Importance

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Abstract

Electronic content is filtered to identify spam using image and linguistic processing. A plurality of information type gatherers assimilate and output different message attributes relating to message content associated with an information type. A categorizer may have a plurality of decision makers for providing as output a message class for classifying the message data. A history processor records the message attributes and the class decision as part of the prior history information and/or modifies the prior history information to reflect changes to fixed data and/or probability data. A categorizer coalescer assesses the message class output by the set of decision makers together with optional user input for producing a class decision identifying whether the message data is spam.

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First Claim