direct word sense matching for lexical substitution

... target words only for a strict sub- 455 4.2 Supervised Methods 4.2.1 Indirect approach The indirect approach for sense matching fol- lows the traditional scheme of performing WSD for lexical substitution. ... unsupervised indirect meth- ods for the sense matching task. Direct. Conceptually, the most appealing solu- tion for the sense matching task is the one-class approach proposed for the direct method ... one definition for each possible word sense. The algo- rithm looks for words in the sense definitions that overlap with context words in the given sentence, and chooses the sense that yields maximal word overlap....

Ngày tải lên: 20/02/2014, 12:20

... efficient algorithm for minimally supervised word- sense dis- ambiguation that attempts to disambiguate all content words in a text using WordNet senses. The results ob- tained on both SENSEVAL-2 and SENSEVAL-3 ... topically related word classes, semantic density, and others. In recent SENSEVAL-3 evaluations, the most suc- cessful approaches for all words word sense disam- biguation relied on information drawn ... algorithm for joint parameter optimization and feature selection. A sep- arate word expert” is learned for each ambiguous word, using a concatenated corpus of English sense- 53 Training SENSEVAL-2 SENSEVAL-3 Model...

Ngày tải lên: 20/02/2014, 15:20

... Perform Word Sense Disambiguation. Sinopalnikova, A. (2004). Word Association Thesau- rus as a Resource for Building Wordnet. In GWC 2004. Sussna, M. (1993). Word Sense Disambiguation for ... for word relationship in human cognition after col- lecting the first response words for the stimulus words list (Kiss et al., 1973). Take the words eat and food for example. There is no direct ... relations in words, we transform the context words of the target into its associated words, which can be retrieved in the EAT, to augment the performance of the lexical hub. There are two word lists...

Ngày tải lên: 08/03/2014, 02:21

Ngày tải lên: 17/03/2014, 22:20

... Cross-Lingual Word Sense Disambiguation task for all five target languages. 1 Introduction Word Sense Disambiguation (WSD) is the NLP task that consists in selecting the correct sense of a polysemous word ... from the Uvt-WSD and ParaSense systems in the sense that the word senses are derived from WordNet, whereas the other systems do not use any external resources. The results for all five classifiers ... related to the focus word itself being the word form of the focus word, the lemma, Part-of-Speech and chunk information ã local context features related to a window of three words preceding and...

Ngày tải lên: 20/02/2014, 05:20

... the Senseval 2 English lexical sample task. It includes 73 target words, among which nouns, adjectives, adverbs and verbs. For each word, training and test instances tagged with WordNet senses ... Combining contextual features for word sense disambigua- tion. In Proceedings of the SIGLEX/SENSEVAL Workshop on Word Sense Disambiguation: Re- cent Successes and Future Directions, pages 88– 94, ... Association for Com- putational Linguistics. Taku Kudo and Yuji Matsumoto. Fast methods for kernel-based text analysis. In Proceedings of Table 1: Two of the Senseval-2 sense classes for the target word...

Ngày tải lên: 20/02/2014, 16:20

... pre- dominant senses between the examples gathered from parallel texts and the evaluation data for the two SENSEVAL tasks. This gave a set of 6 nouns for SENSEVAL-2 and 9 nouns for SENSEVAL- 3. For each ... score for each sense of a word to predict the predominant sense. As in our earlier work (Chan and Ng, 2005b), we normalized the prevalence score of each sense to obtain estimated sense priors for ... 19%. One reason for this is the difference in sense priors (i.e., the proportions of the different senses of a word) between BC and WSJ. For in- stance, the noun interest has these 6 senses in the DSO...

Ngày tải lên: 08/03/2014, 02:21

... 1997). For example, in machine translation, WSD, or translation disambiguation, is responsible for identifying the correct translation for an ambiguous source word. There is not always a direct ... customized for this monolingual task, the ILP approach signif- icantly outperforms the majority sense baseline and performs as well as the state-of-the-art system re- porting results for the same ... frequent translation are shown in Table 1. For the monolingual scenario, we use the sense tagged corpus and sense repositories provided for verbs in Senseval-3. There are 32 verbs with be- tween...

Ngày tải lên: 08/03/2014, 02:21

... D T repeat p min ← ∞ for each d ∈ D A do bs ← word sense prediction for d using Γ p ← confidence of prediction bs if p < p min then p min ← p, d min ← d end end D A ← D A − d min provide correct sense s for ... Table 1 shows some information about these 21 nouns. For instance, these nouns have an average of 6.7 senses in BC and 6.8 senses in WSJ. This is slightly higher than the 5.8 senses per verb in (Chen ... number of BC examples to gather for other senses s according to their respective sense priors in WSJ. If there are in- sufficient training examples in BC for some sense s, whatever available examples...

Ngày tải lên: 08/03/2014, 02:21

... Measure Context Target Sense Preprocessing Format Filter Sense Inventory Context Selection Postprocessing Pick Sense Figure 1: A generalized framework for Word Sense Disambiguation. modules to perform any ... method of word sense disambiguation that com- putes the intended sense of a target word, using WordNet-based measures of seman- tic relatedness (Patwardhan et al., 2003). SenseRelate::TargetWord is ... by selecting that sense of the target word which is most related to the context words. Relatedness between word senses is mea- sured using the WordNet::Similarity Perl modules. 1 Introduction Many words...

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... (more details in Section 7) on applying word sense disambiguation (WSD) techniques in SMT for translation selection. However, WSD techniques for SMT do so indirectly, using source-side context ... of the Association for Computational Linguistics, pages 834–843, Uppsala, Sweden, 11-16 July 2010. c 2010 Association for Computational Linguistics Bilingual Sense Similarity for Statistical Machine ... monolin- gual sense similarity have been widely used in many applications, such as synonym recognizing (Landauer and Dumais, 1997), word clustering (Pantel and Lin 2002), word sense disambigua- tion...

Ngày tải lên: 20/02/2014, 04:20