GRSPOI: A Point-of-Interest Recommender Systems for Groups Using Diversification
Resumo
Context: With the massive availability and usage of the Internet, the search for Points of Interest is becoming an arduous task. Thus, Points of Interest Recommender Systems arise to help users in the search. These systems traditionally recommend points of interest to individual users, however, there are scenarios in which individuals gather, therefore creating the need to recommend items to groups. Problem: The problem is that users’ location is not always considered, only their preferences. Hence, there are studies indicating the greater is users commuting, the less POIs relevance appears to them. Furthermore, the recommendations belong to the same category, without diversity. Solution: Develop a Points of Interest Recommendation System for a group using a diversity algorithm, based on members’ preferences and their locations. IS Theory: This work was conceived in the light of the General Theory of Systems, in particular open systems as they undergo interactions with the environment where they can be inserted. Recommender systems depend on a continuous exchange of information with the external environment. Method: The research is based on the literature, and its evaluation was carried out through an online experiment with real users. The analysis of the results was carried out with a qualitative approach. Summary of Results: Precision metrics were used in the evaluation, and it was observed that the level at which the results are analyzed is relevant. For the top-3, recommendations without diversity performed better, but at the top-5 and top-10 levels, diversification had a positive impact on the results. Contributions and Impact in the IS area: A recommendation system for groups that considers the geographic location of users, their preferences and the diversity of recommendations. In addition, we provide the community with a dataset with user ratings of points of interest and geolocation information.
Palavras-chave:
Recommendation System, Recommendation for Groups, Points of Interest
Referências
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Zahra Bahari Sojahrood and Mohammad Taleai. [n.d.]. Behavior-based POI recommendation for small groups in location-based social networks. Transactions in GIS 1, 2 ([n. d.]), 10.
Zahra Bahari Sojahrood and Mohammad Taleai. 2021. A POI group recommendation method in location-based social networks based on user influence. Expert Systems with Applications 171 (2021), 114593.
Ludovico Boratto and Salvatore Carta. 2011. State-of-the-Art in Group Recommendation and New Approaches for Automatic Identification of Groups. Springer Berlin Heidelberg, Berlin, Heidelberg, 1–20.
Keith Bradley and Barry Smyth. 2001. Improving recommendation diversity. In Proceedings of the Twelfth Irish Conference on Artificial Intelligence and Cognitive Science, Maynooth, Ireland. Citeseer, 85–94.
Lucas Carvalho and Hendrik Macedo. 2014. Introdução aos Sistemas de Recomendação para Grupos. Revista de Informática Teórica e Aplicada 21, 1 (2014), 77–109.
João Paulo Dias de Almeida, Frederico Araújo Durão, and Arthur Fortes da Costa. 2018. Enhancing Spatial Keyword Preference Query with Linked Open Data. J. Univers. Comput. Sci. 24, 11 (2018), 1561–1581.
Luis M de Campos, Juan M Fernández-Luna, Juan F Huete, and Miguel A Rueda-Morales. 2009. Managing uncertainty in group recommending processes. User Modeling and User-Adapted Interaction 19, 3 (2009), 207–242.
Ram Deepak Gottapu and Lakshmi Venkata Sriram Monangi. 2017. Point-Of-Interest Recommender System for Social Groups. Procedia Computer Science 114 (2017), 159–164. Complex Adaptive Systems Conference with Theme: Engineering Cyber Physical Systems, 2017, Chicago, Illinois, USA.
Bo Hu and Martin Ester. 2013. Spatial topic modeling in online social media for location recommendation. In Proceedings of the 7th ACM conference on Recommender systems. ACM, 25–32.
Anthony Jameson. 2004. More than the sum of its members: challenges for group recommender systems. In Proceedings of the working conference on Advanced visual interfaces. ACM, 48–54.
Marius Kaminskas and Derek Bridge. 2016. Diversity, Serendipity, Novelty, and Coverage: A Survey and Empirical Analysis of Beyond-Accuracy Objectives in Recommender Systems. ACM Trans. Interact. Intell. Syst. 7, 1, Article 2 (Dec. 2016), 42 pages. https://doi.org/10.1145/2926720
Takeshi Kurashima, Tomoharu Iwata, Takahide Hoshide, Noriko Takaya, and Ko Fujimura. 2013. Geo topic model: joint modeling of user's activity area and interests for location recommendation. In Proceedings of the sixth ACM international conference on Web search and data mining. ACM, 375–384.
