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SESAME: Mining User Digital Footprints for Fine-Grained Preference-Aware Social Media Search

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Published:17 December 2014Publication History
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Abstract

With the recent popularity of social network services, a significant volume of heterogeneous social media data is generated by users, in the form of texts, photos, videos and collections of points of interest, etc. Such social media data provides users with rich resources for exploring content, such as looking for an interesting video or a favorite point of interest. However, the rapid growth of social media causes difficulties for users to efficiently retrieve their desired media items. Fortunately, users' digital footprints on social networks such as comments massively reflect individual's fine-grained preference on media items, that is, preference on different aspects of the media content, which can then be used for personalized social media search. In this article, we propose SESAME, a fine-grained preference-aware social media search framework leveraging user digital footprints on social networks. First, we collect users' direct feedback on media content from their social networks. Second, we extract users' sentiment about the media content and the associated keywords from their comments to characterize their fine-grained preference. Third, we propose a parallel multituple based ranking tensor factorization algorithm to perform the personalized media item ranking by incorporating two unique features, viz., integrating an enhanced bootstrap sampling method by considering user activeness and adopting stochastic gradient descent parallelization techniques. We experimentally evaluate the SESAME framework using two datasets collected from Foursquare and YouTube, respectively. The results show that SESAME can subtly capture user preference on social media items and consistently outperform baseline approaches by achieving better personalized ranking quality.

