Resources Contact Us Home
Spam filtering using feature relevance assignment in neural networks

Image Number 11 for United States Patent #8131655.

In some embodiments, a spam filtering method includes computing a pattern relevance for each of a set of message feature patterns, and using a neural network filter to classify incoming messages as spam or ham according to the pattern relevancies. Each message feature pattern is characterized by the simultaneous presence within a message of a specific set of message features (e.g., the presence of certain keywords within the message body, various message header heuristics, various message layout features, etc.). Each message feature may be spam- or ham-identifying, and may receive a tunable feature relevance weight from an external source (e.g. data file and/or human operator). The external feature relevance weights modulate the set of neuronal weights calculated through a training process of the neural network.

  Recently Added Patents
Method for spacing electrical conductors and related devices
Sprocket support structure
Flange for xerographic photoreceptor
Sink accessory
Portable auxiliary power-source device for a vehicle
Processing unit, speech recognition apparatus, speech recognition system, speech recognition method, storage medium storing speech recognition program
Lighting apparatus
  Randomly Featured Patents
Method for polishing a semiconductor substrate
Soybean cultivar CL0911428
Acoustical pad
Fuel injection method and device to increase combustion dynamics and efficiency in combustion equipment operating with fluid hydro carbon fuel
Method and device for determining the remaining serviceable life of a product
Portable camp stove, and fuel container
Installing a solution
Quick-action fastening device for a childs seat in a vehicle
Gaming machine