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Method and system of filtering and recommending documents

Patent ·
OSTI ID:1237854
;
Disclosed is a method and system for discovering documents using a computer and providing a small set of the most relevant documents to the attention of a human observer. Using the method, the computer obtains a seed document from the user and generates a seed document vector using term frequency-inverse corpus frequency weighting. A keyword index for a plurality of source documents can be compared with the weighted terms of the seed document vector. The comparison is then filtered to reduce the number of documents, which define an initial subset of the source documents. Initial subset vectors are generated and compared to the seed document vector to obtain a similarity value for each comparison. Based on the similarity value, the method then recommends one or more of the source documents.
Research Organization:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Organization:
USDOE
DOE Contract Number:
AC05-00OR22725
Assignee:
UT-Battelle LLC (Oak Ridge, TN)
Patent Number(s):
9,256,649
Application Number:
13/920,803
OSTI ID:
1237854
Country of Publication:
United States
Language:
English

References (5)

An implementation of a knowledge recommendation system based on similarity among users' profiles conference January 2002
A statistical interpretation of term specificity and its application in retrieval journal October 2004
TF-ICF: A New Term Weighting Scheme for Clustering Dynamic Data Streams conference December 2006
Engene: A genetic algorithm classifier for content-based recommender systems that does not require continuous user feedback conference September 2010
A vector space model for automatic indexing journal November 1975

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97 MATHEMATICS AND COMPUTING
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