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Word Similarity Based Model for Tweet Stream Prospective Notification

Chellal, Abdelhamid and Boughanem, Mohand and Dousset, Bernard Word Similarity Based Model for Tweet Stream Prospective Notification. (2017) In: ECIR 2017 39th European Conference on Information Retrieval, 9 April 2017 - 13 April 2017 (Aberdeen, United Kingdom).

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Official URL: https://doi.org/10.1007/978-3-319-56608-5_62


The prospective notification on tweet streams is a challenge task in which the user wishes to receive timely, relevant, and non-redundant update notification to remain up-to-date. To be effective the system attempts to optimize the aforementioned properties (timeliness, relevance, novelty and redundancy) and find a trade-off between pushing too many and pushing too few tweets. We propose an adaptation of the extended Boolean model based on word similarity to estimate the relevance score of tweets. We take advantage of the word2vec model to capture the similarity between query terms and tweet terms. Experiments on the TREC MB RTF 2015 dataset show that our approach outperforms all considered baselines.

Item Type:Conference or Workshop Item (Paper)
HAL Id:hal-02611135
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
Laboratory name:
Deposited On:18 May 2020 08:45

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