Bae-Hee Lee, Heung-Nam Kim, Jin-Guk Jung, and Geun-Sik Jo. 2006. Location-based service with context data for a restaurant recommendation. In International Conference on Database and Expert Systems Applications. Springer, 430–438.
Defu Lian, Yong Ge, Fuzheng Zhang, Nicholas Jing Yuan, Xing Xie, Tao Zhou, and Yong Rui. 2015. Content-aware collaborative filtering for location recommendation based on human mobility data. In 2015 IEEE international conference on data mining. IEEE, 261–270.
Bin Liu, Yanjie Fu, Zijun Yao, and Hui Xiong. 2013. Learning geographical preferences for point-of-interest recommendation. In Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, 1043–1051.
Yuanliu Liu, Pengpeng Zhao, Victor S Sheng, Zhixu Li, An Liu, Jian Wu, and Zhiming Cui. 2015. RPCV: Recommend Potential Customers to Vendors in Location-Based Social Network. In International Conference on Web-Age Information Management. Springer, 272–284.
Christopher D Manning, Hinrich Schütze, and Prabhakar Raghavan. 2008. Introduction to information retrieval. Cambridge university press.
Judith Masthoff. 2015. Group recommender systems: aggregation, satisfaction and group attributes. In Recommender Systems Handbook. Springer, 743–776.
Thanh Nguyen, Thanh Cong Phan, Thanh Tam Nguyen, Quoc Hung Nguyen, and Bela Stantic. 2018. Diversifying Group Recommendation. (2018), 10.
Thuy Ngoc Nguyen and Francesco Ricci. 2017. Dynamic elicitation of user preferences in a chat-based group recommender system. In Proceedings of the Symposium on Applied Computing. ACM, 1685–1692.
Amanda Oliveira and Frederico Durao. 2021. A Group Recommendation Model Using Diversification Techniques. In Proceedings of the 54th Hawaii International Conference on System Sciences. Hawaii, HI, USA, 2669.
Mark O'connor, Dan Cosley, Joseph A Konstan, and John Riedl. 2001. PolyLens: a recommender system for groups of users. In ECSCW 2001. Springer, 199–218.
Denis Parra and Shaghayegh Sahebi. 2013. Recommender systems: Sources of knowledge and evaluation metrics. In Advanced techniques in web intelligence-2. Springer, 149–175.
Lara Quijano-Sanchez, Juan A Recio-Garcia, Belen Diaz-Agudo, and Guillermo Jimenez-Diaz. 2013. Social factors in group recommender systems. ACM Transactions on Intelligent Systems and Technology (TIST) 4, 1(2013), 8.
Logesh Ravi, V Subramaniyaswamy, Malathi Devarajan, KS Ravichandran, S Arunkumar, V Indragandhi, and V Vijayakumar. 2019. SECRECSY: A Secure Framework for Enhanced Privacy-Preserving Location Recommendations in Cloud Environment. Wireless Personal Communications(2019), 1–39.
Logesh Ravi and Subramaniyaswamy Vairavasundaram. 2016. A collaborative location based travel recommendation system through enhanced rating prediction for the group of users. Computational intelligence and neuroscience 2016 (2016).
Amartya Sen. 1986. Social choice theory. Handbook of mathematical economics 3 (1986), 1073–1181.
Yali Si, Fuzhi Zhang, and Wenyuan Liu. 2017. CTF-ARA: An adaptive method for POI recommendation based on check-in and temporal features. Knowledge-Based Systems 128 (2017), 59–70.
Johny Silva and Yuri Lacerda. 2017. MoveAndShot - Um aplicativo para recomendação dos melhores pontos para captura de fotografias. In Anais do XIII Simpósio Brasileiro de Sistemas de Informação (Lavras). SBC, Porto Alegre, RS, Brasil, 190–197. https://doi.org/10.5753/sbsi.2017.6042
W. R. Tobler. 1970. A Computer Movie Simulating Urban Growth in the Detroit Region. Economic Geography 46(1970), 234–240.
Danfeng Yan, Xuan Zhao, and Zhengkai Guo. 2018. Personalized POI Recommendation Based on Subway Network Features and Users’ Historical Behaviors. Wireless Communications and Mobile Computing 2018 (2018).
