Personalized information retrieval models integrating the user's profile

Abstract : Personalized Information Retrieval (PIR) exploits the user's data in order to refine the retrieval, like for instance when users with different backgrounds may express different information needs with the same query. However, this additional source of information is not supported by the classical Information Retrieval (IR) process. In order to overcome this limit, we propose to generate the user profile out from his profile and social data. Then, we introduce several Personalized Information Retrieval models which integrate this profile at the querying step, allowing to personalize the search results. We study several combinations of the initial user's query with his profile. Furthermore, we present a PIR test collection that we built from the social bookmarking network Delicious, in order to evaluate our PIR models. Our experiments showed that the PIR models improve the retrieval results.
Document type :
Conference papers
Complete list of metadatas

Cited literature [19 references]  Display  Hide  Download

https://hal-ujm.archives-ouvertes.fr/ujm-01377061
Contributor : Mathias Géry <>
Submitted on : Monday, October 10, 2016 - 9:58:43 AM
Last modification on : Wednesday, November 21, 2018 - 1:44:02 PM
Long-term archiving on : Wednesday, January 11, 2017 - 12:40:21 PM

File

paper_34.pdf
Files produced by the author(s)

Identifiers

Citation

Chahrazed Bouhini, Mathias Géry, Christine Largeron. Personalized information retrieval models integrating the user's profile. 10th International Conference on Research Challenges in Information Science (RCIS 2016), Jun 2016, Grenoble, France. pp.1 - 9, ⟨10.1109/RCIS.2016.7549310⟩. ⟨ujm-01377061⟩

Share

Metrics

Record views

98

Files downloads

510