Jisheng Liang from Redmond, WA, age 52

Method And System For Enhanced Data Searching

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US Patent:

7398201, Jul 8, 2008

Filed:

Feb 19, 2003

Appl. No.:

10/371399

Inventors:

Giovanni B. Marchisio - Kirkland WA, US
Krzysztof Koperski - Seattle WA, US
Jisheng Liang - Bellevue WA, US
Alejandro Murua - Seattle WA, US
Thien Nguyen - Edmonds WA, US
Carsten Tusk - Seattle WA, US
Navdeep S. Dhillon - Seattle WA, US
Lubos Pochman - Breckenridge CO, US

Assignee:

Evri Inc. - Seattle WA

International Classification:

G06F 17/27
G06F 7/00
G06F 17/30

US Classification:

704 9, 707102, 707 3

Abstract:

Methods and systems for syntactically indexing and searching data sets to achieve more accurate search results and for indexing and searching data sets using entity tags alone or in combination therewith are provided. Example embodiments provide a Syntactic Query Engine (“SQE”) that parses, indexes, and stores a data set, as well as processes natural language queries subsequently submitted against the data set. The SQE comprises a Query Preprocessor, a Data Set Preprocessor, a Query Builder, a Data Set Indexer, an Enhanced Natural Language Parser (“ENLP”), a data set repository, and, in some embodiments, a user interface. After preprocessing the data set, the SQE parses the data set according to a variety of levels of parsing and determines as appropriate the entity tags and syntactic and grammatical roles of each term to generate enhanced data representations for each object in the data set. The SQE indexes and stores these enhanced data representations in the data set repository. Upon subsequently receiving a query, the SQE parses the query also using a variety of parsing levels and searches the indexed stored data set to locate data that contains similar terms used in similar grammatical roles and/or with similar entity tag types as indicated by the query.

Method And System For Extending Keyword Searching To Syntactically And Semantically Annotated Data

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US Patent:

7526425, Apr 28, 2009

Filed:

Dec 13, 2004

Appl. No.:

11/012089

Inventors:

Giovanni B. Marchisio - Kirkland WA, US
Krzysztof Koperski - Seattle WA, US
Jisheng Liang - Bellevue WA, US
Thien Nguyen - Edmonds WA, US
Carsten Tusk - Seattle WA, US
Navdeep S. Dhillon - Seattle WA, US
Lubos Pochman - Breckenridge CO, US
Matthew E. Brown - Seattle WA, US

Assignee:

Evri Inc. - Seattle WA

International Classification:

G06F 17/27
G06F 17/30

US Classification:

704 9, 707 1, 707102

Abstract:

Methods and systems for extending keyword searching techniques to syntactically and semantically annotated data are provided. Example embodiments provide a Syntactic Query Engine (“SQE”) that parses, indexes, and stores a data set as an enhanced document index with document terms as well as information pertaining to the grammatical roles of the terms and ontological and other semantic information. In one embodiment, the enhanced document index is a form of term-clause index, that indexes terms and syntactic and semantic annotations at the clause level. The enhanced document index permits the use of a traditional keyword search engine to process relationship queries as well as to process standard document level keyword searches. In one embodiment, the SQE comprises a Query Processor, a Data Set Preprocessor, a Keyword Search Engine, a Data Set Indexer, an Enhanced Natural Language Parser (“ENLP”), a data set repository, and, in some embodiments, a user interface or an application programming interface.

