Abstract
An important task in recommender systems is suggesting relevant venues in a city to a user. These suggestions are usually created by exploiting the user’s history of preferences, which are, for example, collected in previously visited cities. In this paper, we first introduce a user model based on venues’ categories and their descriptive keywords extracted from Foursquare tips. Then, we propose an enriched user model which leverages the users’ reviews from Yelp. Our participation in the TREC 2015 Contextual Suggestion track, confirmed that our model outperforms other approaches by a significant margin.
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Aliannejadi, M., Bahrainian, S.A., Giachanou, A., Crestani, F., University of lugano at TREC 2015: Contextual suggestion and temporal summarization tracks. In: TREC, Gaithersburg, Maryland, USA, November 2015
Chen, G., Chen, L.: Recommendation based on contextual opinions. In: Dimitrova, V., Kuflik, T., Chin, D., Ricci, F., Dolog, P., Houben, G.-J. (eds.) UMAP 2014. LNCS, vol. 8538, pp. 61–73. Springer, Heidelberg (2014)
Chen, L., Chen, G., Wang, F.: Recommender systems based on user reviews: the state of the art. User Model. User-Adap. Inter. 25(2), 99–154 (2015)
Cheng, C., Yang, H., King, I., Lyu, M.R.: Fused matrix factorization with geographical and social influence in location-based social networks. In: AAAI, Toronto, Canada, July 2012
Cortes, C., Vapnik, V.: Support-vector networks. Mach. Learn. 20(3), 273–297 (1995)
Dean-Hall, A., Clarke, C.L.A., Kamps, J., Kiseleva, J., Voorhees, E.M.: Overview of the TREC 2015 contextual suggestion track. In: TREC, Gaithersburg, USA, November 2015
Esparza, S.G., O’Mahony, M.P., Smyth, B.: On the real-time web as a source of recommendation knowledge. In: RecSys, Barcelona, Spain, pp. 305–308 September 2010
Gao, H., Tang, J., Hu, X., Liu, H.: Exploring temporal effects for location recommendation on location-based social networks. In: RecSys, Hong Kong, China, pp. 93–100, October 2013
Griesner, J., Abdessalem, T., Naacke, H.: POI recommendation: towards fused matrix factorization with geographical and temporal influences. In: RecSys, Vienna, Austria, pp. 301–304, September 2015
Hariri, N., Zheng, Y., Mobasher, B., Burke, R.: Context-aware recommendation based on review mining. In: Proceedings of the 9th Workshop on Intelligent Techniques for Web Personalization and Recommender Systems (2011)
McCreadie, R., Vargas, S., MacDonald, C., Ounis, I., Mackie, S., Manotumruksa, J., McDonald, G.: University of glasgow at TREC 2015: experiments with terrier in contextual suggestion, temporal summarisation and dynamic domain tracks. In: TREC, Gaithersburg, USA, November 2015
Rikitianskii, A., Harvey, M., Crestani, F.: A personalised recommendation system for context-aware suggestions. In: de Rijke, M., Kenter, T., de Vries, A.P., Zhai, C.X., de Jong, F., Radinsky, K., Hofmann, K. (eds.) ECIR 2014. LNCS, vol. 8416, pp. 63–74. Springer, Heidelberg (2014)
Su, X., Khoshgoftaar, T.M.: A survey of collaborative filtering techniques. Adv. Artif. Intell. 2009, 421425:1–421425:19 (2009)
Yang, P., Fang, H.: University of delaware at TREC 2015: combining opinion profile modeling with complex context filtering for contextual suggestion. In: TREC, Gaithersburg, USA, November 2015
Yuan, Q., Cong, G., Ma, Z., Sun, A., Magnenat-Thalmann, N.: Time-aware point-of-interest recommendation. In: SIGIR, Dublin, Ireland, pp. 363–372, July 2013
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Aliannejadi, M., Mele, I., Crestani, F. (2016). User Model Enrichment for Venue Recommendation. In: Ma, S., et al. Information Retrieval Technology. AIRS 2016. Lecture Notes in Computer Science(), vol 9994. Springer, Cham. https://doi.org/10.1007/978-3-319-48051-0_16
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DOI: https://doi.org/10.1007/978-3-319-48051-0_16
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