Lubos P Pochman

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.

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.

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.

US Patent:

20030233224, Dec 18, 2003

Filed:

Feb 19, 2003

Appl. No.:

10/371399

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
Carsten Tusk - Seattle WA, US
Navdeep Dhillon - Seattle WA, US
Lubos Pochman - Breckenridge CO, US

Assignee:

Insightful Corporation - Seattle WA

International Classification:

G06F017/28

US Classification:

704/004000

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. In this manner, the SQE is able to achieve more contextually accurate search results more frequently than using traditional search engines.