Yahoo! Inc.

Iac Search and Media, Inc.

Alexandrin Popescul

Byron Edward Dom

Clifford A Brunk

Alan Levin

Kaushal Kurapati

Kostas Tsioutsiouliklis

Apostolos Gerasoulis

Tomasz Imielinski

Eren Manavoglu

Tong Zhang

Cliff Brunk

Nadav A Zimak

Techniques are provided for generating quality measures for items, including web pages, based on a 'random searcher' behavior model. The random searcher behavior model takes into account 'implicit' links between items, instead of or in addition to the explicit links. After identifying the implicit links between items, the implicit links may be used as the basis for generating quality measures for the items to which the implicit links point. A variety of types of implicit links are described. To facilitate the generation of quality measures for items based on implicit links, a graph of the implicit links may be constructed in a manner similar to a webgraph.

Determining quality measures for web objects based on searcher behavior

A system is described for targeting data to a site referenced on a page based on a condition. The system may include a processor, a memory, and an interface. The memory may be operatively connected to the processor and the interface and may store a data, a site, a condition, and a page containing content. The interface may be operatively connected to the memory and the processor and may communicate the page to a user. The processor may identify the data, site, condition, and page containing content. The processor may add the data to the page if the content of the page satisfies the condition.

System for targeting data to sites referenced on a page

A system and method are disclosed for identifying a keyword that is a novel concept or anomaly based on prior search results for the keyword. Advertisements may be sold for the keyword, or the keyword may be purchased or recommended for purchase based on anticipation of increased future searches on the keyword.

Keyword bidding strategy for novel concepts

An improved system and method is provided for determining web page quality using collective inference based on local and global web page information. A classification engine may be provided for classifying a web page using local features of a seed set of web pages and global web graph information about the seed set of web pages. A dual algorithm based on graph regularization formulated as a well-formed optimization solution may be used in an embodiment for applying collective inference for binary classification of the web page using the local web page information and global web graph information of a web page, the local web page information and global web graph information of an authoritative set of web pages, and the local web page information and global web graph information of a non-authoritative set of web pages.

System and method for determining web page quality using collective inference based on local and global information

Methods and systems for generating query and result-based relevance indexes are provided. For one embodiment, a plurality of queries is received from a plurality of users. Each query of the plurality of queries is measured based on one or more metrics. The measured data of each query is stored. The queries are associated into topical query categories. A performance of a first query category is calculated based on at least one metric of the one or more metrics. A metric data request for a select category is received from a client. Lastly, the stored measured data of the selected category is transmitted to the client in response to the metric data request.

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Mountain View, CA, United States of America

Alexandrin Popescul