{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,11]],"date-time":"2026-01-11T04:32:13Z","timestamp":1768105933889,"version":"3.49.0"},"reference-count":29,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2020,2,3]],"date-time":"2020-02-03T00:00:00Z","timestamp":1580688000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["11671001"],"award-info":[{"award-number":["11671001"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>In this paper, we study the feasibility of performing fuzzy information retrieval by word embedding. We propose a fuzzy information retrieval approach to capture the relationships between words and query language, which combines some techniques of deep learning and fuzzy set theory. We try to leverage large scale data and the continuous-bag-of words model to find the relevant feature of words and obtain word embedding. To enhance retrieval effectiveness, we measure the relativity among words by word embedding, with the property of symmetry. Experimental results show that the recall ratio, precision ratio, and harmonic average of two ratios of the proposed method outperforms the ones of the traditional methods.<\/jats:p>","DOI":"10.3390\/sym12020225","type":"journal-article","created":{"date-parts":[[2020,2,7]],"date-time":"2020-02-07T03:13:27Z","timestamp":1581045207000},"page":"225","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Fuzzy Information Retrieval Based on Continuous Bag-of-Words Model"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4088-5371","authenticated-orcid":false,"given":"Dong","family":"Qiu","sequence":"first","affiliation":[{"name":"College of Science, Chongqing University of Post and Telecommunication, Chongqing 400065, China"}]},{"given":"Haihuan","family":"Jiang","sequence":"additional","affiliation":[{"name":"College of Science, Chongqing University of Post and Telecommunication, Chongqing 400065, China"}]},{"given":"Shuqiao","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Science, Chongqing University of Post and Telecommunication, Chongqing 400065, China"}]}],"member":"1968","published-online":{"date-parts":[[2020,2,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"525","DOI":"10.1007\/978-3-642-35644-5_14","article-title":"The Role of Fuzzy Sets in Information Retrieval","volume":"299","author":"Pasi","year":"2013","journal-title":"Stud. 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