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Among the demographical information, the impact of the user gender is less explored when compared with other information like age, profession, region, etc. In this work, a genetic algorithm-influenced gender-based top-n recommender algorithm is proposed to address the new user cold start problem. The algorithm utilises the evolution concepts of the genetic algorithm to render top-n recommendations to a new user. The evaluation of the proposed algorithm using real world datasets proved that the algorithm has a better efficiency than the state of art approaches.<\/jats:p>","DOI":"10.4018\/ijsir.2020040104","type":"journal-article","created":{"date-parts":[[2020,1,10]],"date-time":"2020-01-10T13:12:15Z","timestamp":1578661935000},"page":"62-79","source":"Crossref","is-referenced-by-count":2,"title":["Genetic Algorithm Influenced Top-N Recommender System to Alleviate New User Cold Start Problem"],"prefix":"10.4018","volume":"11","author":[{"family":"Sharon Moses J.","sequence":"first","affiliation":[{"name":"VIT University, Vellore, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"family":"Dhinesh Babu L.D.","sequence":"additional","affiliation":[{"name":"VIT University, Vellore, India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","reference":[{"key":"IJSIR.2020040104-0","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2007.07.024"},{"key":"IJSIR.2020040104-1","doi-asserted-by":"crossref","unstructured":"Alahmadi, D. 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