Xin Grace Li, 56Foster City, CA

7206281, Apr 17, 2007

May 3, 2002

10/138853

Wen Chen - San Jose CA, US
Xin Li - Santa Clara CA, US
Makarand S. Bhatambarekar - San Jose CA, US

Ciena Corporation - Linthicum MD

G01R 31/08

370222, 3702381

A system operating on a communication network for mapping service-level information comprising logical connections to physical-level information comprising working physical paths of the logical connections, where the physical-level information is obscured by activation of protect schemes within the communication network.

7283466, Oct 16, 2007

Oct 25, 2002

10/280896

Wen Chen - San Jose CA, US
Xin Li - San Jose CA, US
Makarand Bhatambarekar - San Jose CA, US

Ciena Corporation - Linthicum MD

G01R 31/08

370225, 370242

A method and system for tracking physical route changes in an optical switching network. One embodiment comprises a method for detecting changes in physical routes of connections within an optical switching network. The method includes receiving an event message from a node of the optical switching network where the event message relates to an event at the node, applying a filtering function to the event message to determine whether the event message may be ignored, ignoring the event message if the event message does not pass the filtering function, and processing the event message if the event message passes the filtering function.

7487486, Feb 3, 2009

Jun 11, 2005

11/629445

Mustafa Celik - Santa Clara CA, US
Jiayong Le - Mountain View CA, US
Lawrence Pileggi - Pittsburgh PA, US
Xin Li - Pittsburgh PA, US

G06F 17/50
G06F 7/60
G06F 7/52

716 6, 716 4, 716 5, 703 2, 708607

The large-scale process and environmental variations for today's nano-scale ICs are requiring statistical approaches for timing analysis and optimization (). Significant research has been recently focused on developing new statistical timing analysis algorithms (), but often without consideration for how one should interpret the statistical timing results for optimization. The invention provides a sensitivity-based metric () to assess the criticality of each path and/or arc in the statistical timing graph (). The statistical sensitivities for both paths and arcs are defined. It is shown that path sensitivity is equivalent to the probability that a path is critical, and arc sensitivity is equivalent to the probability that an arc sits on the critical path. An efficient algorithm with incremental analysis capability () is described for fast sensitivity computation that has a linear runtime complexity in circuit size. The efficacy of the proposed sensitivity analysis is demonstrated on both standard benchmark circuits and large industry examples.

7630978, Dec 8, 2009

Dec 14, 2006

11/639492

Xin Li - Sunnyvale CA, US
Nawaaz Ahmed - San Francisco CA, US
Fuchun Peng - Sunnyvale CA, US
Yumao Lu - Santa Clara CA, US

Yahoo! Inc. - Sunnyvale CA

G06F 17/30

707 5, 707 3

Techniques for rewriting queries submitted to a query engine are provided. A query is submitted by a user and sent to a search mechanism. Based on the query, one or more query suggestions are generated. Features are generated based on the query and the query suggestions. Those features are input to a trained machine learning mechanism that generates a rewrite score. The rewrite score signifies a confidence score that indicates how confident the search mechanism is that the user intended to submit the original query. If the rewrite score is below a certain threshold, then the original query is rewritten to a second query. Results of executing the original query may be sent to the user along with a reference to the second query. Additionally or alternatively, results of executing the second query are sent to the user.

7693865, Apr 6, 2010

Aug 30, 2006

11/514076

Yumao Lu - Santa Clara CA, US
Fuchun Peng - Sunnyvale CA, US
Xin Li - Sunnyvale CA, US
Nawaaz Ahmed - San Francisco CA, US

Yahoo! Inc. - Sunnyvale CA

G06F 17/00

707102, 707200, 715738

To accurately classify a query as navigational, thousands of available features are explored, extracted from major commercial search engine results, user Web search click data, query log, and the whole Web's relational content. To obtain the most useful features for navigational query identification, a three level system is used which integrates feature generation, feature integration, and feature selection in a pipeline. Because feature selection plays a key role in classification methodologies, the best feature selection method is coupled with the best classification approach to achieve the best performance for identifying navigational queries. According to one embodiment, linear Support Vector Machine (SVM) is used to rank features and the top ranked features are fed into a Stochastic Gradient Boosting Tree (SGBT) classification method for identifying whether or not a particular query is a navigational query.

7949672, May 24, 2011

Jun 10, 2008

12/136279

Ya Zhang - Sunnyvale CA, US
Srinivas Vadrevu - Santa Clara CA, US
Belle Tseng - Cupertino CA, US
Gordon Guo-Zheng Sun - Redwood City CA, US
Xin Li - San Jose CA, US

Yahoo! Inc. - Sunnyvale CA

G06F 7/00
G06F 17/30

707767, 707769

A system for determining the intent of query that includes a search engine that receives a first search query, a query/click log module configured to store log data associated with the first search query; and a computational module that generates metric values associated with the first search query based on the log data and that determines that the first search query is one of a regional specific query or a global query based on the metric values, where the metric values reflect a likelihood of local intent of the first search query, and where the search engine provides search results selected in part based on the metric values.

7987195, Jul 26, 2011

Apr 8, 2008

12/099762

Xin Li - North Bergen NJ, US
Dolapo Falola - New York NY, US

Google Inc. - Mountain View CA

G06F 7/00
G06F 17/00

707765, 707769

A computer-implemented method includes providing location factors for first phrases in a collection of phrases, where each location factor for a first phrase is associated with a likelihood that a second phrase of a search query is associated with a location when the first phrase and the second phrase are used in the search query. A search query is received, where the received search query includes a first phrase from the collection of phrases and a second phrase. Whether the second phrase of the received search query refers to a location is determined based, at least in part, on the location factor for the first phrase of the search query.

8024342, Sep 20, 2011

Jul 31, 2008

12/183217

Xin Li - Sunnyvale CA, US
Lei Guo - San Jose CA, US
Eric Zhao - San Jose CA, US

Yahoo! Inc. - Sunnyvale CA

G06F 7/00

707736, 707750

The present invention is directed towards systems and methods for determining a tag match ratio. The method according to one embodiment of the present invention comprises selecting a content item, identifying one or more tags that are associated with the content item and determining a weight for each of the one or more tags associated with the content item. The method further comprises extracting one or more keywords from the content item. A tag match ratio for the one or more tags associated with the content item is then calculated and stored.