web
`sites. Thus, when a user uses a directory like Yahoo to
`perform a search, he/she is searching the database main(cid:173)
`tained by Yahoo and browsing its contents.
`Search engines like Infoseek, Webcrawler and Lycos use
`software such as "spiders" and "robots" that crawl around
`the Web and index, and catalogue the contents from different
`web sites into the database of the search engine itself.
`A more sophisticated class of search engines includes 55
`super engines, which use a similar kind of software as
`"robots" and "spiders." However, they are different from
`ordinary search engines because they index keywords
`appearing not only on the title but anywhere in the text of a
`site content. Hot Bot and Altavista are examples of super 60
`engines.
`Search engines further include meta search engines,
`which consist of several search engines. A user using a meta
`search engine actually browses through a whole set of search
`engines contained in the database of the meta search engine.
`Dogpile and Savvy Search are examples of meta search
`engines.
`
`5
`
`2
`Special search engines are another type of search engines
`that cater to the needs of users seeking information on
`particular subject areas. Deja News and Infospace are
`examples of special search engines.
`Thus, each one of these search tools is unique in terms of
`the way it performs a search and works towards fulfilling the
`common goal of making resources on the web available to
`users.
`However, most of these search engines are limited in their
`10 scope in so far as most of these search engines cater to the
`needs of the English speaking community alone and help in
`the search and retrieval of monolingual documents only.
`Most of these search engines require input in English and
`search web sites that have information available in English
`only. In other words, most of the search tools cater primarily
`15 to the needs of the English speaking Internet user. This
`attribute renders these search tools almost useless to the
`non-English speaking Internet users who constitute as much
`as 75% of the Internet user population. This non-English
`speaking user community is unable to search English web
`20 sites since it cannot adequately input phrases or queries in
`English. Consequently, this community of users is unable to
`benefit from the search tools and web documents available
`in English. This is a serious drawback, which has not been
`addressed by any of the existing search engines.
`Likewise, the non-English speaking Internet users also
`create web sites to store information in non-English lan(cid:173)
`guages. This rich source of information is not available to
`query by English oriented search engines. As a result the
`English speaking population remains deprived of the
`resources available in the other languages of the world for
`the same reasons as discussed above.
`As an example, when preparing a Chinese To-fu dish
`which calls for "shrimp caviare," a search was made on a
`super engine, such as Altavista.com to check the availability
`of "shrimp caviare" anywhere in the world. A search using
`Altavista.com under "all language" revealed no matching
`results under either "English" or "Chinese" setting. A search
`was then made for the English term "shrimp caviare" at
`China. com, which is a Chinese search engine, but to no
`40 avail. Subsequently, the term "shrimp caviare" was looked
`up in Chinese to find its Chinese equivalent. The Chinese
`equivalent thus found was "xiazi" (meaning, "shrimp roe").
`This word was then used for making the search on China-
`.com and yielded as many as twenty-four hits.
`Thus, a need exists for a translingual search engine with
`a built-in translator. Such a system should be capable of
`standardizing the query or phrase input by the user to a
`commonly known word and then translating the same into a
`target language prior to a search for sites that satisfies the
`50 search criteria. Such a system should be capable of inputting
`the translated keyword into a search engine of the target
`language to yield search results. Further, for convenience of
`the user, the system should be capable of translating the
`search results obtained in the target language back into the
`source language.
`Such a system will help the users to transcend language
`barriers while making a search on the web. Such a system
`also obviates the need to manually and unsystematically find
`out the translated equivalent of a word in another language
`prior to conducting a search in that language.
`Such a system will go a long way in transcending all
`language barriers and improving inter-human communica(cid:173)
`tion. This will not only pave the way for a healthier
`interactive environment and cultural exchange but also help
`65 in an optimal utilization of available resources on the Web.
`There are some web sites, which offer translation services,
`but such sites merely create an illusion of multilingual
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`US 6,604,101 B1
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`5
`
`3
`search and information retrieval. What these sites offer in
`effect are machine translation services. Machine translation
`services are services that provide a literal translation of the
`words queried by users. Such translations are often found to
`be unintelligible and incomprehensible and as a result fall
`short of fulfilling any meaningful objective of users.
`Systems have also been developed which attempt to
`transform a query input by the user in the native language
`also referred to as source language into a resulting language
`also referred to as a target language and provide as many 10
`translations as possible in the target language. The idea is to
`have such a transformed query ready for use in any of the
`available information retrieval systems.
