Metric graph structure for information retrieval. [Considers semantic distance between documents to enhance retrieval relevancy]

Technical Report · Tue Feb 01 04:00:00 EST 1977

DOI:https://doi.org/10.2172/7119927· OSTI ID:7119927

Melendez, K J

Document retrieval systems accept a user request for information and respond with a list of documents which contain information relevant to the request. When the documents (or abstracts of the documents) are stored in a computer memory, a function can be defined which estimates the semantic distance between documents. If this function together with the set of documents forms a metric space, a graph, which I call a progressive graph, can be constructed to aid the search for the documents with relevant information. Progressive graphs are studied and the search algorithms which use this graph structure are presented. The search algorithms always perform correctly on any progressive graph, but the presence of the progressive property in a graph is not sufficient to insure that the algorithms will work efficiently. The characteristics of a progressive graph which will optimize the search algorithms are discussed, and algorithms to build and optimize progressive graphs are given. The results of a small problem show that the search process using the graph created by these algorithms can be very efficient. Finally, the distance function property which determines when a graph is a progressive graph is isolated and studied. 10 figures, 4 tables

• Research Organization: Los Alamos Scientific Lab., NM (USA)
• DOE Contract Number: W-7405-ENG-36
• OSTI ID: 7119927
• Report Number(s): LA-6341-T
• Country of Publication: United States
• Language: English

Related Subjects

99 GENERAL AND MISCELLANEOUS
990300* -- Information Handling
ALGORITHMS
CORRELATIONS
INFORMATION RETRIEVAL
MATHEMATICAL LOGIC
OPTIMIZATION