Yahoo! Inc.

Oath Inc.

Verizon Media Inc.

Verity, Inc.

Jinhui Liu

Wendell Craig Baker

Csaba Kecskemeti

Jonathan Malkin

Jerry Zhang

Jianchang Mao

Alpha Kamchiu Luk

Sumit Taank

Zengyan Zhang

Christina Yip Chung

George E Mavromatis

Vamsi Vutukuru

An electronic system may be configured to determine if a first-type device ID and a second-type device ID both identify a same device. To do so, the electronic system may preliminarily group a particular first-type ID with a particular second-type ID based on matching time slots and network addresses. Individual scores for each of the preliminary groups may be determined based on cardinalities associated with the time slots. Combined scores may then be determined for groups having the same first-type device ID and second-type device ID. A final analysis may be performed to confirm, with a sufficient level of confidence, whether first-type device IDs and second-type device IDs included in the preliminary groups identify the same device.

Device identification for multiple device IDs

Device identification for multiple device IDS

Methods, apparatuses and systems directed to processing client requests in distributed systems. Particular implementations of the invention are directed to allowing application servers to return partially processed results after having consumed a time slice allocation based on performance estimates, network performance metrics, and/or system performance metrics.

Delivering partially processed results based on system metrics in network content delivery systems

The invention is a method, system and computer program for automatically discovering concepts from a corpus of documents and automatically generating a labeled concept hierarchy. The method involves extraction of signatures from the corpus of documents. The similarity between signatures is computed using a statistical measure. The frequency distribution of signatures is refined to alleviate any inaccuracy in the similarity measure. The signatures are also disambiguated to address the polysemy problem. The similarity measure is recomputed based on the refined frequency distribution and disambiguated signatures. The recomputed similarity measure reflects actual similarity between signatures. The recomputed similarity measure is then used for clustering related signatures. The signatures are clustered to generate concepts and concepts are arranged in a concept hierarchy. The concept hierarchy automatically generates query for a particular concept and retrieves relevant documents associated with the concept.

System and method for automatically discovering a hierarchy of concepts from a corpus of documents

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Sunnyvale, CA, United States of America

Jinhui Liu