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Background/Objectives: In this study, a term weighting scheme derived from probabilistic multiple correlation is defined for measuring similarity between unstructured text records.Methods:While the intra-correlation is the correlation of terms in the same record, inter-correlation is the correlation of terms that exist in different records. Probabilistic multiple correlation based term weighting calculates the weight or relevance of a term by considering its intracorrelation with one or more terms simultaneously. Subsequently, the term weights are used in measuring the inter-correlation of terms and then the similarity between two text records. Findings: The experiments are run onunstructured text records that are incomplete and employ abbreviations. There is significant improvement in precision, recall and f-score using probabilistic multiple correlation based term weighting scheme when compared with probabilistic simple correlation weighting scheme. Applications: Using probabilistic multiple correlation based term weighting scheme can improve the overall accuracy in matching unstructured text records that contain abbreviations and incomplete data.

Probabilistic multiple correlation based term weighting scheme for measuring similarity of unstructured text records