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In some online social network services, users are allowed to label users with similar interests as \u201ctrust\u201d to get the information they want and use \u201cdistrust\u201d to label users with opposite interests to avoid browsing content they do not want to see. The networks containing such trust relationships and distrust relationships are named signed social networks (SSNs), and some real-world complex systems can be also modeled with signed networks. However, the sparse social relationships seriously hinder the expansion of users\u2019 social circle in social networks. In order to solve this problem, researchers have done a lot of research on link prediction. Although these studies have been proved to be effective in the unsigned social network, the prediction of trust and distrust in SSN has not achieved good results. In addition, the existing link prediction research does not consider the needs of user privacy protection, so most of them do not add privacy protection measures. To solve these problems, we propose a trust-based missing link prediction method (TMLP). First, we use the simhash method to create a hash index for each user. Then, we calculate the Hamming distance between the two users to determine whether they can establish a new social relationship. Finally, we use the fuzzy computing model to determine the type of their new social relationship (e.g., trust or distrust). In the paper, we gradually explain our method through a case study and prove our method\u2019s feasibility.<\/jats:p>","DOI":"10.1155\/2020\/8849536","type":"journal-article","created":{"date-parts":[[2020,11,16]],"date-time":"2020-11-16T19:20:20Z","timestamp":1605554420000},"page":"1-10","source":"Crossref","is-referenced-by-count":6,"title":["Trust-Based Missing Link Prediction in Signed Social Networks with Privacy Preservation"],"prefix":"10.1155","volume":"2020","author":[{"given":"Huaizhen","family":"Kou","sequence":"first","affiliation":[{"name":"School of Computer Science, Qufu Normal University, Rizhao, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fan","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer Science, Qufu Normal University, Rizhao, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chao","family":"Lv","sequence":"additional","affiliation":[{"name":"China Telecom Smart Home Competence Center, E-Surfing Smart Home Technology Co., Ltd, Nanjing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9075-3959","authenticated-orcid":true,"given":"Zhaoan","family":"Dong","sequence":"additional","affiliation":[{"name":"School of Computer Science, Qufu Normal University, Rizhao, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wanli","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Computer Science, Qufu Normal University, Rizhao, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9301-5989","authenticated-orcid":true,"given":"Hao","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Norwegian University of Science and Technology, Trondheim, Norway"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuwen","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Computer Science, Qufu Normal University, Rizhao, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"key":"1","first-page":"11","article-title":"Combining time, keywords and authors information to construct papers correlation graph (s)","volume-title":"The 31st International Conference on Software Engineering and Knowledge Engineering","author":"H. 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