direct word sense matching

... target word, providing a decision criterion for sense matching. In other words, we expect that under a matching sense the target word would oc- cur in prototypical contexts of the source word. To ... sense matches the source word. On the other hand, a direct approach would address the binary sense matching task directly, without selecting explicitly a concrete sense for the target word. This section describes ... 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...

Ngày tải lên: 20/02/2014, 12:20

... classification- based approach to Word Sense Disambigua- tion. Instead of using a predefined monolin- gual sense- inventory such as WordNet, we use a language-independent framework where the word senses are derived ... 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 ... testing phase. This system also differs 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...

Ngày tải lên: 20/02/2014, 05:20

... two words. An ambiguous word has the same number of EPs as of senses. Each EP's sense maps to a sense of ambiguous word. The semantic equivalence demands further equivalence at each sense ... monosemous word is usually synonymous to some polysemous words. For example the words "信守, 严守, 恪守 遵照 遵从 遵循 , , , , 遵守 " has similar meaning as one of the senses of the ambiguous word ... morpheme words for every sense of the word in construction of the EP, rich semantic information can be acquired in the training step and is an advantage for sense disambiguation. 2) Senseval-3...

Ngày tải lên: 20/02/2014, 12:20

... describes SENSELEARNER – a minimally supervised word sense disam- biguation system that attempts to disam- biguate all content words in a text using WordNet senses. We evaluate the accu- racy of SENSELEARNER ... 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 data sets ... a memory-based word- expert approach to unrestricted word sense dis- ambiguation. In Proceedings of the ACL Workshop on Word Sense Disambiguatuion: Recent Successes and Future Directions”, Philadelphia,...

Ngày tải lên: 20/02/2014, 15:20

... 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 ... text analysis. In Proceedings of Table 1: Two of the Senseval-2 sense classes for the target word “art”, from WordNet 1.7 (Fellbaum 1998). Class Sense 1 the creation of beautiful or significant things 2 ... with sense class 1 : training example with sense class 2 : test example with unknown sense class : test example with predicted sense first principal “ quasi-axis” class 2 (correct sense...

Ngày tải lên: 20/02/2014, 16:20

... topic of this paper is word sense induction, that is the automatic discovery of the possible senses of a word. A related problem is word sense disambiguation: Here the senses are assumed to ... the overall be- havior of a word in a corpus. If a word is se- mantically ambiguous, this means that these vectors are mixtures of all its senses. Inducing a word s senses therefore involves ... Problem of Automatic Word Sense Induction Reinhard Rapp University of Mainz, FASK D-76711 Germersheim, Germany rapp@mail.fask.uni-mainz.de Abstract Recent studies in word sense induction...

Ngày tải lên: 20/02/2014, 16:20

... of the SENSEVAL-3. Barcelona. Niu, Zheng-Yu, Dong-Hong Ji, and Chew-Lim Tan. 2007. I2r: Three systems for word sense discrimination, chinese word sense disambiguation, and english word sense dis- ambiguation. ... sam- pling a sense from the sense distribution, then choosing a word from the sense- context distribu- tion. P(s i = j) denotes the probability that the jth sense was sampled for the ith word token ... plausible senses for drug on the WSJ corpus (top half of Table 1). Sense 1 corresponds to the “enforcement” sense of drug, Sense 2 refers to “medication”, Sense 3 to the “drug industry” and Sense...

Ngày tải lên: 22/02/2014, 02:20

... 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 each word, ... @comp.nus.edu.sg Abstract Instances of a word drawn from different domains may have different sense priors (the proportions of the different senses of a word) . This in turn affects the accuracy of word sense disambiguation ... 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 corpus: sense 1, 2, 3,...

Ngày tải lên: 08/03/2014, 02:21

... Re- latedness to 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 ... of WordNet), we still can’t com- pletely rely on WordNet, which focuses on the paradigmatic relations of words, to fully cover the complexity of contextual happenings of words. Since the word ... Then for each context word we retrieve its corresponding words in each word list and calculate the similarity be- tween the target and these words including the context words. As a result we...

Ngày tải lên: 08/03/2014, 02:21

... Introduction Many words have multiple meanings, depending on the context in which they are used. Word sense dis- ambiguation (WSD) is the task of determining the correct meaning or sense of a word in context. ... n- gram matching, where n is up to 4. First, we performed word alignment on the FBIS parallel corpus using GIZA++ (Och and Ney, 2000) in both directions. The word alignments of both directions ... Chinese- English word- based statistical MT system using the ISI ReWrite decoder (Germann, 2003). Though they acknowledged that directly using English transla- tions as word senses would be ideal,...

Ngày tải lên: 08/03/2014, 02:21

... words to the right and left of the verb, identified using POS tags, represented by has_narrow(snt, word_ position, word) : has_narrow(snt 1 , 1st _word_ left, mind). has_narrow(snt 1 , 1st _word_ right, ... the positions of the words, represented by has_narrow_trns(snt, word_ position, portuguese _word) : has_narrow_trns(snt 1 , 1st _word_ right, como). has_narrow_trns(snt 1 , 2nd _word_ right, um). … ... simple, containing only the sentence identifier and the sense of the verb in that sentence, i.e. sense( snt, sense) : sense( snt 1 ,voltar). sense( snt 2 ,ir). … Based on the examples, background...

Ngày tải lên: 08/03/2014, 02:21

... Introduction In natural language, a word often assumes different meanings, and the task of determining the correct meaning, or sense, of a word in different contexts is known as word sense disambiguation (WSD). ... the dif- ference in sense priors (i.e., the proportions of the different senses of a word) between BC and WSJ. When the authors assumed they knew the sense pri- ors of each word in BC and WSJ, ... of the different senses of each word were the same between BC and WSJ. We can simi- larly choose BC examples such that the sense priors in the BC training data adhere to the sense priors in the...

Ngày tải lên: 08/03/2014, 02:21

... 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 ... Relatedness Measure Context Target Sense Preprocessing Format Filter Sense Inventory Context Selection Postprocessing Pick Sense Figure 1: A generalized framework for Word Sense Disambiguation. modules...

Ngày tải lên: 08/03/2014, 04:22

... significance. L1 words that translate into the same L2 word are grouped into clusters; SALAAM identifies the appropriate senses for the words in those clusters based on the words senses’ proximity in WordNet. ... GenCor (Mihalcea&Moldovan, 1999). GenCor creates seeds from monosemous words in WordNet, Sem- cor data, sense tagged examples from the glosses of polysemous words in WordNet, and other hand tagged data if available. ... that directly and indirectly affect the perfor- mance of quantified as a performance ratio, PR. Sense Distribution Correlation (SDC) and Sense Context Confusability (SCC) have the highest direct...

Ngày tải lên: 08/03/2014, 04:22

... sample task of SENSEVAL-2. We rely on two sources to decide on the sense classes of w: (i) The sense definitions in WordNet 1.7, which lists seven senses for the noun channel. Two senses are ... Hopkins SENSEVAL2 system descrip- tions. In Proceedings of the Second International Workshop on Evaluating Word Sense Disambigua- tion Systems (SENSEVAL-2), pages 163-166. WordNet 1.7 sense ... defining sense distinction in terms of different tar- get translations, the outcome of word sense disam- biguation of a source language word is the selection of a target word, which directly...

Ngày tải lên: 08/03/2014, 04:22

Ngày tải lên: 08/03/2014, 04:22

Ngày tải lên: 08/03/2014, 06:20

Ngày tải lên: 08/03/2014, 07:20

Ngày tải lên: 08/03/2014, 21:20

Ngày tải lên: 08/03/2014, 21:20