Serendipitous Page Recommendation on Web IndeX System with Potential Preferences
Pages 104 - 110
Abstract
Most recommendation systems excessively pursue the recommendation accuracy and give rise to over-specialization. However, the existing recommendation systems research has not studied serendipity much. Hence, the serendipitous item recommendation has received more attention in recent years. The serendipitous recommendation of our research is not included in the area that the user predict easily but recommends the keywords that match the potential preferences. Potential preferences are those that are present in the user profile, which the user may not know. In this research, we recommend keywords that can express serendipity by intersecting the relation between keywords mainly. Furthermore, we propose the related page recommendation method on Web IndeX System for recommending linked pages related to these serendipitous keywords based on the user's potential preferences.
References
[1]
Denis Kotkov, ShuaiqiangWang, and Jari Veijalainen. 2016. A survey of serendipity in recommender systems. Knowledge-Based Systems 111 (2016), 180--192. https://doi.org/10.1016/j.knosys.2016.08.014
[2]
Santosh Kumar, Varsha," Survey on Personalized Web Recommender System", International Journal of Information Engineering and Electronic Business(IJIEEB), Vol.10, No.4, pp. 33--40, 2018.
[3]
Mouzhi Ge, Carla Delgado-Battenfeld, and Dietmar Jannach. 2010. Beyond accuracy: evaluating recommender systems by coverage and serendipity. In Proceedings of the fourth ACM conference on Recommender systems (RecSys '10). Association for Computing Machinery, New York, NY, USA, 257--260.
[4]
Qingyun Wu, Huazheng Wang, Yanen Li, and Hongning Wang. 2019. Dynamic Ensemble of Contextual Bandits to Satisfy Users' Changing Interests. In The World Wide Web Conference (WWW '19). Association for Computing Machinery, New York, NY, USA, 2080--2090.
[5]
Hiroki Satou, Motomichi Toyama. "Trial manufacture of a browser which has a function of attachment A-doc file." Data engineering workshop, DEWS2007, 2007
[6]
Bharti, Pooja M. and Tushar J. Raval. "Improving Web Page Access Prediction using Web Usage Mining and Web Content Mining." 2019 3rd International conference on Electronics, Communication and Aerospace Technology (ICECA)(2019): 1268--1273.
[7]
Denis Kotkov, Joseph A. Konstan, Qian Zhao, and Jari Veijalainen. 2018. Investigating serendipity in recommender systems based on real user feedback. In Proceedings of the 33rd Annual ACM Symposium on Applied Computing. ACM, 1341--1350.
[8]
Ryosuke Koshishima, Motomichi Toyama. "Related Content Recommendation System for Web Index Using Web Resource." DEIM2015. The 7th Forum on Data Engineering and Information Management(The 13th Annual Meeting of the Japan Database Society) 2015.
[9]
Arisa Inoue, Motomichi Toyama. "Keyword conforming service recommendation system in Web Index." DEIM2018. The 10th Forum on Data Engineering and Information Management (The 16th Annual Meeting of the Japan Database Society) 2018.
[10]
Shinzato Takumi, Motomichi Toyama." Page-adaptive Web Index (WIX) file recommendation system." DEIM2019. The 11th Forum on Data Engineering and Information Management (The 17th Annual Meeting of the Japan Database Society) 2019.
[11]
Xingyu Chen, Motomichi Toyama." Proposal of related page recommendation method for improving serendipity in Web IndeX system." DEIM 2020. The 12th Forum on Data Engineering and Information Management (The 18th Annual Meeting of the Japan Database Society) 2020.
[12]
Xin Xin, Xiangnan He, Yongfeng Zhang, Yongdong Zhang, and Joemon Jose. 2019. Relational Collaborative Filtering: Modeling Multiple Item Relations for Recommendation. In Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'19). Association for Computing Machinery, New York, NY, USA, 125--134.
[13]
T. T. S. Nguyen, H. Y. Lu and J. Lu, "Webpage Recommendation Based on Web Usage and Domain Knowledge," in IEEE Transactions on Knowledge and Data Engineering, vol. 26, no. 10, pp. 2574--2587, Oct. 2014.
[14]
Qiuxia Lu, Tianqi Chen, Weinan Zhang, Diyi Yang, and Yong Yu. 2012. Serendipitous Personalized Ranking for Top-N Recommendation. In 2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology, Vol. 1. IEEE, 258--265.
[15]
Makoto Nakatsuji, Yasuhiro Fujiwara, Akimichi Tanaka, Toshio Uchiyama, Ko Fujimura, and Toru Ishida. 2010. Classical Music for Rock Fans?: Novel Recommendations for Expanding User Interests. In Proceedings of the 19th ACM International Conference on Information and Knowledge Management (CIKM '10). ACM, New York, NY, USA, 949--958. https://doi.org/10.1145/1871437.1871558
[16]
Xueqi Li, Wenjun Jiang, Weiguang Chen, Jie Wu, and Guojun Wang. 2019. HAES: A New Hybrid Approach for Movie Recommendation with Elastic Serendipity. In Proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM '19). Association for Computing Machinery, New York, NY, USA, 1503--1512.
[17]
Chang-Dong Wang, Zhi-Hong Deng, Jian-Huang Lai, and Philip S. Yu. 2018. Serendipitous Recommendation in E-Commerce Using Innovator-Based Collaborative Filtering. IEEE Transactions on Cybernetics 49, 7 (2018), 2678--2692. https://doi.org/10.1109/TCYB.2018.2841924
[18]
Alan Menk, Laura Sebastia, and Rebeca Ferreira. 2017. CURUMIM: A Serendipitous Recommender System for Tourism Based on Human Curiosity. In 2017 IEEE 29th International Conference on Tools with Artificial Intelligence (ICTAI). 788--795. https://doi.org/10.1109/ICTAI.2017.00124
[19]
Gopalachari, M. Venu and P. Sammulal. "Personalized collaborative filtering recommender system using domain knowledge." International Conference on Computing and Communication Technologies (2014): 1--6.
[20]
Ishizaki Bunkin, Motomichi Toyama. "Proposal of additional update method for large-scale Aho-Corasick automaton." DEIM2012. The 4th Forum on Data Engineering and Information Management(The 10th Annual Meeting of the Japan Database Society) 2012.
[21]
Liverpool_F.C.https://en.wikipedia.org/wiki/Liverpool_F.C.
[22]
The Son of Man's figure https://www.flickr.com/photos/willwm/2065975725
[23]
MovieLens 25M Dataset https://grouplens.org/datasets/movielens/25m/
[24]
Wikipedia data of jawiki https://dumps.wikimedia.org/jawiki/latest/
[25]
Wikipedia data of enwiki https://dumps.wikimedia.org/enwiki/latest/
Index Terms
- Serendipitous Page Recommendation on Web IndeX System with Potential Preferences
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Published In
November 2020
492 pages
ISBN:9781450389228
DOI:10.1145/3428757
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- Johannes Kepler University, Linz, Austria
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 27 January 2021
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iiWAS '20
iiWAS '20: The 22nd International Conference on Information Integration and Web-based Applications & Services
November 30 - December 2, 2020
Chiang Mai, Thailand
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