Yahoo! Inc.

Debora Donato

Francesco Bonchi

Aristides Gionis

Andrei Z Broder

Yoelle Smadja Maarek

Ronny Lempel

Liang-Yu Tom Chi

Edward Bortnikov

Wei-Cheng Lai

Su-Lin Wu

Evgeniy Gabrilovich

Peter Mika

Paolo Ferragina

Christopher C LuVogt

Claudio Corsi

The present invention provides a method and system for providing targeted applications within a search engine results page. The method and system includes receiving a search query from a user and interpreting the search query. The method and system then first maps the interpreted query to one or more action templates, wherein mapping the interpreted query to one or more action templates comprises selecting one or more actions associated with the interpreted query. The method and system then maps the selected one or more actions associated with the interpreted query to a plurality of applications and selecting one or more applications associated with the one or more actions. Finally, the method and system displays the one or more applications within a search results page.

System and method for providing contextual actions on a search results page

Disclosed are methods and apparatus for detecting spam hosts. In one embodiment, one or more graphs are generated using data obtained from a query log, where the one or more graphs include at least one of an anticlick graph or a view graph. Values of one or more syntactic features of the one or more graphs are ascertained. Values of one or more semantic features of the one or more graphs are determined by propagating categories from a web directory among nodes in each of the one or more graphs. Spam hosts are then detected based upon the values of the syntactic features and the semantic features.

Query log mining for detecting spam hosts

A system and method is described herein that automatically determines if a user of a search engine is conducting a research mission and then provides one or more research tools, one or more specialized searches, one or more directed ads, and/or one or more marketplace events responsive to determining that the research mission is being conducted. The automatic provision of various events and/or tools responsive to determination of the research mission can advantageously improve the experience of the user conducting the research mission.

Research mission identification

Methods and apparatus are described for modeling sequences of events with Markov models whose states correspond to nodes in a provided taxonomy. Each state represents the events in the subtree under the corresponding node. By lumping observed events into states that correspond to internal nodes in the taxonomy, more compact models are achieved that are easier to understand and visualize, at the expense of a decrease in the data likelihood. The decision for selecting the best model is taken on the basis of two competing goals: maximizing the data likelihood, while minimizing the model complexity (i.e., the number of states).

Taxonomy-driven lumping for sequence mining

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San Francisco, CA, United States of America

Debora Donato