Download e-book for iPad: Advances in natural language processing: 4th international by José Luis Vicedo, Particio Martínez-Barco, Rafael Munoz,

By José Luis Vicedo, Particio Martínez-Barco, Rafael Munoz, Maximiliano Saiz Noeda

ISBN-10: 3540234985

ISBN-13: 9783540234982

This booklet constitutes the refereed court cases of the 4th foreign convention, EsTAL 2004, held in Alicante, Spain in October 2004.

The forty two revised complete papers provided have been rigorously reviewed and chosen from seventy two submissions. The papers deal with present concerns in computational linguistics and monolingual and multilingual clever language processing and functions, specifically written language research and new release; pragmatics, discourse, semantics, syntax, and morphology; lexical assets; observe feel disambiguation; linguistic, mathematical, and morphology; lexical assets; observe feel disambiguation; linguistic, mathematical, and mental versions of language; wisdom acquisition and illustration; corpus-based and statistical language modeling; laptop translation and translation instruments; and computational lexicography; info retrieval; extraction and query answering; automated summarization; record categorization; average language interfaces; and discussion platforms and assessment of systems.

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Additional info for Advances in natural language processing: 4th international conference, EsTAL 2004, Alicante, Spain, October 20-22, 2004: proceedings

Example text

In this paper we focus on improving the basic BLEU algorithm with different representations of the student’s text, by incorporating increasingly more complex syntactic and semantic information into our system. The paper is organised as follows: in Section 2 we describe the variations of the original algorithm. Section 3 describes how the algorithm could be ported through languages automatically with a very slight loss in accuracy. Section 4 explains how it could be integrated inside an e-learning system.

Apply a brevity factor to penalise the short candidate texts (which may have many n-grams in common with the references, but may be incomplete). If the candidate is shorter than the references, this factor is calculated as the ratio between the length of the candidate text and the length of the reference which has the most similar length. The use of several references, made by different human translators, increases the probability that the candidate translation has chosen the same words (and in the same order) as any of the references.

95 confidence. Surprisingly for us, the best result using this modified penalty factor was obtained just for unigrams. In automatic summarisation evaluations, unigrams have been found also to work better than n-grams in some cases [11, 12]. 4 Extensions Proposed There are a number of simple modifications to the original algorithm: 1. g. to manage and for managing. Automatic Assessment of Open Ended Questions 29 2. Removal of Closed-Class Words. These are usually important for finding matching N-grams for long values of N; however, in the case of unigrams, they are probably present in every kind of text and are not very informative.

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Advances in natural language processing: 4th international conference, EsTAL 2004, Alicante, Spain, October 20-22, 2004: proceedings by José Luis Vicedo, Particio Martínez-Barco, Rafael Munoz, Maximiliano Saiz Noeda


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