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Second, it has used explicit demographic information to alleviate the cold start issue, and third, it proposes a new strategy for assessing user preferences and also combined the context parameters in the form of a vector model with the Term Frequency Inverse Document Frequency technique to find contexts\u2019 similarity. Furthermore, our framework discovers a list of optimal candidate trips by involving personalized POIs in sequential patterns\u2019 mining (SPM); also, it used an adjusted forgotten function to involve the date context of each trip. Based on two datasets (Flickr and Gowalla), our methodology beats other prior approaches in F-score, RMSE, MAP, and NDCG factors in the experimental evaluation.<\/jats:p>","DOI":"10.1007\/s40747-022-00958-5","type":"journal-article","created":{"date-parts":[[2023,1,17]],"date-time":"2023-01-17T04:39:21Z","timestamp":1673930361000},"page":"4457-4482","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["A hybrid recommender system using topic modeling and prefixspan algorithm in social media"],"prefix":"10.1007","volume":"9","author":[{"given":"Ali Akbar","family":"Noorian Avval","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2382-5120","authenticated-orcid":false,"given":"Ali","family":"Harounabadi","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,1,17]]},"reference":[{"key":"958_CR1","doi-asserted-by":"publisher","DOI":"10.22054\/tms.2020.41870.2137","author":"A Noorian","year":"2020","unstructured":"Noorian A, Ravanmehr R, Harounabadi A, Nouri F (2020) Trust-based tourism recommendation system using context-aware clustering. 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