Feedback loop for spam prevention
First Claim
1. A system that facilitates classifying items in connection with spam prevention, comprising:
- a component that receives a set of the items;
a component that identifies intended recipients of the items, and tags a subset of the items to be polled, the subset of items corresponding to a subset of recipients that are known spam fighting users; and
a feedback component that receives information relating to the spam fighter'"'"'s classification of the polled items, and employs the information in connection with training a spam filter and populating a spam list.
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Accused Products
Abstract
The subject invention provides for a feedback loop system and method that facilitate classifying items in connection with spam prevention in server and/or client-based architectures. The invention makes uses of a machine-learning approach as applied to spam filters, and in particular, randomly samples incoming email messages so that examples of both legitimate and junk/spam mail are obtained to generate sets of training data. Users which are identified as spam-fighters are asked to vote on whether a selection of their incoming email messages is individually either legitimate mail or junk mail. A database stores the properties for each mail and voting transaction such as user information, message properties and content summary, and polling results for each message to generate training data for machine learning systems. The machine learning systems facilitate creating improved spam filter(s) that are trained to recognize both legitimate mail and spam mail and to distinguish between them.
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Citations
95 Claims
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1. A system that facilitates classifying items in connection with spam prevention, comprising:
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a component that receives a set of the items;
a component that identifies intended recipients of the items, and tags a subset of the items to be polled, the subset of items corresponding to a subset of recipients that are known spam fighting users; and
a feedback component that receives information relating to the spam fighter'"'"'s classification of the polled items, and employs the information in connection with training a spam filter and populating a spam list. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31)
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32. A method that facilitates classifying messages in connection with spam prevention comprising:
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receiving a set of the messages;
identifying intended recipients of the messages;
tagging a subset of the messages to be polled, the subset of messages corresponding to a subset of the recipients that are known spam fighting users;
receiving information relating to the user'"'"'s classification of polling messages; and
employing the information in connection with training a spam filter and populating a spam list. - View Dependent Claims (33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86)
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87. A cross-validation method that facilitates verifying reliability and trustworthiness of user classifications comprising:
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excluding one or more suspected user'"'"'s classifications from data employed to train the spam filter;
training the spam filter using all other available user classifications; and
running the suspected user'"'"'s polling messages through the trained spam filter to determine how it would have classified the messages compared to the suspected user'"'"'s classifications. - View Dependent Claims (88)
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89. A method that facilitates verifying reliability and trustworthiness in user classifications for training a spam filter via a feedback loop system comprising:
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identifying a subset of spam-fighting users as suspect users;
providing one or more messages having a known result to the suspect users for polling; and
determining whether the suspected users'"'"' classification of the one or more test messages matches the known classification to ascertain the reliability of the users'"'"' classifications. - View Dependent Claims (90, 91, 92, 93)
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94. A computer-readable medium having stored thereon the following computer executable components:
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a component that receives a set of messages;
a component that identifies intended recipients of the messages, and tags a subset of the messages to be polled, the subset of messages corresponding to a subset of recipients that are known spam fighting users;
a message modification component that modifies the tagged messages to identify them as polling messages to users; and
a feedback component that receives information relating to the user'"'"'s classification of the polled messages, and employs the information in connection with training a spam filter and populating a spam list.
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95. A system that facilitates classifying messages in connection with spam prevention comprising:
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means for receiving a set of the messages;
means for identifying intended recipients of the messages;
means for tagging a subset of the messages to be polled, the subset of messages corresponding to a subset of the recipients that are known spam fighting users;
means for receiving information relating to the user'"'"'s classification of the polling messages; and
means for employing the information in connection with training a spam filter and populating a spam list.
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Specification