Concept Based Adaptive IR Model Using FCA-BAM Combination for Concept Representation and Encoding

Authors:
R. K. Rajapakse;M. Denham
Affiliations:
-;-
Venue:
Proceedings of the 24th BCS-IRSG European Colloquium on IR Research: Advances in Information Retrieval
Year:
2002

Citing 13
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Abstract

The model described here is based on the theory of Formal Concept Analysis (FCA). Each document is represented in a Concept Lattice: a structured organisation of concepts according to a subsumption relation and is encoded in a Bidirectional Associative Memory (BAM): a two-layer heterogeneous neural network architecture. The document retrieval process is viewed as a continuous conversation between queries and documents, during which documents are allowed to learn a consistent set of significant concepts to help its retrieval. A reinforcement learning strategy based on relevance feedback information makes the similarity of relevant documents stronger and nonrelevant documents weaker for each query.