Báo cáo khoa học: "Rule Markov Models for Fast Tree-to-String Translation" pot

... the Association for Computational Linguistics, pages 856–864, Portland, Oregon, June 19-24, 2011. c 2011 Association for Computational Linguistics Rule Markov Models for Fast Tree-to-String Translation Ashish ... another threshold. 3 Tree-to-string decoding with rule Markov models In this paper, we use our rule Markov model frame- work in the context of tree-to-string...

Ngày tải lên: 17/03/2014, 00:20

... context. For example, among the possible senses of the verb “run” are “to move fast by using one's feet” and “to direct or control”. WSD can be useful for many applications, includ- ing information ... 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 r...

Ngày tải lên: 08/03/2014, 02:21

... types of infor- mation provide rich clues for building dialog mod- els (Grosz and Sidner, 1986). Dialog models can be built ofine (for dialog mining and summariza- tion), or online (for dialog ... to improved performance for any method. One utterance of context is best for shift-reduce and start-join; three is best for the connection path method. The shift- reduce method performs...

Ngày tải lên: 22/02/2014, 02:20

... again form a lattice and we can calculate the best path for layer 2. The Markov Model for layer 1 operates on the output of the Markov Model for part-of-speech tagging, the model for layer ... Cascaded Markov Models The basic idea of Cascaded Markov Models is to construct the parse tree layer by layer, first struc- tures of depth one, then structures of depth two,...

Ngày tải lên: 22/02/2014, 03:20

... perform preprocess- ing (refer to Section 3.4 for details) before build- ing topic models for C R (q), where some low- frequency items are removed. Determine the number of topics: Most topic models ... number k. We fix the k value for all dif- ferent query item q, as has been done for the top- ic model approach. For fair comparison, the same postprocessing is made for all th...

Ngày tải lên: 08/03/2014, 00:20

... hypothesis is given by C = project C (bestpath 1 (λ SLU )), where bestpath n (in this case n is 1 for the 1-best hypothesis) performs a Viterbi search on the FST 203 and outputs the n-best hypotheses ... hypotheses. This means that re-ranking the m-best hypotheses in a convenient way could improve the SLU performance. The best choice in this case is a discriminative model, since it allows...

Ngày tải lên: 08/03/2014, 21:20

... 1993), for example, allow to take this fact into account. We can envisage more complex models, in- cluding distortion parameters, multiword no- tions, or information on part-of-speech, infor- ... can simplify the above formula and write: le+l 1 P(a,e,,f,)= ]-I p(ei,f~ilal )i-1 (5) i=1 where a~ -1 is a shorthand for (al, ,ai-1). p(ei, f~,) is a shorthand for p(a~(ei) = f~,...

Ngày tải lên: 17/03/2014, 07:20

... (z|n) =  ac f nac ¯ P (z|nac)  ac f nac . (13) For classification, we use the formula : P (c|na) =  z P (c|az)P (z|n). (14) 3.3 Other Models for Comparison We will also test the 3-PLSI model ... the clusters that are suitable for our task, by incorporating the new variable c for semantic orientation in the EM computation. 5 Conclusion We proposed models for phrases with semant...

Ngày tải lên: 17/03/2014, 22:20

... the Association for Computational Linguistics, pages 311–319, Jeju, Republic of Korea, 8-14 July 2012. c 2012 Association for Computational Linguistics Smaller Alignment Models for Better Translations: Unsupervised ... d, but the differences do not concern us here. All three models, as well as IBM Models 3–5, share the same t. For further details of these models, the reader is...

Ngày tải lên: 30/03/2014, 17:20

... a fundamental problem for distributional models. Typically, distributional models compute a single “type” vector for a target word, which contains co- occurrence counts for all the occurrences ... contextual features for all the senses of the target. For example, among the top 20 features for coach, we get match and team (for the “trainer” sense) as well as driver and car (...

Ngày tải lên: 30/03/2014, 21:20