Source: http://www.google.com/patents/US8224905?dq=georgia+pacific+dispenser&ei=3350T6jaCc-q0AHQucGAAw
Timestamp: 2014-11-28 10:17:18
Document Index: 197016411

Matched Legal Cases: ['Application No. 2513967', 'application No. 200510107384', 'application No. 04011978', 'Application No. 206121', 'Application No. 2003', 'application No. 10', 'application No. 04714607', 'Application No. 2003115902']

Patent US8224905 - Spam filtration utilizing sender activity data - Google PatentsSearch Images Maps Play YouTube News Gmail Drive More »Sign inAdvanced Patent SearchPatentsSpam is identified by computing sender reputation derived from historical activity data across counts for various categories. A spam filter or machine learning system can be trained utilizing pre-categorized data in conjunction with activity data associated with a sender aggregated across at least one...http://www.google.com/patents/US8224905?utm_source=gb-gplus-sharePatent US8224905 - Spam filtration utilizing sender activity dataAdvanced Patent SearchPublication numberUS8224905 B2Publication typeGrantApplication numberUS 11/567,632Publication dateJul 17, 2012Filing dateDec 6, 2006Priority dateDec 6, 2006Also published asUS20080140781Publication number11567632, 567632, US 8224905 B2, US 8224905B2, US-B2-8224905, US8224905 B2, US8224905B2InventorsAlexei V. Bocharov, Joshua T. GoodmanOriginal AssigneeMicrosoft CorporationExport CitationBiBTeX, EndNote, RefManPatent Citations (118), Non-Patent Citations (97), Referenced by (6), Classifications (6), Legal Events (1) External Links: USPTO, USPTO Assignment, EspacenetSpam filtration utilizing sender activity dataUS 8224905 B2Abstract Spam is identified by computing sender reputation derived from historical activity data across counts for various categories. A spam filter or machine learning system can be trained utilizing pre-categorized data in conjunction with activity data associated with a sender aggregated across at least one time period. This sender activity filter can be employed alone or in combination with other filters to facilitate classification of messages as spam or non-spam.
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