INEX2014: Tweet Contextualization Using Association Rules between Terms
Meriem Amina Zingla, Mohamed Ettaleb, Cherif Chiraz Latiri, Yahya Slimani · 2014
Abstract. Tweets are short messages that do not exceed 140 characters. Since they must be written respecting this limitation, a particular vocab-ulary is used. To make them understandable to a reader, it is therefore necessary to know their context. In this paper, we describe our approach submitted for the tweet contextualization track in CLEF 2014 (Confer-ence and Labs of Evaluation Forums). This approach allows the extension of the tweet’s vocabulary by a set of thematically related words using mining association rules between terms.