Vincent W Zheng, Yu Zheng, Xing Xie, and Qiang Yang. 2010. Collaborative location and activity recommendations with GPS history data. In Proceedings of the 19th international conference on World wide web. ACM, 1029–1038.
Cai-Nicolas Ziegler, Sean M. McNee, Joseph A. Konstan, and Georg Lausen. 2005. Improving Recommendation Lists through Topic Diversification. In Proceedings of the 14th International Conference on World Wide Web (Chiba, Japan) (WWW ’05). ACM, New York, NY, USA, 22–32.
Zahra Bahari Sojahrood and Mohammad Taleai. [n.d.]. Behavior-based POI recommendation for small groups in location-based social networks. Transactions in GIS 1, 2 ([n. d.]), 10.
Zahra Bahari Sojahrood and Mohammad Taleai. 2021. A POI group recommendation method in location-based social networks based on user influence. Expert Systems with Applications 171 (2021), 114593.
Ludovico Boratto and Salvatore Carta. 2011. State-of-the-Art in Group Recommendation and New Approaches for Automatic Identification of Groups. Springer Berlin Heidelberg, Berlin, Heidelberg, 1–20.
Keith Bradley and Barry Smyth. 2001. Improving recommendation diversity. In Proceedings of the Twelfth Irish Conference on Artificial Intelligence and Cognitive Science, Maynooth, Ireland. Citeseer, 85–94.
Lucas Carvalho and Hendrik Macedo. 2014. Introdução aos Sistemas de Recomendação para Grupos. Revista de Informática Teórica e Aplicada 21, 1 (2014), 77–109.
João Paulo Dias de Almeida, Frederico Araújo Durão, and Arthur Fortes da Costa. 2018. Enhancing Spatial Keyword Preference Query with Linked Open Data. J. Univers. Comput. Sci. 24, 11 (2018), 1561–1581.
Luis M de Campos, Juan M Fernández-Luna, Juan F Huete, and Miguel A Rueda-Morales. 2009. Managing uncertainty in group recommending processes. User Modeling and User-Adapted Interaction 19, 3 (2009), 207–242.
Ram Deepak Gottapu and Lakshmi Venkata Sriram Monangi. 2017. Point-Of-Interest Recommender System for Social Groups. Procedia Computer Science 114 (2017), 159–164. Complex Adaptive Systems Conference with Theme: Engineering Cyber Physical Systems, 2017, Chicago, Illinois, USA.
Bo Hu and Martin Ester. 2013. Spatial topic modeling in online social media for location recommendation. In Proceedings of the 7th ACM conference on Recommender systems. ACM, 25–32.
Anthony Jameson. 2004. More than the sum of its members: challenges for group recommender systems. In Proceedings of the working conference on Advanced visual interfaces. ACM, 48–54.
Marius Kaminskas and Derek Bridge. 2016. Diversity, Serendipity, Novelty, and Coverage: A Survey and Empirical Analysis of Beyond-Accuracy Objectives in Recommender Systems. ACM Trans. Interact. Intell. Syst. 7, 1, Article 2 (Dec. 2016), 42 pages. https://doi.org/10.1145/2926720
Takeshi Kurashima, Tomoharu Iwata, Takahide Hoshide, Noriko Takaya, and Ko Fujimura. 2013. Geo topic model: joint modeling of user's activity area and interests for location recommendation. In Proceedings of the sixth ACM international conference on Web search and data mining. ACM, 375–384.
Bae-Hee Lee, Heung-Nam Kim, Jin-Guk Jung, and Geun-Sik Jo. 2006. Location-based service with context data for a restaurant recommendation. In International Conference on Database and Expert Systems Applications. Springer, 430–438.
Defu Lian, Yong Ge, Fuzheng Zhang, Nicholas Jing Yuan, Xing Xie, Tao Zhou, and Yong Rui. 2015. Content-aware collaborative filtering for location recommendation based on human mobility data. In 2015 IEEE international conference on data mining. IEEE, 261–270.
Bin Liu, Yanjie Fu, Zijun Yao, and Hui Xiong. 2013. Learning geographical preferences for point-of-interest recommendation. In Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, 1043–1051.
Yuanliu Liu, Pengpeng Zhao, Victor S Sheng, Zhixu Li, An Liu, Jian Wu, and Zhiming Cui. 2015. RPCV: Recommend Potential Customers to Vendors in Location-Based Social Network. In International Conference on Web-Age Information Management. Springer, 272–284.