References

  1. Peter Anick. 2003. Using terminological feedback for web search refinement: A log-based study. In Proceedings of the Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'03). ACM, 88--95. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Stefano Baccianella, Andrea Esuli, and Fabrizio Sebastiani. 2010. SentiWordNet 3.0: An enhanced lexical resource for sentiment analysis and opinion mining. In Proceedings of the Annual Conference on Language Resources and Evaluation (LREC'10). 2200--2204.Google ScholarGoogle Scholar
  3. Léon Bottou. 2010. Large-scale machine learning with stochastic gradient descent. In Proceedings in Computational Statistics. Springer, 177--186.Google ScholarGoogle ScholarCross RefCross Ref
  4. Mohamed Reda Bouadjenek, Hakim Hacid, and Mokrane Bouzeghoub. 2013. Sopra: A new social personalized ranking function for improving web search. In Proceedings of the Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'13). ACM, 861--864. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Yi Cai and Qing Li. 2010. Personalized search by tag-based user profile and resource profile in collaborative tagging systems. In Proceedings of the International Conference on Information and Knowledge Management (CIKM'10). ACM, 969--978. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Paul-Alexandru Chirita, Claudiu S Firan, and Wolfgang Nejdl. 2007. Personalized query expansion for the web. In Proceedings of the Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'07). ACM, 7--14. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Lieven De Lathauwer, Bart De Moor, and Joos Vandewalle. 2000. A multilinear singular value decomposition. SIAM J. Matrix Anal. Appl. 21, 4, 1253--1278. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Li Ding, Tim Finin, Anupam Joshi, Rong Pan, R Scott Cost, Yun Peng, Pavan Reddivari, Vishal Doshi, and Joel Sachs. 2004. Swoogle: A search and metadata engine for the semantic web. In Proceedings of the International Conference on Information and Knowledge Management (CIKM'04). ACM, 652--659. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Magdalini Eirinaki and Michalis Vazirgiannis. 2003. Web mining for web personalization. ACM Trans. Internet Technol. 3, 1, 1--27. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Rainer Gemulla, Erik Nijkamp, Peter J. Haas, and Yannis Sismanis. 2011. Large-scale matrix factorization with distributed stochastic gradient descent. In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'11). ACM, 69--77. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Frank Allan Hansen, Niels Olof Bouvin, Bent G. Christensen, Kaj Grønbæk, Torben Bach Pedersen, and Jevgenij Gagach. 2004. Integrating the web and the world: Contextual trails on the move. In Proceedings of the ACM Hypertext Conference (HT'04). ACM, 98--107. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Jonathan L. Herlocker, Joseph A. Konstan, Loren G. Terveen, and John T. Riedl. 2004. Evaluating collaborative filtering recommender systems. ACM Trans. Inf. Syst. 22, 1, 5--53. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Anh Huy Phan and Andrzej Cichocki. 2011. PARAFAC algorithms for large-scale problems. Neurocomputing 74, 11, 1970--1984. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Mayu Iwata, Takahiro Hara, Kentaro Shimatani, Tomohiro Mashita, Kiyoshi Kiyokawa, Shojiro Nishio, and Haruo Takemura. 2011. A location-based content search system considering situations of mobile users. Procedia Computer Science 5, 426--433.Google ScholarGoogle ScholarCross RefCross Ref
  15. Heung-Nam Kim, Majdi Rawashdeh, Abdullah Alghamdi, and Abdulmotaleb El Saddik. 2012. Folksonomy-based personalized search and ranking in social media services. Inf. Syst. 37, 1, 61--76. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Yehuda Koren. 2010. Collaborative filtering with temporal dynamics. Commun. ACM 53, 4, 89--97. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Dariusz Król, Michal Szymanski, and Bogdan Trawinski. 2006. The recommendation mechanism in an internet information system with time impact coefficient. Int. J. Comp. Sci. Appl. 3, 3, 65--80.Google ScholarGoogle Scholar
  18. Nicholas D. Lane, Dimitrios Lymberopoulos, Feng Zhao, and Andrew T. Campbell. 2010. Hapori: context-based local search for mobile phones using community behavioral modeling and similarity. In Proceedings of the ACM International Conference on Ubiquitous Computing (UbiComp'10). ACM, 109--118. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Fangtao Li, Sinno Jialin Pan, Ou Jin, Qiang Yang, and Xiaoyan Zhu. 2012. Cross-domain co-extraction of sentiment and topic lexicons. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL'12). Association for Computational Linguistics, 410--419. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Edward Loper and Steven Bird. 2002. NLTK: The natural language toolkit. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL'02) Workshop on Effective Tools and Methodologies for Teaching Natural Language Processing And Computational Linguistics. Association for Computational Linguistics, 63--70. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Takuya Maekawa, Yutaka Yanagisawa, Yasushi Sakurai, Yasue Kishino, Koji Kamei, and Takeshi Okadome. 2012. Context-aware web search in ubiquitous sensor environments. ACM Trans. Internet Technol. 11, 3, 12. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Wilfred Ng, Lin Deng, and Dik Lun Lee. 2007. Mining user preference using spy voting for search engine personalization. ACM Trans. Internet Technol. 7, 4, 19. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Anastasios Noulas, Salvatore Scellato, Cecilia Mascolo, and Massimiliano Pontil. 2011. An empirical study of geographic user activity patterns in foursquare. In Proceedings of the International Conference on Weblogs and Social Media (ICWSM'11). 70--573.Google ScholarGoogle Scholar
