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The overall scheme is based on Mamdani Inferencing scheme which helps in designing Fuzzy Rule base for inferencing about the decision variable from a set of antecedent variables. The antecedent variables chosen for the task are from linguistic and positional heuristics, and similarity of the documents with the user-defined query. The decision variable is the rank of the sentences as decided by the rules. The final summary is generated by solving an Integer Linear Programming problem. For abstraction coreference resolution is applied on the input sentences in the pre-processing step. Although designed on the basis of a small set of antecedent variables the results are very promising.<\/jats:p>","DOI":"10.3233\/jifs-219252","type":"journal-article","created":{"date-parts":[[2022,1,4]],"date-time":"2022-01-04T11:31:15Z","timestamp":1641295875000},"page":"4641-4652","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":2,"title":["Query-focused multi-document text summarization using fuzzy inference"],"prefix":"10.1177","volume":"42","author":[{"given":"Raksha","family":"Agarwal","sequence":"first","affiliation":[{"name":"Department of Mathematics, Indian Institute of Technology Delhi, Hauz Khas, Delhi, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Niladri","family":"Chatterjee","sequence":"additional","affiliation":[{"name":"Department of Mathematics, Indian Institute of Technology Delhi, Hauz Khas, Delhi, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2021,12,24]]},"reference":[{"key":"e_1_3_2_2_2","unstructured":"ManiI. and MayburyM.T. 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