IRIT at INEX 2014 : Tweet Contextualization Track

Liana Ermakova (1) , Josiane Mothe (1, 2)

1 IRIT-SIG - Systèmes d’Informations Généralisées
2 UT2J - Université Toulouse - Jean Jaurès

The paper presents IRIT's approach used at INEX Tweet Contextualization Track 2014. Systems had to provide a context to a tweet from the perspective of the entity. This year we further modified our approach presented at INEX 2011, 2012 and 2013 underlain by the product of different measures based on smoothing from local context, named entity recognition, part-ofspeech weighting and sentence quality analysis. We introduced two ways to link an entity and a tweet, namely (1) concatenation of the entity and the tweet and (2) usage of the results obtained for the entity as a restriction to filter results retrieved for the tweet. Besides, we examined the influence of topic-comment relationship on contextualization.

Mots clés: Tweet contextualization; Summarization; Information retrieval; Sentence extraction; Readability; Topic-comment relationship

Domaines: Théorie de l'information [cs.IT]; Recherche d'information [cs.IR]

Liana Ermakova, Josiane Mothe. IRIT at INEX 2014 : Tweet Contextualization Track. CLEF 2014 - Conference on Multilingual and Multimodal Information Access Evaluation, Sep 2014, Sheffield, United Kingdom. pp.0. ⟨hal-01156597⟩