Method And System For Extending Keyword Searching To Syntactically And Semantically Annotated Data

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US Patent:

7953593, May 31, 2011

Filed:

Mar 10, 2009

Appl. No.:

12/401386

Inventors:

Giovanni B. Marchisio - Kirkland WA, US
Krzysztof Koperski - Seattle WA, US
Jisheng Liang - Bellevue WA, US
Thien Nguyen - Edmonds WA, US
Carsten Tusk - Seattle WA, US
Navdeep S. Dhillon - Seattle WA, US
Lubos Pochman - Breckenridge CO, US
Matthew E. Brown - Portland OR, US

Assignee:

Evri, Inc. - Seattle WA

International Classification:

G06F 17/27
G06F 17/30
G06F 7/00

US Classification:

704 9, 707707, 707708, 707759, 707771

Abstract:

Methods and systems for extending keyword searching techniques to syntactically and semantically annotated data are provided. Example embodiments provide a Syntactic Query Engine (“SQE”) that parses, indexes, and stores a data set as an enhanced document index with document terms as well as information pertaining to the grammatical roles of the terms and ontological and other semantic information. In one embodiment, the enhanced document index is a form of term-clause index, that indexes terms and syntactic and semantic annotations at the clause level. The enhanced document index permits the use of a traditional keyword search engine to process relationship queries as well as to process standard document level keyword searches. In one embodiment, the SQE comprises a Query Processor, a Data Set Preprocessor, a Keyword Search Engine, a Data Set Indexer, an Enhanced Natural Language Parser (“ENLP”), a data set repository, and, in some embodiments, a user interface or an application programming interface.

Method And System For Extending Keyword Searching To Syntactically And Semantically Annotated Data

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US Patent:

8131540, Mar 6, 2012

Filed:

Mar 10, 2009

Appl. No.:

12/401421

Inventors:

Giovanni B. Marchisio - Kirkland WA, US
Krzysztof Koperski - Seattle WA, US
Jisheng Liang - Bellevue WA, US
Thien Nguyen - Edmonds WA, US
Carsten Tusk - Seattle WA, US
Navdeep S. Dhillon - Seattle WA, US
Lubos Pochman - Breckenridge CO, US
Matthew E. Brown - Portland OR, US

Assignee:

Evri, Inc. - Seattle WA

International Classification:

G06F 17/27
G06F 7/00
G06F 17/30

US Classification:

704 9, 707713, 707731, 707759, 707791, 707794

Abstract:

Methods and systems for extending keyword searching techniques to syntactically and semantically annotated data are provided. Example embodiments provide a Syntactic Query Engine (“SQE”) that parses, indexes, and stores a data set as an enhanced document index with document terms as well as information pertaining to the grammatical roles of the terms and ontological and other semantic information. In one embodiment, the enhanced document index is a form of term-clause index, that indexes terms and syntactic and semantic annotations at the clause level. The enhanced document index permits the use of a traditional keyword search engine to process relationship queries as well as to process standard document level keyword searches. In one embodiment, the SQE comprises a Query Processor, a Data Set Preprocessor, a Keyword Search Engine, a Data Set Indexer, an Enhanced Natural Language Parser (“ENLP”), a data set repository, and, in some embodiments, a user interface or an application programming interface.

Nlp-Based Entity Recognition And Disambiguation

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US Patent:

8594996, Nov 26, 2013

Filed:

Oct 15, 2008

Appl. No.:

12/288158

Inventors:

Jisheng Liang - Bellevue WA, US
Krzysztof Koperski - Seattle WA, US
Navdeep S. Dhillon - Seattle WA, US
Carsten Tusk - Seattle WA, US
Satish Bhatti - Seattle WA, US

Assignee:

Evri Inc. - Seattle WA

International Classification:

G06F 17/27

US Classification:

704 9, 704 10, 707737

Abstract:

Methods and systems for entity recognition and disambiguation using natural language processing techniques are provided. Example embodiments provide an entity recognition and disambiguation system (ERDS) and process that, based upon input of a text segment, automatically determines which entities are being referred to by the text using both natural language processing techniques and analysis of information gleaned from contextual data in the surrounding text. In at least some embodiments, supplemental or related information that can be used to assist in the recognition and/or disambiguation process can be retrieved from knowledge repositories such as an ontology knowledge base. In one embodiment, the ERDS comprises a linguistic analysis engine, a knowledge analysis engine, and a disambiguation engine that cooperate to identify candidate entities from a knowledge repository and determine which of the candidates best matches the one or more detected entities in a text segment using context information.

