Jesús Vilares

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The work described in this paper was originally motivated by the need to map verbs associated with FrameNet 2.0 frames to appropriate WordNet 2.0 senses. As the work evolved, it became apparent that the developed method was applicable for a number of other tasks, including assignment of WordNet senses to word lists used in attitude and opinion analysis, and(More)
With increasingly higher numbers of non-English language web searchers the problems of efficient handling of non-English Web documents and user queries are becoming major issues for search engines. The main aim of this review paper is to make researchers aware of the existing problems in monolingual non-English Web retrieval by providing an overview of open(More)
This article describes the application of lemmatization and shallow parsing as a linguistically-based alternative to stemming in Text Retrieval, with the aim of managing linguistic variation at both word level and phrase level. Several alternatives for selecting the index terms among the syntactic dependencies detected by the parser are evaluated. Though(More)
In this paper we consider a set of natural language processing techniques that can be used to analyze large amounts of texts, focusing on the advanced tokenizer which accounts for a number of complex linguistic phenomena, as well as for pre-tagging tasks such as proper noun recognition. We also show the results of several experiments performed in order to(More)
The performance of Information Retrieval systems is limited by the linguistic variation present in natural language texts. Word-level Natural Language Processing techniques have been shown to be useful in reducing this variation. In this article, we summarize our work on the extension of these techniques for dealing with phrase-level variation in European(More)
In this our first participation in CLEF, we have applied Natural Language Processing techniques for single word and multi-word term conflation. We have tested several approaches at different levels of text processing in our experiments: firstly, we have lemmatized the text to avoid inflectional variation; secondly, we have expanded the queries through(More)
To date, attempts for applying syntactic information in the document-based retrieval model dominant have led to little practical improvement, mainly due to the problems associated with the integration of this kind of information into the model. In this article we propose the use of a locality-based retrieval model for reranking, which deals with syntactic(More)
This paper describes our participation at RepLab 2014, a competitive evaluation for reputation monitoring on Twitter. The following tasks were addressed: (1) categorisation of tweets with respect to standard reputation dimensions and (2) characterisation of Twitter profiles, which includes: (2.1) identifying the type of those profiles, such as journalist or(More)