Feedback loop for spam prevention
First Claim
1. A system, that facilitates classifying items in connection with spam prevention, comprising computer-executable components embodied on a computer-readable storage medium, the system 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, wherein the subset of the items to be polled is determined before the items are labeled as spam or not spam, as such all items are considered for polling including those items which are designated as spam by a currently employed spam filter;
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, wherein the feedback component employs machine learning techniques to train the spam filter; and
a component that modifies an item tagged for polling to identify it as a polling item, wherein the modified item comprises voting instructions and any one of at least two voting buttons and links which correspond to at least two respective classes of items facilitate classification of the item by the user, wherein the voting buttons correspond to respective links such that when any one of the voting buttons is selected by the user, information relating to the selected voting button, the respective user, and the item'"'"'s unigue ID assigned thereto is sent to a database for storage.
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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.
272 Citations
81 Claims
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1. A system, that facilitates classifying items in connection with spam prevention, comprising computer-executable components embodied on a computer-readable storage medium, the system 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, wherein the subset of the items to be polled is determined before the items are labeled as spam or not spam, as such all items are considered for polling including those items which are designated as spam by a currently employed spam filter; 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, wherein the feedback component employs machine learning techniques to train the spam filter; and a component that modifies an item tagged for polling to identify it as a polling item, wherein the modified item comprises voting instructions and any one of at least two voting buttons and links which correspond to at least two respective classes of items facilitate classification of the item by the user, wherein the voting buttons correspond to respective links such that when any one of the voting buttons is selected by the user, information relating to the selected voting button, the respective user, and the item'"'"'s unigue ID assigned thereto is sent to a database for storage. - 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)
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26. 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, wherein the subset of messages to be polled is determined before the messages are labeled as spam or not spam, as such all messages are considered for polling including those messages which are designated as spam by a currently employed spam filter; receiving information relating to the user'"'"'s classification of polling messages; employing the information in connection with training a spam filter and populating a spam list, wherein training the spam filter is employed via a machine learning technique; and modifying a message tagged for polling to identify it as a polling message, wherein the modified message comprises voting instructions and any one of at least two voting buttons and links which correspond to at least two respective classes of messages facilitate classification of the message by the user, wherein the voting buttons correspond to respective links such that when any one of the voting buttons is selected by the user, information relating to the selected voting button, the respective user, and the message'"'"'s unique ID assigned thereto is sent to a database for storage. - View Dependent Claims (27, 28, 29, 30, 31, 32, 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)
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80. A computer-readable storage medium having stored thereon computer components, when executed by one or more processor for facilitating classification of messages in connection with spam prevention, the components comprising:
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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, wherein the subset of messages to be polled is determined before the messages are labeled as spam or not spam, as such all messages are considered for polling including those messages which are designated as spam by a currently employed spam filter; a message modification component that modifies the tagged messages to identify them as polling messages to users; 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, wherein the feedback component employs machine learning techniques to train the spam filter; and a component that modifies a message tagged for polling to identify it as a polling message, wherein the modified message comprises voting instructions and any one of at least two voting buttons and links which correspond to at least two respective classes of messages facilitate classification of the message by the user, wherein the voting buttons correspond to respective links such that when any one of the voting buttons is selected by the user, information relating to the selected voting button, the respective user, and the message'"'"'s unigue ID assigned thereto is sent to a database for storage.
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81. A system that facilitates classifying messages in connection with spam preVention comprising a computer-readable storage medium, comprising:
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computer-executable means for receiving a set of the messages; computer-executable means for identifying intended recipients of the messages; computer-executable 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 wherein the subset of messages to be polled is determined before the messages are labeled as spam or not spam, as such all messages are considered for polling including those messages which are designated as spam by a currently employed spam filter; computer-executable means for receiving information relating to the user'"'"'s classification of the polling messages; computer-executable means for employing the information in connection with training a spam filter and populating a spam list, wherein training the spam filter is employed via a machine learning technique; and computer-executable means for modifying a message tagged for polling to identify it as a polling message, wherein the modified message comprises voting instructions and any one of at least two voting buttons and links which correspond to at least two respective classes of messages facilitate classification of the message by the user, wherein the voting buttons correspond to respective links such that when any one of the voting buttons is selected by the user, information relating to the selected voting button, the respective user, and the message'"'"'s unigue ID assigned thereto is sent to a database for storage.
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Specification