Skip to Main content Skip to Navigation
New interface
Conference papers

Effective Tweet Contextualization with Hashtags Performance Prediction and Multi-Document Summarization

Romain Deveaud 1 Florian Boudin 2 
LINA - Laboratoire d'Informatique de Nantes Atlantique
Abstract : In this paper we describe our participation in the INEX 2013 Tweet Contextualization track and present our contributions. Our ap- proach is the same as last year, and is composed of three main com- ponents: preprocessing, Wikipedia articles retrieval and multi-document summarization. We however took advantage of a larger use of hashtags in the topics and used them to enhance the retrieval of relevant Wikipedia articles. We also took advantage of the training examples from last year which allowed us to learn the weights of each sentence selection feature. Two of our submitted runs achieved the two best informativeness results, while our generated contexts where almost as readable as those of the most readable system.
Document type :
Conference papers
Complete list of metadata

Cited literature [6 references]  Display  Hide  Download
Contributor : Florian Boudin Connect in order to contact the contributor
Submitted on : Thursday, December 12, 2013 - 4:47:24 PM
Last modification on : Friday, May 6, 2022 - 3:46:09 AM
Long-term archiving on: : Friday, March 14, 2014 - 11:30:34 AM


Files produced by the author(s)


  • HAL Id : hal-00917956, version 1


Romain Deveaud, Florian Boudin. Effective Tweet Contextualization with Hashtags Performance Prediction and Multi-Document Summarization. INitiative for the Evaluation of XML Retrieval (INEX), Dec 2013, Valence, Spain. pp.n/a. ⟨hal-00917956⟩



Record views


Files downloads