This work develops an efficient and effect similarity measure for text mining, based on Boolean logic algebra basics, to effectively reach the desired accuracy at the fastest run time. Using TF/IDF for feature selection, the K nearest neighbor (KNN) classifier and K-means clustering algorithm, a comprehensive empirical evaluation is presented for the proposed measure against seven of the most-frequently used measures on two of the most-popular datasets, namely, Reuters-21 and Web-KB.

Abdalla HI, Amer AA. 2021. Boolean logic algebra driven similarity measure for text based applications. PeerJ Computer Science 7:e641 https://doi.org/10.7717/peerj-cs.641