`However, this system is similar to the other search tools
`discussed earlier that fail to placate the long standing need 15
`for a one stop shop for users to dialectally standardize a user
`query to a more commonly known word and then translate
`this standardized word intelligently to the target language
`prior to search. Such a tool being also capable of conducting
`a search in the target language through the input of the 20
`translated keyword into a search engine of the target lan(cid:173)
`guage and producing search results, and even generating
`translations of the search results in the source language.
`
`4
`Once the search results are made available to the user, the
`user has a set of available options. The user may either
`browse the search results in the target language or request
`that the search results obtained in the target language be
`translated into the source language. The user may further
`specify whether the entire search results or just portions of
`it need to be translated. This can be done by merely
`highlighting the portions of the search results desired to be
`translated and then entering the appropriate command.
`The user may also specify as to what kind of a translation
`is required by the user depending on his/her needs i.e
`whether a simple machine translation with reading aids will
`be sufficient or a more intelligible translation of the search
`results and the contents of those web sites is desired.
`An alternative embodiment of the present invention may
`also be used with a query prompter on the server so that in
`cases where the initial query entered by the user is insuffi(cid:173)
`cient for dialectal standardization, more input is solicited by
`the query prompter from the user to help standardize the
`words into acceptable and known words in the target lan(cid:173)
`guage.
`One advantage of the present invention is to provide a
`method and a system that dialectally standardizes the key-
`25 word or query input by the user to a more commonly known
`and/or used term. Dialectal standardization is distinctly
`helpful because standardizing the word to a commonly
`known word insures that the target language search engine
`will recognize it.
`Another advantage of the present invention is to provide
`a method and system that translates intelligently the stan(cid:173)
`dardized keyword or query input by the user in a source
`language into a target language.
`Yet another advantage of the invention is that it provides
`an option to the users to have the search results retrieved in
`the target language to be translated back into the source
`language.
`The foregoing and other objects, features and advantages
`of the invention will be apparent from the following detailed
`description of the preferred embodiment, which makes ref(cid:173)
`erence to the drawings.
`
`SUMMARY OF THE INVENTION
`One object of the present invention is to provide a method
`and a system that dialectally standardizes the keyword or
`query input by the user to a more commonly known and/or
`used term. Dialectal standardization is distinctly helpful
`because standardizing the word to a commonly known word 30
`insures that the search engine of the target language will
`recognize it.
`Another object of the present invention is to provide a
`method and system that translates intelligently the standard(cid:173)
`ized keyword or query input by the user in a source language 35
`into the target language.
`Yet another object of the invention is to provide an option
`to the users to have the search results retrieved in the target
`language to be translated back into the source language.
`A method for dialectally standardizing a query input by 40
`the user in the source language and then translating the
`standardized keyword to the target language and searching
`and retrieving web documents in the target language as well
`as providing translations of said search results into the
`source language.
`In this method, the user first inputs a query in the source
`language through a unit such as the keyboard. This query is
`then processed by the server at the backend to extract
`content word from the input query. The next step takes place
`at the dialectal controller, which performs the function of 50
`dialectally standardizing the content word/words extracted
`from the input query. This insures that the keyword is
`standardized to a commonly known word/term. At this stage,
`the user may be prompted for some more input so as to refine
`the search or to perform dialectal standardization where the 55
`initial input phrase by the user was insufficient to perform
`Dialectal Standardization.
`Thereafter, the dialectally standardized word is inputted
`into a translator to translate the dialectally standardized
`word into the target language. This process of translation 60
`that takes place prior to a search is known as pre-search
`engine translation. Following translation, the translated
`word is input into a search engine in the target language.
`Such an input yields search results in the target language that
`satisfy the search criteria. The results so obtained are then 65
`displayed in the form of site names (URL) on the user's
`screen.
`
`BRIEF DESCRIPTION OF THE DRAWINGS
`
`FIG. 1 is a schematic representation of one embodiment
`45 of the general overview of the system for translingual
`translation of query and search and retrieval of multilingual
`web documents;
`FIG. 2 is a schematic diagram of the different steps
`involved in the process of translingual translation of query
`and search and retrieval of multilingual web documents; and
`FIG. 3 is a flow diagram illustrating the processing of
`query input by a user in the source language, dialectal
`standardization of the input query, translation of the stan(cid:173)
`dardized wordlkeyword into a target language and obtaining
`search results in the target language and translation of search
`results into the source language.
`
`DETAILED DESCRIPTION OF THE
`INVENTION
`
`The invention incorporates a new and unique methodol(cid:173)
`ogy and system for translingual translation of query and
`search and retrieval of multilingual web documents. Such a
`system enables a user to access web documents in a target
`language other than his/her own source language with the
`option of having these web documents translated back either
`in part or in whole into the source language.
