{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,6,1]],"date-time":"2022-06-01T22:12:00Z","timestamp":1654121520921},"reference-count":28,"publisher":"IGI Global","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014,1,1]]},"abstract":"<p>Search for documents is a common and pertinent task lots of organizations face every day as well as common Internet users in their daily searches. One specific document search is scientific paper search in reference manager systems such as Mendeley or IEEExplore. Considering the difficult task finding documents can sometimes represent, semantic search is currently being applied to improve this type of search. As the act of deciding if a document is a good result for a given search expression is vague, fuzziness becomes an important aspect when defining search algorithms. In this paper, the author present a fuzzy algorithm for improving documental searches optimized for specific scenarios where we want to find a document but don\u00b4t remember the exact words used, if plural or singular words were used or if a synonym was used. The author also present the application of this algorithm to a real scenario comparing to Mendeley and IEEExplore results.<\/p>","DOI":"10.4018\/ijwp.2014010104","type":"journal-article","created":{"date-parts":[[2014,7,23]],"date-time":"2014-07-23T12:40:54Z","timestamp":1406119254000},"page":"50-63","source":"Crossref","is-referenced-by-count":0,"title":["A Fuzzy Algorithm for Optimizing Semantic Documental Searches"],"prefix":"10.4018","volume":"6","author":[{"given":"Sara","family":"Paiva","sequence":"first","affiliation":[{"name":"Polytechnic Institute of Viana do Castelo, Viana do Castelo, Portugal"}]}],"member":"2432","reference":[{"key":"ijwp.2014010104-0","doi-asserted-by":"publisher","DOI":"10.1016\/0742-051X(90)90005-P"},{"key":"ijwp.2014010104-1","unstructured":"Anyanwu, K., & Seth, A. (2003). The \u03c1-Operator: Enabling querying for semantic associations on the semantic web. 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