Annotation of Scientific Summaries for Information Retrieval.

Abstract : We present a methodology combining surface NLP and Machine Learning techniques for ranking asbtracts and generating summaries based on annotated corpora. The corpora were annotated with meta-semantic tags indicating the category of information a sentence is bearing (objective, findings, newthing, hypothesis, conclusion, future work, related work). The annotated corpus is fed into an automatic summarizer for query-oriented abstract ranking and multi- abstract summarization. To adapt the summarizer to these two tasks, two novel weighting functions were devised in order to take into account the distribution of the tags in the corpus. Results, although still preliminary, are encouraging us to pursue this line of work and find better ways of building IR systems that can take into account semantic annotations in a corpus.
Type de document :
Communication dans un congrès
Omar Alonso ; Hugo Zaragoza. ECIR'08 Workshop on: Exploiting Semantic Annotations for Information Retrieval, Mar 2008, Glasgow, United Kingdom. pp.70-83, 2008


https://hal.archives-ouvertes.fr/hal-00635699
Contributeur : Fidelia Ibekwe-Sanjuan <>
Soumis le : mardi 25 octobre 2011 - 17:14:40
Dernière modification le : mercredi 23 mars 2016 - 09:48:48
Document(s) archivé(s) le : jeudi 15 novembre 2012 - 10:32:14

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  • HAL Id : hal-00635699, version 1
  • ARXIV : 1110.5722

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Fidelia Ibekwe-Sanjuan, Fernandez Silvia, Sanjuan Eric, Charton Eric. Annotation of Scientific Summaries for Information Retrieval.. Omar Alonso ; Hugo Zaragoza. ECIR'08 Workshop on: Exploiting Semantic Annotations for Information Retrieval, Mar 2008, Glasgow, United Kingdom. pp.70-83, 2008. <hal-00635699>

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