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DESCRIPTION OF THE PROPOSED ALGORITHM
EXPERIMENTAL RESULTS AND EVALUATION
acceptable term pair ADI collection algorithm 2.1 base set BCV's BCV(i class matches classification matrix classified DQ pairs clustering the document computed relevant computing the ACSR COS(D,Q cosine correlations cosine function cost current classification defined irrelevant document and query document collection documents relevant DQ pairs type evaluation set exhaustive search Flowchart hash table incorrectly classified DQ incorrectly classified pairs increasing the matching index terms Initial classification produced inverted file iteration matching function value number of classes number of DQ number of incorrectly number of term pair is computed pairs type RN performing operations positively related term processed DQ pairs produced by clustering pseudoclassification algorithm pseudoclassification process pseudoclassification program query 22 query Q R-P Graph Recall Precision Precision relationships between terms relevance judgments relevance matrix relevant documents retrieval system satisfy assessment semantic relationship set of queries SMART system t_th entry Table term class vectors term-term matrix terms contained vector of terms