Navdeep S Dhillon

7398201, Jul 8, 2008

Feb 19, 2003

10/371399

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

Evri Inc. - Seattle WA

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

704 9, 707102, 707 3

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.

7526425, Apr 28, 2009

Dec 13, 2004

11/012089

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

Evri Inc. - Seattle WA

G06F 17/27
G06F 17/30

704 9, 707 1, 707102

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.

7881931, Feb 1, 2011

Feb 4, 2008

12/025373

Maxwell Wells - Seattle WA, US
Vidya Venkatachalam - Bellevue WA, US
Luca Cazzanti - Bellevue WA, US
Kwan Fai Cheung - Bellevue WA, US
Navdeep Dhillon - Seattle WA, US
Somsak Sukittanon - Seattle WA, US

Gracenote, Inc. - Emeryville CA

G10L 15/06

704243, 704245

Copies of original sound recordings are identified by extracting features from the copy, creating a vector of those features, and comparing that vector against a database of vectors. Identification can be performed for copies of sound recordings that have been subjected to compression and other manipulation such that they are not exact replicas of the original. Computational efficiency permits many hundreds of queries to be serviced at the same time. The vectors may be less than 100 bytes, so that many millions of vectors can be stored on a portable device.

7953593, May 31, 2011

Mar 10, 2009

12/401386

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

Evri, Inc. - Seattle WA

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

704 9, 707707, 707708, 707759, 707771

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.

8131540, Mar 6, 2012

Mar 10, 2009

12/401421

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

Evri, Inc. - Seattle WA

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

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

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.

8326584, Dec 4, 2012

Apr 21, 2000

09/556086

Maxwell J. Wells - Seattle WA, US
David Waller - Goleta CA, US
Navdeep S. Dhillon - Seattle WA, US

Gracenote, Inc. - Emeryville CA

G06F 17/10

703 2

A method for characterizing a musical recording as a set of scalar descriptors, each of which is based on human perception. A group of people listens to a large number of musical recordings and assigns to each one many scalar values, each value describing a characteristic of the music as judged by the human listeners. Typical scalar values include energy level, happiness, danceability, melodicness, tempo, and anger. Each of the pieces of music judged by the listeners is then computationally processed to extract a large number of parameters which characterize the electronic signal within the recording. Algorithms are empirically generated which correlate the extracted parameters with the judgments based on human perception to build a model for each of the scalars of human perception. These models can then be applied to other music which has not been judged by the group of listeners to give to each piece of music a set of scalar values based on human perception. The set of scalar values can be used to find other pieces that sound similar to humans or vary in a dimension of one of the scalars.

8594996, Nov 26, 2013

Oct 15, 2008

12/288158

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

Evri Inc. - Seattle WA

G06F 17/27

704 9, 704 10, 707737

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.

8645125, Feb 4, 2014

Mar 30, 2011

13/075799

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

Evri, Inc. - Seattle WA

G06F 17/27

704 9, 704257, 704251

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.