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MEMORY ORGANIZATION AS THE MISSING LINK BETWEEN CASE‐BASED REASONING AND INFORMATION RETRIEVAL IN BIOMEDICINE
Author(s) -
Bichindaritz Isabelle
Publication year - 2006
Publication title -
computational intelligence
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.353
H-Index - 52
eISSN - 1467-8640
pISSN - 0824-7935
DOI - 10.1111/j.1467-8640.2006.00280.x
Subject(s) - computer science , information retrieval , ranking (information retrieval) , rank (graph theory) , inverted index , data mining , search engine indexing , artificial intelligence , mathematics , combinatorics
Mémoire proposes a general framework for reasoning from cases in biology and medicine. Part of this project is to propose a memory organization capable of handling large cases and case bases as occur in biomedical domains. This article presents the essential principles for an efficient memory organization based on pertinent work in information retrieval (IR). IR systems have been able to scale up to terabytes of data taking advantage of large databases research to build Internet search engines. They search for pertinent documents to answer a query using term‐based ranking and/or global ranking schemes. Similarly, case‐based reasoning (CBR) systems search for pertinent cases using a scoring function for ranking the cases. Mémoire proposes a memory organization based on inverted indexes which may be powered by databases to search and rank efficiently through large case bases. It can be seen as a first step toward large‐scale CBR systems, and in addition provides a framework for tight cooperation between CBR and IR.