A graph model with integrated pattern and query-based technique for extracting answer to questions in community question answering system

This paper presents an extension of the community question-answering (CQA) system we developed previously. graph-based method that builds ranked answers for related questions using nKullback–Leibler (KL) divergence. The process extracting to in this work involves; question core, building query, query-based answer extraction (QBAE), pattern-based (PBAE), and combined extraction. source data were existing from ResearchGate, a socio-academic networking website provides researchers platform collaborate, ask questions, offer questions. performance 2786 shows when 80% patterns keywords considered, QBAE PBAE extracted 2765 2766 correct answers, respectively, while + 2782 answers. Also, 90% utilized, 2784 whereas Our was able identify 229 without Finally, evaluation our model reveals high-performance accuracy precision.