`
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`US 6,604,101 B1
`
`6
`PRE-SEARCH TRANSLATION
`
`According to a preferred embodiment of the present
`invention, the dialectally standardized output for the iden(cid:173)
`tified keyword is input 126 into the translator. The translator
`translates the standardized keyword into an equivalent in a
`target language and gives an output in the target language
`130, such target language having been pre-selected by the
`user prior to the translation stage. In one embodiment, a
`pre-determined target language can be selected as a default
`target language. The output so obtained in the target lan-
`guage is then fed into a search engine of the target language
`132. This input sets the search engine into motion and the
`search engine begins searching for sites related to that
`particular keyword and provides an output of search results
`134. The search results obtained following the search are
`displayed as search results on the screen 115 of the user. The
`search results obtained may be of many different kinds such
`as titles/catalogs along with their URL links or actual web
`20 sites or web pages with contents or even subpages with title
`along with their URL links. The search results obtained may
`be any or all of these.
`
`15
`
`5
`Broadly speaking, the process and system embodied by
`the invention take place in three stages: dialectal
`standardization, pre-search engine translation and post
`search engine translation.
`FIG. 1 is a schematic representation of one embodiment 5
`of the general overview of the system for translingual
`translation of query and search and retrieval of multilingual
`web documents.
`As illustrated in FIG. 1, a query input unit 100 is present
`on the computer used by a user. The query input unit has a 10
`query input device 102 such as a keyboard. The query input
`unit is connected to a server 104 which has at least three
`units, namely, a dialectal controller 106, a query prompter
`108 and a translator 110. The server 104 is connected to a
`search engine 112, which in turn is connected to the Internet
`114.
`FIG. 2 is a schematic diagram of the different steps
`involved in the process of translingual translation of query
`and search and retrieval of multilingual web documents. The
`different steps take place in the three stages of dialectal
`standardization, pre-search translation and post-search
`translation.
`DIALECTAL STANDARDIZATION
`According to a preferred embodiment of the present
`invention, as illustrated in FIG. 2, a user 116 inputs a query 25
`in the source language 118 through an input device such as
`a keyboard. The query is received by a dialectal controller
`which processes the query and identifies a keyword from the
`query input 120. The dialectal controller extracts content
`word out of the query. The next step involves dialectal 30
`standardization 122, wherein the dialectal controller at
`server backend picks up the keyword and standardizes it to
`a commonly known word and/or term. This is done to bring
`about a consistency in the meaning of a word notwithstand(cid:173)
`ing dialectal variations.
`Dialectal standardization is an important step because
`often times words encountered have several different dia(cid:173)
`lectal variations. A language such as English itself is full of
`dialectal variations in the form of British English and
`American English to name a few. Good examples of dia- 40
`lectal variations in these two dialects of English include
`centre vs. center, lorry vs. truck, queue vs. line and petrol vs.
`gasoline etc. Similar instances could be cited in many of the
`other languages of the world, too. In Chinese, for instance
`there are as many as 41 different dialectal variations for just 45
`one particular word. Such instances corroborate the fact that
`dialectal variations are the rule rather than the exception and
`therefore the only way to counter them is by standardizing
`a query or a word to a commonly known word.
`In particular, the importance of dialectal standardization 50
`cannot be undermined in the present invention where the
`identified keyword needs to be given one consistent mean(cid:173)
`ing. Otherwise, a single inconsistency could result in a
`wrong translation and ruin the entire search process during
`subsequent stages of search and information retrieval.
`In a preferred embodiment of the present invention, if the
`dialectal controller fails to recognize the word and thus is
`unable to perform dialectal standardization, the query
`prompter unit may prompt the user for more input or request
`the user to choose from a set of expressions to assist, to 60
`clarify and to sharpen his/her query 128. In that case the user
`may submit another query to the query input device. Such a
`query may either be a standard term or a non-standard term.
`For instance, different variants of the word "auto" including
`automobile and transportation vehicle are permitted to be 65
`input by the user as part of the dialectal standardization
`process.
`
`POST- SEARCH TRANSLATION
`
`According to the preferred embodiment of this invention,
`the user now has access to the search results in the target
`language.
`Depending on the user's competence level and needs, the
`user may either choose to view the search results so obtained
`in the target language itself, or he/she may specify that the
`search results be translated in whole or in part into the source
`language.
`This can be done by the user by selectively highlighting
`the portions that he/she desires to be translated and by
`35 entering an appropriate command or selecting an appropriate
`option. In accordance with a preferred embodiment of the
`present invention, if the user chooses to have a post-search
`translation 136 of the search results from target language to
`source language, the user has two available options.
