Báo cáo khoa học: "Exemplar-Based Models for Word Meaning In Context" pptx

... data. In Proceedings of EMNLP- 09. D. McCarthy, R. Koeling, J. Weeds, J. Carroll. 2004. Finding predominant word senses in untagged text. In Proceedings of the 42nd Meeting of the Associa- tion for ... abstract). In Re- search and Development in Information Retrieval, 279–280. P. Sorg, P. Cimiano. 2008. Cross-lingual information retrieval with explicit semantic analysis. In In...

Ngày tải lên: 23/03/2014, 16:20

... paraphrasing task, we find that a simple exemplar model outperforms more complex state-of-the-art models. 1 Introduction Distributional models are a popular framework for representing word meaning. ... model for modeling word meaning in context, applying the model to the task of decid- ing paraphrase applicability. With a very simple vector representation and just using activa...

Ngày tải lên: 30/03/2014, 21:20

... explicitly smooth the resulting p s (e|f), since many word pairs will be unseen for a given domain s, we are already performing an implicit form of smoothing (when computing the expected counts), since each docu- ment ... is to increase the likelihood of selecting rele- vant phrases for translation. Matsoukas et al. (2009) introduced assigning a pair of binary features to each training...

Ngày tải lên: 19/02/2014, 19:20

... training sentences whose n-gram scores are low, we can dupli- cate such training sentences in word alignment. This method is appealing, but unfortunately if we use mgiza or GIZA++, our training ... is the following: if we witness bad sentence-based scores in word- based MT, we can consider our MT system failing to incorporating a n : m mapping object for those sentences. Later in o...

Ngày tải lên: 08/03/2014, 01:20

... translations in the proper word order by attempting many possible 529 word reorderingsduring the translation process. Trying all possible word reordering is an NP-Complete prob- lem as shown in (Knight, ... counting over align- ment links in the training data. Any aligner such as (Al-Onaizan et al., 1999) or (Vogel et al., 1996) can be used to obtain word alignments. For the r...

Ngày tải lên: 08/03/2014, 02:21

... every sentence in a document and inference was solved us- ing a min-cut algorithm. However, jointly modeling the document label and allowing for non-binary la- bels complicates min-cut style solutions as inference becomes ... algorithm is outlined in Figure 3. The algorithm works by considering a single training in- stance during each iteration. The weight vector w is updated in lin...

Ngày tải lên: 08/03/2014, 02:21

... and adjectives in a text, using the senses pro- vided in WordNet. The senses are ranked us- ing two sources of information: (1) the Inter- net for gathering statistics for word- word co- occurrences ... word PROCEDURE: STEP 1. Form a similarity list ]or each sense of one of the words. Pick one of the words, say W2, and using WordNet, form a similarity list for each sens...

Ngày tải lên: 08/03/2014, 06:20

... important for our purposes to allow mul- tiple links from each word (source and target) to corresponding words in the other language in or- der to obtain phrasal links We say that a word- to -word link ... task is to combine available clues in order to find inter- lingual links. Clues are defined as probabilities of associations. In order to combine all indications which are gi...

Ngày tải lên: 08/03/2014, 21:20

... as information extraction. We extend our su- pertagging models to perform this task in a fash- ion similar to that described in Srinivas (1997b). Selected models have been trained on 200K words. ... are combined using various vot- ing strategies. The same 1000K word test corpus is used in models of classifier combination as is used in pre- vious models. We created three...

Ngày tải lên: 08/03/2014, 21:20

... of words in q is denoted by g(ci), cl begins at the first word in the sentence, and ct(c) ends at the last word in the sentence. The clumps form a proper partition of E. All the words in ... modeling tech- niques for modeling clump generation are n-gram language models (Miller et al., 1995; Levin and Pier- accini, 1995; Epstein, 1996), and headword language models (E...

Ngày tải lên: 08/03/2014, 21:20