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 and apparatus for an active low power mode of a portable computing device
Image forming apparatus
Visually tracking an object in real world using 2D appearance and multicue depth estimations
Use of LPA for encouraging pregnancy, and fertility agent
Interface circuit
Nanoparticle entrapment of materials
Communication apparatus and communication system
  Randomly Featured Patents
Linear feedback shift register, multiple input signature register, and built-in self test circuit using such registers
Thrust bearing for a shaft of an open-end spinning rotor
Charged particle beam lithography system
Lighting equipment built-in on-line uninterruptible power system capable of outputting AC sinusoidal power from a single DC source
Sound-image position control apparatus
Modular plug connector
Thiazolyl urea compounds and methods of uses
Vehicle mounted carrier assembly
Organizer for golf equipment
Radioactive source wire, apparatus and treatment methods