Christopher D Manning, Hinrich Schütze, and Prabhakar Raghavan. 2008. Introduction to information retrieval. Cambridge university press.
Judith Masthoff. 2015. Group recommender systems: aggregation, satisfaction and group attributes. In Recommender Systems Handbook. Springer, 743–776.
Thanh Nguyen, Thanh Cong Phan, Thanh Tam Nguyen, Quoc Hung Nguyen, and Bela Stantic. 2018. Diversifying Group Recommendation. (2018), 10.
Thuy Ngoc Nguyen and Francesco Ricci. 2017. Dynamic elicitation of user preferences in a chat-based group recommender system. In Proceedings of the Symposium on Applied Computing. ACM, 1685–1692.
Amanda Oliveira and Frederico Durao. 2021. A Group Recommendation Model Using Diversification Techniques. In Proceedings of the 54th Hawaii International Conference on System Sciences. Hawaii, HI, USA, 2669.
Mark O'connor, Dan Cosley, Joseph A Konstan, and John Riedl. 2001. PolyLens: a recommender system for groups of users. In ECSCW 2001. Springer, 199–218.
Denis Parra and Shaghayegh Sahebi. 2013. Recommender systems: Sources of knowledge and evaluation metrics. In Advanced techniques in web intelligence-2. Springer, 149–175.
Lara Quijano-Sanchez, Juan A Recio-Garcia, Belen Diaz-Agudo, and Guillermo Jimenez-Diaz. 2013. Social factors in group recommender systems. ACM Transactions on Intelligent Systems and Technology (TIST) 4, 1(2013), 8.
Logesh Ravi, V Subramaniyaswamy, Malathi Devarajan, KS Ravichandran, S Arunkumar, V Indragandhi, and V Vijayakumar. 2019. SECRECSY: A Secure Framework for Enhanced Privacy-Preserving Location Recommendations in Cloud Environment. Wireless Personal Communications(2019), 1–39.
Logesh Ravi and Subramaniyaswamy Vairavasundaram. 2016. A collaborative location based travel recommendation system through enhanced rating prediction for the group of users. Computational intelligence and neuroscience 2016 (2016).
Amartya Sen. 1986. Social choice theory. Handbook of mathematical economics 3 (1986), 1073–1181.
Yali Si, Fuzhi Zhang, and Wenyuan Liu. 2017. CTF-ARA: An adaptive method for POI recommendation based on check-in and temporal features. Knowledge-Based Systems 128 (2017), 59–70.
Johny Silva and Yuri Lacerda. 2017. MoveAndShot - Um aplicativo para recomendação dos melhores pontos para captura de fotografias. In Anais do XIII Simpósio Brasileiro de Sistemas de Informação (Lavras). SBC, Porto Alegre, RS, Brasil, 190–197. https://doi.org/10.5753/sbsi.2017.6042
W. R. Tobler. 1970. A Computer Movie Simulating Urban Growth in the Detroit Region. Economic Geography 46(1970), 234–240.
Danfeng Yan, Xuan Zhao, and Zhengkai Guo. 2018. Personalized POI Recommendation Based on Subway Network Features and Users’ Historical Behaviors. Wireless Communications and Mobile Computing 2018 (2018).
Vincent W Zheng, Yu Zheng, Xing Xie, and Qiang Yang. 2010. Collaborative location and activity recommendations with GPS history data. In Proceedings of the 19th international conference on World wide web. ACM, 1029–1038.
Cai-Nicolas Ziegler, Sean M. McNee, Joseph A. Konstan, and Georg Lausen. 2005. Improving Recommendation Lists through Topic Diversification. In Proceedings of the 14th International Conference on World Wide Web (Chiba, Japan) (WWW ’05). ACM, New York, NY, USA, 22–32.
Publicado
16/05/2022
Como Citar
CRUZ, Jadna Almeida da; OLIVEIRA, Amanda Chagas; SILVA, Diego Corrêa da; DURÃO, Frederico Araújo.
GRSPOI: A Point-of-Interest Recommender Systems for Groups Using Diversification. In: SIMPÓSIO BRASILEIRO DE SISTEMAS DE INFORMAÇÃO (SBSI), 18. , 2022, Curitiba.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2022
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