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Multi-Document Text Summarization using Fuzzy Logic and Association Rule Mining | ||
| Al-Rafidain University College For Sciences | ||
| Article 1, Volume 0, Issue 41, 2017, Pages 241-258 | ||
| Author | ||
| Suhad Malallah | ||
| Abstract | ||
| Information is very necessary. The huge quantity of information on the Internet makes text summarization research increase rapidly. Text summarization is the process of choosing significant sentences from one or multi-document without losing the main ideas of the original text. In this paper a new multi-document English text summarization was proposed, which is based on linguistic and statistical features of the sentences. The extracted features fed to the fuzzy logic system, then the Apriori algorithm used for association rule extraction. The proposed model is performed using dataset supplied by the Text Analysis Conference (TAC-2011) for English documents. The results were measured by using Recall-Oriented Understudy for Gisting Evaluation(ROUGE). The obtained results support the effectiveness of the proposed model. | ||
| Keywords | ||
| Fuzzy Logic; Support; Frequent Itemset; Apriori; confidence | ||
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