Nlp-Based Systems And Methods For Providing Quotations

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US Patent:

8645125, Feb 4, 2014

Filed:

Mar 30, 2011

Appl. No.:

13/075799

Inventors:

Jisheng Liang - Bellevue WA, US
Navdeep Dhillon - Seattle WA, US
Krzysztof Koperski - Seattle WA, US

Assignee:

Evri, Inc. - Seattle WA

International Classification:

G06F 17/27

US Classification:

704 9, 704257, 704251

Abstract:

Techniques for providing quotations obtained from text documents using natural language processing techniques are described. Some embodiments provide a content recommendation system (“CRS”) configured to provide quotations by extracting quotations from a corpus text documents, and providing access to the extracted quotations in response to search requests received from users. The CRS may extract quotations by using natural language processing-based techniques to identify one or more entities, such as people, places, objects, concepts, or the like, that are referenced by the extracted quotations. The CRS may then store the extracted quotations along with identified entities, such as quotation speakers and subjects, for later access via search requests.

Keyword-Based Search Engine Results Using Enhanced Query Strategies

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US Patent:

8645372, Feb 4, 2014

Filed:

Oct 29, 2010

Appl. No.:

12/915213

Inventors:

Ted Diamond - Seattle WA, US
Jisheng Liang - Bellevue WA, US
Jonathan Reichhold - Seattle WA, US
Krzysztof Koperski - Seattle WA, US

Assignee:

Evri, Inc. - Seattle WA

International Classification:

G06F 7/00

US Classification:

707733, 707767

Abstract:

Enhanced computer- and network-based methods, systems, techniques are provided for retrieving more accurate and responsive search results when searching content for a designated entity using an off-the-shelf keyword-based search engine. For example, the embodiments described herein may be used to improve search results by eliminating off-topic results when presenting queries to an existing keyword-based search engine invoked by means of an API from an intermediating application. Example embodiments provide a Keyword-Based Search Enhancement System (“KBSES”), which enables intermediating applications to obtain information more closely related to user queries by enhancing such queries, on behalf of the user, with disambiguating information when deemed necessary. Based upon a variety of rules and heuristics, which can be modified as well, the KBSES determines whether an entity name in a user's query should be enhanced with additional disambiguating information, and to what extent, to prevent the retrieval of off-topic results.

Method And System For Enhanced Data Searching

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US Patent:

20040221235, Nov 4, 2004

Filed:

Nov 8, 2001

Appl. No.:

10/007299

Inventors:

Giovanni Marchisio - Kirkland WA, US
Krzysztof Koperski - Seattle WA, US
Jisheng Liang - Bellevue WA, US
Alejandro Murua - Seattle WA, US
Thien Nguyen - Edmonds WA, US

Assignee:

Insightful Corporation - Seattle 98109-3044

International Classification:

G06F015/00

US Classification:

715/534000

Abstract:

Methods and systems for syntactically indexing and searching data sets to achieve more accurate search results are provided. Example embodiments provide a Syntactic Query Engine ( SQE ) that parses, indexes, and stores a data set, as well as processes natural language queries subsequently submitted against the data set. The SQE comprises a Query Preprocessor, a Data Set Preprocessor, a Query Builder, a Data Set Indexer, an Enhanced Natural Language Parser ( ENLP ), a data set repository, and, in some embodiments, a user interface. After preprocessing the data set, the SQE parses the data set and determines the syntactic and grammatical roles of each term to generate enhanced data representations for each object in the data set. The SQE indexes and stores these enhanced data representations in the data set repository. Upon subsequently receiving a query, the SQE parses the query similarly and searches the indexed stored data set to locate data that contains similar terms used in similar grammatical roles. In this manner, the SQE is able to achieve more contextually accurate search results more frequently than using traditional search engines.