Mobile Networks and Applications

, Volume 23, Issue 6, pp 1610–1623 | Cite as

CrossRec: Cross-Domain Recommendations Based on Social Big Data and Cognitive Computing

  • Yin Zhang
  • Xiao Ma
  • Shaohua Wan
  • Haider Abbas
  • Mohsen Guizani


With the explosion of social data comes a great challenge called information overloading. To overcome this challenge, recommender systems are expected to support users in quickly accessing the appropriate content. However, cold-start users are a formidable challenge in the design of recommender systems because the conventional recommendation services are based on a single data source, namely, a single field. Considering the advantages of social-based and cross-domain approaches involving further additional data, we propose a cross-domain recommender system, including three approaches, based on multi-source social big data. The proposed approach is expected to effectively alleviate the issues of cold-start users by transferring user preferences from a related auxiliary domain to a target domain. Moreover, the transferred preferences are able to improve the diversity of recommendations. Through adequate evaluations based on an actual dataset in the book and music domains, it is shown that the accuracies of the three proposed approaches are significantly improved compared with the conventional recommender approaches, such as collaborative filtering and matrix factorization. In particular, the proposed approaches are available to provide cold-start users with highly effective recommendations.


Cross-domain recommender Social big data Collaborative filtering Association rule 



This work was supported by the China National Natural Science Foundation under Grant 61702553 and the Project of Humanities and Social Sciences (17YJCZH252) funded by the China Ministry of Education (MOE).


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Information and Safety EngineeringZhongnan University of Economics and LawWuhanChina
  2. 2.National University of Sciences and TechnologyIslamabadPakistan
  3. 3.Florida Institute of TechnologyMelbourneUSA
  4. 4.Electrical and Computer Engineering DepartmentUniversity of IdahoMoscowUSA

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