Method and apparatus for predicting document access in a collection of linked documents featuring link proprabilities and spreading activation

A method for modeling document access in a collection of linked documents based on prior usage information of said collection, said method comprising the steps of:

• a) generating an initial activation matrix, said initial activation matrix indicating a set of focus documents in said collection of linked documents;
• b) generating a transition matrix using said prior usage information, said transition matrix indicating user traversal information between documents in said collection of link ed documents;
• c) generating a link probability vector from said prior usage information, said link probability vector indicating probabilities that a user will link to another document in said document collection;
• d) performing a spreading activation operation using said initial activation matrix, transition matrix and link probability vector to obtain a spreading activation result;
• and
• e) extracting document access information from said spreading activation result.

A system for predicting document access within a collection of linked documents comprising:

• means for gathering usage data for said collection of linked documents;
• means for generating initial activation information, said initial activation information indicating a set of focus documents in said collection of linked documents;
• means for generating page to page transition information from said usage data, said page to page transition information indicating a strength of association between documents in said collection of linked documents;
• means for generating link probability information from said usage data, said link probability information indicating a distribution of the number of documents a user will access in said collection of linked documents;
• spreading activation means for performing a spreading activation operation based on said initial activation information, page to page transition information and said probability information based on a network representation of said collection of linked documents;
• and
• information extraction means for extracting said document access information resulting from said spreading activation step when a stable pattern of activation across all nodes of said network representation of said collection of linked documents is reached.