  24. Derek O'Callaghan, Martin Harrigan, Joe Carthy, and &Pacute;adraig Cunningham. 2012. Network analysis of recurring YouTube spam campaigns. In Proceedings of the International Conference on Weblogs and Social Media (ICWSM'12).Google ScholarGoogle Scholar
  25. Steffen Rendle, Leandro Balby Marinho, Alexandros Nanopoulos, and Lars Schmidt-Thieme. 2009a. Learning optimal ranking with tensor factorization for tag recommendation. In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'09). ACM, 727--736. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, and Lars Schmidt-Thieme. 2009b. BPR: Bayesian personalized ranking from implicit feedback. In Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI'09). AUAI Press, 452--461. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. Steffen Rendle and Lars Schmidt-Thieme. 2010. Pairwise interaction tensor factorization for personalized tag recommendation. In Proceedings of the International Conference on Web Search and Data Mining (WSDM'10). ACM, 81--90. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. Jitao Sang, Changsheng Xu, and Dongyuan Lu. 2012. Learn to personalized image search from the photo sharing websites. IEEE Trans. Multimedia 14, 4, 963--974. Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. Pravin Shankar, Yun-Wu Huang, Paul Castro, Badri Nath, and Liviu Iftode. 2012. Crowds replace experts: Building better location-based services using mobile social network interactions. In Proceedings of the IEEE International Conference on Pervasive Computing and Communication (PerCom'12). IEEE, 20--29.Google ScholarGoogle ScholarCross RefCross Ref
  30. Shabnam Shariaty and Samaneh Moghaddam. 2011. Fine-grained opinion mining using conditional random fields. In Proceedings of the International Conference on Data Mining Workshops (ICDMW'11). IEEE, 109--114. Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. Yue Shi, Alexandros Karatzoglou, Linas Baltrunas, Martha Larson, Alan Hanjalic, and Nuria Oliver. 2012. TFMAP: Optimizing MAP for top-n context-aware recommendation. In Proceedings of the Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'12). ACM, 155--164. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. Nakatani Shuyo. 2010. Language Detection Library for Java. (2010). http://code.google.com/p/language-detection/.Google ScholarGoogle Scholar
  33. Lucia Specia and Enrico Motta. 2007. Integrating folksonomies with the semantic web. In Proceedings of the European Semantic Web Conference (ESWC'07). Springer, 624--639. Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. Kazunari Sugiyama, Kenji Hatano, and Masatoshi Yoshikawa. 2004. Adaptive web search based on user profile constructed without any effort from users. In Proceedings of the International World Wide Web Conference (WWW'04). ACM, 675--684. Google ScholarGoogle ScholarDigital LibraryDigital Library
  35. Jian-Tao Sun, Hua-Jun Zeng, Huan Liu, Yuchang Lu, and Zheng Chen. 2005. CubeSVD: A novel approach to personalized Web search. In Proceedings of the International World Wide Web Conference (WWW'05). ACM, 382--390. Google ScholarGoogle ScholarDigital LibraryDigital Library
  36. Ledyard R. Tucker. 1966. Some mathematical notes on three-mode factor analysis. Psychometrika 31, 3, 279--311.Google ScholarGoogle ScholarCross RefCross Ref
  37. Shengliang Xu, Shenghua Bao, Ben Fei, Zhong Su, and Yong Yu. 2008. Exploring folksonomy for personalized search. In Proceedings of the Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'08). ACM, 155--162. Google ScholarGoogle ScholarDigital LibraryDigital Library
  38. Dingqi Yang, Daqing Zhang, Zhiyong Yu, and Zhu Wang. 2013a. A sentiment-enhanced personalized location recommendation system. In Proceedings of the ACM Hypertext Conference (HT'13). 119--128. Google ScholarGoogle ScholarDigital LibraryDigital Library
  39. Dingqi Yang, Daqing Zhang, Zhiyong Yu, and Zhiwen Yu. 2013b. Fine-grained preference-aware location search leveraging crowdsourced digital footprints from LBSNs. In Proceedings of the ACM International Conference on Ubiquitous Computing (UbiComp'13). ACM, 479--488. Google ScholarGoogle ScholarDigital LibraryDigital Library
  40. D. Yang, D. Zhang, V. W. Zheng, and Z. Yu. 2014. Modeling user activity preference by leveraging user spatial temporal characteristics in LBSNs. IEEE Trans. Syst. Man Cybern: Syst. DOI:http://dx.doi. org/10.1109/TSMC.2014.2327053Google ScholarGoogle Scholar
  41. Shuang-Hong Yang, Bo Long, Alex Smola, Narayanan Sadagopan, Zhaohui Zheng, and Hongyuan Zha. 2011. Like like alike: joint friendship and interest propagation in social networks. In Proceedings of the International World Wide Web Conference (WWW'11). ACM, 537--546. Google ScholarGoogle ScholarDigital LibraryDigital Library
  42. Daqing Zhang, Bin Guo, and Zhiwen Yu. 2011. The emergence of social and community intelligence. Computer 44, 7, 21--28. Google ScholarGoogle ScholarDigital LibraryDigital Library
  43. Qiang Zhang, Michael W. Berry, Brian T. Lamb, and Tabitha Samuel. 2009. A parallel nonnegative tensor factorization algorithm for mining global climate data. In Proceedings of the International Conference on Computational Science (ICCS'09). Springer, 405--415. Google ScholarGoogle ScholarDigital LibraryDigital Library
  44. Dong Zhou, Séamus Lawless, and Vincent Wade. 2012. Web search personalization using social data. In Theory and Practice of Digital Libraries, Springer, 298--310. Google ScholarGoogle ScholarDigital LibraryDigital Library
  45. Yong Zhuang, Wei-Sheng Chin, Yu-Chin Juan, and Chih-Jen Lin. 2013. A fast parallel SGD for matrix factorization in shared memory systems. In Proceedings of the ACM Conference on Recommender Systems (RecSys'13). ACM, 249--256. Google ScholarGoogle ScholarDigital LibraryDigital Library
  46. Martin Zinkevich, Markus Weimer, Lihong Li, and Alex J Smola. 2010. Parallelized stochastic gradient descent. In Proceedings of the Conference on Advances in Neural Information Processing Systems (NIPS'10). 2595--2603.Google ScholarGoogle Scholar

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