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Communication Dans Un Congrès Année : 2019

Patterns Based Query Expansion for Enhanced Search on Twitter Data

Résumé

Social microblogging services have an especially significant role in our society. Twitter is one of the most popular microblogging sites used by people to find relevant information (e.g., breaking news, popular trends, information about people of interest, etc). In this context, retrieving information from such data has recently gained growing attention and opened new challenges. However, the size of such data and queries is usually short and may impact the search result. Query Expansion (QE) has a main task in this issue. In fact, words can have different meanings where only one is used for a given context. In this paper, we propose a QE method by considering the meaning of the context. Thus, we use patterns and Word Embeddings to expand users’ queries. We experiment and evaluate the proposed method on the TREC 2011 dataset containing approximately 16 million tweets and 49 queries. Results revealed the effectiveness of the proposed approach and show the interest of combining patterns and word embedding for enhanced microblog retrieval.
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Dates et versions

hal-02438614 , version 1 (14-01-2020)

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  • HAL Id : hal-02438614 , version 1

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Meryem Bendella, Mohamed Quafafou. Patterns Based Query Expansion for Enhanced Search on Twitter Data. Supplementary Proceedings of International Conference on Formal Concept Analysis (ICFCA) Conference and Workshops, BigFCA Workshops, Jun 2019, Frankfurt, Germany. ⟨hal-02438614⟩
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