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
Packet bundling at the PDCP layer
Wideband multi-channel receiver with fixed-frequency notch filter for interference rejection
Die seal ring
Switchable memory diodes based on ferroelectric/conjugated polymer heterostructures and/or their composites
Camera system, video processing apparatus, and camera apparatus
Motor and disk drive apparatus
Organic light-emitting display and method of manufacturing the same
  Randomly Featured Patents
Magnetoresistive semiconductor pressure sensors and fingerprint identification/verification sensors using same
Portable work platform
Apparatus for feeding plate-form parts
Ground fault detection system and method
Rotary regenerative heat exchanger and method of operating same
Application service provider and automated transaction machine system and method
Magnetic field generating assembly
Protocol analyzer and time precise method for capturing multi-directional packet traffic
Sustained release capsule