Locally computable spam detection features and robust pagerank

Data processing: artificial intelligence – Miscellaneous

Reexamination Certificate

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

C706S014000, C706S015000, C706S018000, C706S020000, C706S045000, C706S047000, C706S052000

Reexamination Certificate

active

08010482

ABSTRACT:
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.

REFERENCES:
patent: 6285999 (2001-09-01), Page
patent: 7231395 (2007-06-01), Fain et al.
patent: 2005/0015626 (2005-01-01), Chasin
patent: 2005/0289148 (2005-12-01), Dorner et al.
patent: 2006/0004748 (2006-01-01), Ramarathnam et al.
patent: 2006/0095416 (2006-05-01), Barkhin et al.
patent: 2006/0122957 (2006-06-01), Chen
patent: 2006/0184500 (2006-08-01), Najork et al.
patent: 2007/0067282 (2007-03-01), Prakash et al.
patent: 2007/0233777 (2007-10-01), Bates et al.
patent: 2008/0082481 (2008-04-01), Joshi et al.
patent: 2008/0147669 (2008-06-01), Liu et al.
patent: 2009/0276389 (2009-11-01), Constantine et al.
Zhou et al, “Transductive Link Spam Detection”, AIRWeb '07, 2007, 8 pages.
Zhou et a., “Spectral Clustering and Transductive Learning with Multiple Views”, Preceedings of the International Conference on Machine Learning, 2007, 8 pages.
Svore et al. “Improving Web Spam Classification Using Rank-Time Features”, AIRWeb '07, 2007, 8 pages.
Berkhin, “A Survey on PageRank Computing”, Internet Mathematics, 2005, pp. 73-120.
Andras A. Benczur, et al. SpamRank—Fully Automatic Link Spam Detection Work in progress http://www.searchlores.org/library/benczur.pdf. Last accessed Nov. 14, 2007, 14 pages.
Ricardo Baeza-Yates, et al. Generalizing PageRank: Damping Functions for Link Based Ranking Algorithms. SIGIR'06, Aug. 6-10, 2006, Seattle, Washington, USA. ACM 1595933697/06/0008 http://www.dcc.uchile.cl/˜ccastill/papers/baeza06—general—pagerank—damping—functions—link—ranking.pdf. Last accessed Nov. 14, 2007, 8 pages.
Zoltan Gyongyi, et al. Web Spam Taxonomy http://airweb.cse.lehigh.edu/2005/gyongyi.pdf. Last accessed Nov. 14, 2007, 9 pages.
Carlos Castillo, et al. Know your Neighbors: Web Spam Detection using the Web Topology, Draft version, updated: Nov. 23, 2006. http://www.dcc.uchile.cl/˜ccastill/papers/cdgms—2006—know—your—neighbors.pdf. Last accessed Nov. 14, 2007, 10 pages.
Becchetti, et al., “Link-Based Characterization and Detection of Web Spam”, In Second International Workshop on Adversarial Information Retrieval on the Web, 2006, pp. 1-8.
Castillo, et al., “Know Your Neighbors: Web Spam Detection Using the Web Topology”, In Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Association for Computing Machinery, 2007, pp. 423-430.
Zhou, et al., “Transductive Link Spam Detection”, In Proceedings of the 3rd International Workshop on Adversarial Information Retrieval on the Web, Association for Computing Machinery, 2007 pp. 21-28.
PCT Search Report for PCT Application No. PCT/US2009/034963, mailed Aug. 26, 2009 (10 pages).

LandOfFree

Say what you really think

Search LandOfFree.com for the USA inventors and patents. Rate them and share your experience with other people.

Rating

Locally computable spam detection features and robust pagerank does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Locally computable spam detection features and robust pagerank, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Locally computable spam detection features and robust pagerank will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFUS-PAI-O-2705616

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.