`The user can choose between having a machine transla(cid:173)
`tion 138 of the web sites into the source language, such
`translation being available with reading aids. Alternatively,
`the user may choose a well translated version 140 of the site
`into the source language. The selection of a particular kind
`of translation by the user depends on hislher particular
`needs.
`For instance, users who are totally unfamiliar with the
`sites in the target language may opt for machine translations
`with reading aids so as to get an idea about the contents of
`the site in a broad manner. On the other hand, users whose
`needs warrant a more clear and unambiguous translation of
`the sites will prefer well-translated sites.
`After the user makes the selection of the kind of transla-
`55 tion required by himlher, the search results are translated to
`the source language and the translated results 142 are
`displayed as search results on the screen of the user. The
`search results obtained may be of many different kinds such
`as titles/catalogs along with their URL links or actual web
`sites or web pages with contents or even sub pages with title
`along with their URL links. The search results obtained may
`be any or all of these and the user may opt to have any or
`all of these search results translated.
`According to one embodiment of the present invention,
`the user may choose to have any or all of these different
`kinds of search results translated into the source language if
`he/she so desires.
`
`AOL Ex. 1003
`Page 7 of 9
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`Case 1:15-cv-00262-SLR Document 1-1 Filed 03/25/15 Page 9 of 10 PageID #: 20
`
`US 6,604,101 B1
`
`7
`FIG. 3 is a flow diagram illustrating the processing of the
`query submitted in the source language, dialectal standard(cid:173)
`ization of the keyword, translation of the standardized
`keyword into the target language, search and retrieval of
`information and post-search translation. The process begins 5
`with the selection of a target language by the user 144. This
`is followed by an input of a query in a source language 146
`by the user. The query so input is received by the server 148.
`If the server finds the query acceptable 150, the query is sent
`to the dialectal controller for processing. The dialectal 10
`controller uses processing logic to identify the keyword 152.
`Statistical data in conjunction with syntactic analysis pro(cid:173)
`vides the foundation for the processing logic so as to include
`and exclude certain kind of verbal entries. Thereafter, the
`dialectal controller applies dialectal standardization logic to
`standardize keyword 154. Such a logic is used so as to 15
`standardize the keyword to a commonly known word/term.
`If the standardization 156 is successful, the standardized
`word is input into a translator for translation of the stan(cid:173)
`dardized keyword into the target language 158. This step is
`followed by the input of this translated keyword into the 20
`search engine of the target language to perform search in the
`target language 160. This search yields results in target
`language 162 satisfying the search criteria. Depending on
`the user's competency level and needs, the user may choose
`to access the displayed search results in the target language 25
`itself 164 or alternatively, the user may have the results of
`the search translated in whole or in part into the source
`language 166.
`In the event that the user chooses to have a post search
`translation, the user is provided with two options. The user 30
`can choose from either a machine translation of the web sites
`into the source language or a well translated version of the
`sites in the source language.
`If the user opts for a well translated site 168, the well(cid:173)
`translated version of the search results will be obtained from 35
`the collection of well-translated sites indexed in the database
`of the search engine 170. The database has a huge selection
`of well-translated sites, which are constantly updated so that
`users may have access to newer web documents. The user
`may then select a site and browse it in the source language 40
`174.
`The user's choice of the kind of translation desired
`depends on his/her particular needs. For instance, users who
`are totally unfamiliar with the sites in the target language
`may opt for machine translations with reading aids 172 so as 45
`to get an idea about the contents of the site in a broad
`manner. On the other hand, users whose needs warrant a
`more clear and unambiguous translation of the sites will
`prefer well-translated sites. If the user opts for a machine
`translation of web sites, such machine translation is done by 50
`the server 176 and displayed as translated search results to
`the user who may then select a site and browse it in the
`source language 174.
`Whereas the present invention may be embodied in many
`forms, details of a preferred embodiment are schematically 55
`shown in FIGS. 1 through 3, with the understanding that the
`present disclosure is not intended to limit the invention to the
`embodiment illustrated. While the invention has been par(cid:173)
`ticularly shown and described with reference to certain
`embodiments, it will be understood by those skilled in the art 60
`that various alterations and modifications in form and detail
`may be made therein. Accordingly, it is intended that the
`following claims cover all such alterations and modifications
`as fall within the true spirit and scope of the invention.
`What is claimed is:
`1. A method for performing a contextual search and
`retrieval of documents in a computer network, comprising:
`
`65
`
`8
`recelvmg through an input device, a query in a first
`language;
`processing said query to extract at least one content word
`from the query;
`performing dialectal standardization of the at least one
`content word extracted from the query;
`translating the at least one dialectally standardized content
`word into a second language through a translator;
`performing a contextual search in the second language
`based on the at least one translated content word, u