Abstract
The user’s search history includes some latent semantics that can be used to improve the user’s interests representation. In this paper we present a personalized information retrieval approach that highlights and use this latent semantics. This semantics, which we call personal semantics, is expressed by the different co-occurrence relationships between relevant terms, according to the different user’s search contexts. This personal semantics is integrated in a geo-social user profile for giving it more representativeness of the user interests. Then, to improve the search results relevance, the user profile is used to reformulate the user query for broadening the search scope without going further than the user needs.
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References
Hadjouni Krir, M.: Un système de recherche d’information personnalisée basé sur la modélisation multidimensionnelle de l’utilisateur. Ph.D. thesis Université Paris Sud – paris XI, France (2012)
Daoud, M., Tamine, L., Boughanem, M.: A personalized search using a semantic distance measure in a graph-based ranking model. J. Inf. Sci. (JIS) 37(6), 614–636 (2011). https://doi.org/10.1177/0165551511420220
Uddin, M.N., Duong, T.H., Sean, V., Jo, G.-S.: Construction of semantic user profile for personalized web search. In: Nguyen, N.-T., Hoang, K., Jȩdrzejowicz, P. (eds.) ICCCI 2012. LNCS (LNAI), vol. 7654, pp. 99–108. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-34707-8_11
Bouhini, C., Géry, M., Largeron, C.: Personalized information retrieval models integrating the user’s profile. In: 10th International Conference on Research Challenges in Information Science (RCIS 2016), June 2016, Grenoble, France, pp. 1–9. IEEE (2016). https://doi.org/10.1109/rcis.2016.7549310, <ujm-01377061>
Aimé, X., Fürst, F., Kuntz, P., Trichet, F.: Enrichissement sémantique de requêtes au moyen d’ontologies de domaine personnalisées. In: Actes de l’atelier «Personnalisation du Web», 10ième Journées francophones d’Extraction et de Gestion de Connaissances (EGC 2010), Hammamet, Tunisie (2010)
Zargayouna, H., Roussey, C., Chevallet, J.-P.: Recherche d’information sémantique: état des lieux. In: TAL, vol. 56, no. 3, pp 49–73 (2015)
Saoud, Z., Kechid, S.: Integrating social profile to improve the source selection and the result merging process in distributed information retrieval. Inf. Sci. 336, 115–128 (2016). https://doi.org/10.1016/j.ins.2015.12.012
Akermi, I., Boughanem, M., Faiz, R.: Une approche de recommandation proactive dans un environnement mobile. In: INFORSID 2015, France, pp. 301–316 (2015)
Buidguaguen, O.: Accès contextuel à l’information dans un environnement mobile: approche basée sur l’utilisation d’un profil situationnel de l’utilisateur et d’un profil de localisation des requêtes. Ph.D. thesis, Univ Toulouse III - Paul Sabatier, France (2011)
Tahar, R., Samir, K.: A geo-social user profile for a personalized information retrieval. In: ACM ICIME 2016, Istanbul, Turkey, pp. 62–66 (2016). http://dx.doi.org/10.1145/3012258.3012270
Aneja, N., Gambhir, S.: Geo-social profile matching algorithm for dynamic interests in Ad-Hoc social network. In: Social Networking-3, pp. 240–247 (2014). http://dx.doi.org/10.4236/sn.2014.35029
Bao, J., Zheng, Y., Mokbel, M.F.: Location-based and preference-aware recommendation using sparse geo-social networking data. In: ACM SIGSPATIAL GIS 2012, Redondo Beach, CA, USA (2012)
Mohamed, S., Abdelmoty, A.I.: Spatio-semantic user profiles in location-based social networks. Int. J. Data Sci. Anal. 4, 127–142 (2017). https://doi.org/10.1007/s41060-017-0059-9
Hopfgartner, F., Jose, J.M.: Semantic user profiling techniques for personalised multimedia recommendation. Multimed. Syst. 16(4–5), 255–274 (2010). https://doi.org/10.1007/s00530-010-0189-6
Salton, G., Buckley, C.: Term weighting approaches in automatic text retrival. Inf. Process. Manag. 24, 513–523 (1988)
Toms, E., Agosti, M., Fuhr, N., Vakkari, P.: Evaluation methodologies in information retrieval. In: Agstuhl Reports, vol. 3, no.10, pp. 92–126 (2013)
Khazri, M., Tmar, M., Abid, M., Boughanem, M.: Proposition pour l’intégration des réseaux petits mondes en recherche d’information. In: Assogba, M.K. (ed.) Numéro spécial CARI, ARIMA, vol. 11, pp. 69–81 (2008)
Boubekeur, F., Azzoug, W.: Concept-based indexing in text information retrieval. Int. J. Comput. Sci. Inf. Technol. (IJCSIT) 5(1), 119–136 (2013). https://doi.org/10.5121/ijcsit.2013.5110
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Rafa, T., Kechid, S. (2018). A Semantic-Based Personalized Information Retrieval Approach Using a Geo-Social User Profile. In: Elloumi, M., et al. Database and Expert Systems Applications. DEXA 2018. Communications in Computer and Information Science, vol 903. Springer, Cham. https://doi.org/10.1007/978-3-319-99133-7_25
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DOI: https://doi.org/10.1007/978-3-319-99133-7_25
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