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2018 | OriginalPaper | Buchkapitel

Toward a Context-Aware Multilingual Personalized Search

verfasst von : Mohamed Seghir Hadj Ameur, Youcef Moulahoum, Lamia Berkani, Ahmed Guessoum

Erschienen in: Arabic Language Processing: From Theory to Practice

Verlag: Springer International Publishing

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Abstract

In recent years, personalized search has widely been used in Information Retrieval Systems (IRS) to provide the end user with more sophisticated and accurate search results. A basic element that plays an important role in personalized search is the user context which contains several aspects such as the user preferences, navigation history, habits, etc. A user may express his information needs in various languages. This requires the IRS to be able to consider all the contextual information provided in these languages. In this work, we present M-CAIRS, a Multilingual Context-aware Information Retrieval System that takes into account multilingual user contexts to better model the user search interests. Experimental results show a strong correlation between the user’s relevance judgment and the automatic results obtained by our system, which proves the consistency and adequacy of our proposal.

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Fußnoten
1
Internet live stats is a website that provides live statistics regarding the Internet http://​www.​internetlivestat​s.​com.
 
3
The nodes of the ontology (hierarchy) are generally called concepts.
 
5
We note that other languages can be integrated exactly in the same way.
 
6
We have used the Google Language Detection API [27], to identify the document language.
 
7
If a certain document contain textual information in several languages, the text identification process will chose the most dominant one among them.
 
8
The page rank algorithm works by estimating the rank/quality of a web page based on the number and the importance of the web pages that reference it.
 
9
We note that we have implemented ourselves all the systems we have compared; thus conclusions should be taken with some caution.
 
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Metadaten
Titel
Toward a Context-Aware Multilingual Personalized Search
verfasst von
Mohamed Seghir Hadj Ameur
Youcef Moulahoum
Lamia Berkani
Ahmed Guessoum
Copyright-Jahr
2018
DOI
https://doi.org/10.1007/978-3-319-73500-9_13