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The Web has made possible many advanced textmining applications, such as news summarization, essay grading, question answering, and semantic search. For many of such applications, statistical text-mining techniques are ineffective since they do not utilize the morphological structure of the text. Thus, many approaches use NLP-based techniques, that parse the text and use patterns to mine and analyze the parse trees which are often unnecessarily complex. Therefore, we propose a weighted-graphdoi:10.1109/icsc.2014.31 dblp:conf/semco/MousaviKIZ14 fatcat:5omm44j6gzg7jbtssxhmeyp4mm