Catálogo de publicaciones - libros

Within the framework of Transformation Based Learning (TBL), the rule template is one of the most important elements in the learning process. This paper presents a new model for TBL templates, in which the basic unit, denominated here as an atomic term (AT), encodes a variable sized window and a test that precedes the capture of a feature’s value. A case study of Portuguese NP identification is described and the experimental results obtained are presented.

This paper describes an approach for the integration of linguistic information in passage retrieval in an open-source question answering system for Dutch. Annotation produced by the wide-coverage dependency parser Alpino is stored in multiple index layers to be matched with natural language question that have been analyzed by the same parser. We present a genetic algorithm to select features to be included in retrieval queries and for optimizing keyword weights. The system is trained on questions annotated with their answers from the competition on Dutch question answering within the Cross-Language Evaluation Forum (CLEF). The optimization yielded a significant improvement of about 19% in mean reciprocal rank scores on unseen evaluation data compared to the base-line using traditional information retrieval with plain text keywords.

We report on a set of experiments in text mining, specifically, finding semantic patterns given only a few keywords. The experiments employ the Counter-training framework for discovery of semantic knowledge from raw text in a weakly supervised fashion. The experiments indicate that the framework is suitable for efficient acquisition of semantic word classes and collocation patterns, which may be used for Information Extraction.

This paper presents a new method that aims at improving semantic indexing while reducing the number of indexing terms. Indexing terms are determined using a minimum redundancy cut in a hierarchy of conceptual hypernyms provided by an ontology (e.g. , ). The results of some information retrieval experiments carried out on several standard document collections using the ontology are presented, illustrating the benefit of the method.

This paper describes an original hybrid system that extracts multiword unit candidates from part-of-speech tagged corpora. While classical hybrid systems manually define local part-of-speech patterns that lead to the identification of well-known multiword units (mainly compound nouns), we automatically identify relevant syntactical patterns from the corpus. Word statistics are then combined with the endogenously acquired linguistic information in order to extract the most relevant sequences of words. As a result, (1) human intervention is avoided providing total flexibility of use of the system and (2) different multiword units like phrasal verbs, adverbial locutions and prepositional locutions may be identified. Finally, we propose an exhaustive evaluation of our architecture based on the multi-domain, bilingual Slovene-English IJS-ELAN corpus where surprising results are evidenced. To our knowledge, this challenge has never been attempted before.

This paper presents a variant of Lappin and Leass’ Algorithm for pronoun resolution in Portuguese texts; the algorithm resolves third person pronominal anaphora, as well as reflexive and reciprocal pronouns. It relies on salience measures, derived from the syntactic structure of the sentence, and on a simple discourse representation model. The algorithm, as well as its evaluation with legal and literary corpora, are presented.

Stemming algorithms have traditionally been utilized in information retrieval systems as they generate a more concise word representation. However, the efficiency of these algorithms varies according to the language they are used with. This paper presents STEMBR, a stemmer for Brazilian Portuguese whereby the suffix treatment is based on a statistical study of the frequency of the last letter for words found in Brazilian web pages. The proposed stemmer is compared with another algorithm specifically developed for Portuguese. The results show the efficiency of our stemmer.