2016
DOI: 10.1016/j.is.2015.07.008
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Social networks and information retrieval, how are they converging? A survey, a taxonomy and an analysis of social information retrieval approaches and platforms

Abstract: a b s t r a c tThere is currently a number of research work performed in the area of bridging the gap between Information Retrieval (IR) and Online Social Networks (OSN). This is mainly done by enhancing the IR process with information coming from social networks, a process called Social Information Retrieval (SIR). The main question one might ask is What would be the benefits of using social information (no matter whether it is content or structure) into the information retrieval process and how is this curre… Show more

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Cited by 84 publications
(48 citation statements)
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References 99 publications
(147 reference statements)
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“…As a result it covers only the "Social Matching: User-oriented" category as we have presented in this survey. Table 2 provides comparative insights of this work in respect to the surveys described in [15], [85], [98], [106] and [107].. It consists of three columns.…”
Section: Similar Surveysmentioning
confidence: 99%
“…As a result it covers only the "Social Matching: User-oriented" category as we have presented in this survey. Table 2 provides comparative insights of this work in respect to the surveys described in [15], [85], [98], [106] and [107].. It consists of three columns.…”
Section: Similar Surveysmentioning
confidence: 99%
“…ask-Valerie (Willems et al, 2015) is an example of an IR system that uses ontologies in the domain of agriculture and forestry for QE. Another approach is to use user profiles and social context to deliver more personalised QE (Bouadjenek et al, 2016).…”
Section: Information Retrievalmentioning
confidence: 99%
“…In personalized search using social media (Jamali and Ester, 2010;Lin et al, 2013), the search process is either performed over "social" data gathered from Web 2.0 applications such as social bookmarking systems, wikis, blogs etc., or it readapts the web search results produced by search engines by using social data (Carman et al, 2008;Bouadjenek et al, 2016). For example, the authors in (Vallet et al, 2010) investigated how the ranking of search engine results can be improved with respect to users if the users' social information is taken into consideration.…”
Section: Personalized Search Using Social Mediamentioning
confidence: 99%
“…Thus the social annotation or bookmarking system demonstrates an extreme example of the vocabulary mismatch problem encountered in personalized web search. To tackle the problem, various personalized query expansion (QE) and results reranking techniques have been proposed and evaluated (Bouadjenek et al, 2016).…”
Section: Introductionmentioning
confidence: 99%