Microsoft Technology Licensing, LLC

John E Hopcroft

Christian Herwarth Borgs

Jennifer Tour Chayes

Krishna Chaitanya Gade

Seyed Vahab Mirrokni

Amit Prakash

Reid Andersen

Tao Tao

Shang-Hua Teng

Kamal Jain

Vahab Mirrokni

A SPAM detection system is provided. The system includes a graph clustering component to analyze web data. A link analysis component can be associated with the graph clustering component to facilitate SPAM detection in accordance with the web data.

Spam score propagation for web spam detection

The claimed subject matter relates to an architecture that can identify, store, and/or output local contributions to a rank of a vertex in a directed graph. The architecture can receive a directed graph and a parameter, and examine a local subset of vertices (e.g., local to a given vertex) in order to determine a local supporting set. The local supporting set can include a local set of vertices that each contributes a minimum fraction of the parameter to a rank of the vertex. The local supporting set can be the basis for an estimate of the supporting set and/or rank of the vertex for the entire graph and can be employed as a means for detecting link or web spam as well as other influence-based social network applications.

Local computation of rank contributions

The claimed subject matter provides a system and/or a method that facilitates reducing spam in search results. An interface can obtain web graph information that represents a web of pages. A spam detection component can determines one or more features based at least in part on the web graph information. The one or more features can provide indications that a particular page of the web graph is spam. In addition, a robust rank component is provided that limits amount of contribution a single page can provide to the target page.

Locally computable spam detection features and robust pagerank

Neighborhood clustering for web spam detection

Growing community of inventors

Ithaca, NY, United States of America

John E Hopcroft