Articles

Previously topic models such as PLSI (Prob- abilistic Latent Semantic Indexing) and LDA (Latent Dirichlet Allocation) were developed for modeling the contents of plain texts. Re- cently, topic models for processing hyper- texts such as web pages were also proposed. The proposed hypertext models are generative models giving rise to …...

Parallel web pages are important source of training data for statistical machine translation. In this paper, we present a new approach to sentence alignment on parallel web pages. Parallel web pages tend to have parallel structures，and the structural correspondence can be indica- tive information for identifying parallel sentences. In our …...

In this paper, we first introduce a new archi- tecture for parsing, bidirectional incremental parsing. We propose a novel algorithm for in- cremental construction, which can be applied to many structure learning problems in NLP. We apply this algorithm to LTAG dependency parsing, and achieve significant improvement on accuracy over …...

Although Machine Translation (MT) is a very active research field which is receiving an in- creasing amount of attention from the research community, the results that current MT sys- tems are capable of producing are still quite far away from perfection. Because of this, and in order to build systems …...

Most state-of-the-art wide-coverage parsers are trained on newspaper text and suffer a loss of accuracy in other domains, making parser adaptation a pressing issue. In this paper we demonstrate that a CCG parser can be adapted to two new domains, biomedical text and questions for a QA system, by us- …...

We investigate the combination of several sources of information for the purpose of sub- jectivity recognition and polarity classification in meetings. We focus on features from two modalities, transcribed words and acoustics, and we compare the performance of three dif- ferent textual representations: words, charac- ters, and phonemes. Our experiments …...

String transformation, which maps a source string s into its desirable form t∗, is related to various applications including stemming, lemmatization, and spelling correction. The essential and important step for string trans- formation is to generate candidates to which the given string s is likely to be transformed. This paper …...

We propose a novel lexicon acquirer that works in concert with the morphological ana- lyzer and has the ability to run in online mode. Every time a sentence is analyzed, it detects unknown morphemes, enumerates candidates and selects the best candidates by comparing multiple examples kept in the storage. When …...

Most attempts to integrate FrameNet in NLP systems have so far failed because of its lim- ited coverage. In this paper, we investigate the applicability of distributional and WordNet- based models on the task of lexical unit induc- tion, i.e. the expansion of FrameNet with new lexical units. Experimental results …...

We investigate the problem of binary text clas- sification in the domain of legal docket entries. This work presents an illustrative instance of a domain-specific problem where the state- of-the-art Machine Learning (ML) classifiers such as SVMs are inadequate. Our investiga- tion into the reasons for the failure of these …...

This paper explores the challenge of scaling up language processing algorithms to increas- ingly large datasets. While cluster comput- ing has been available in commercial environ- ments for several years, academic researchers have fallen behind in their ability to work on large datasets. I discuss two barriers contribut- ing to …...

Lexical gaps between queries and questions (documents) have been a major issue in ques- tion retrieval on large online question and answer (Q&A) collections. Previous stud- ies address the issue by implicitly expanding queries with the help of translation models pre-constructed using statistical techniques. However, since it is possible for …...

This paper introduces a new kernel which computes similarity between two natural lan- guage sentences as the number of paths shared by their dependency trees. The paper gives a very efficient algorithm to compute it. This kernel is also an improvement over the word subsequence kernel because it only counts …...

Foreign name translations typically include multiple spelling variants. These variants cause data sparseness problems, increase Out-of-Vocabulary (OOV) rate, and present challenges for machine translation, information extraction and other NLP tasks. This paper aims to identify name spelling variants in the target language using the source name as an anchor. Based …...

There is growing interest in applying Bayesian techniques to NLP problems. There are a number of different estimators for Bayesian models, and it is useful to know what kinds of tasks each does well on. This paper compares a variety of different Bayesian estimators for Hidden Markov Model POS taggers …...

How can the development of ideas in a sci- entific field be studied over time? We ap- ply unsupervised topic modeling to the ACL Anthology to analyze historical trends in the field of Computational Linguistics from 1978 to 2006. We induce topic clusters using Latent Dirichlet Allocation, and examine the …...

This paper describes a lexical trigger model for statistical machine translation. We present various methods using triplets incorporating long-distance dependencies that can go be- yond the local context of phrases or n-gram based language models. We evaluate the pre- sented methods on two translation tasks in a reranking framework and …...

In this paper we present a textual dialogue system that uses word associations retrieved from the Web to create propositions. We also show experiment results for the role of modal- ity generation. The proposed system automat- ically extracts sets of words related to a con- versation topic set freely by …...

This paper introduces a new method for iden- tifying named-entity (NE) transliterations in bilingual corpora. Recent works have shown the advantage of discriminative approaches to transliteration: given two strings (ws, wt) in the source and target language, a classifier is trained to determine if wt is the translitera- tion of …...

We describe the first tractable Gibbs sam- pling procedure for estimating phrase pair frequencies under a probabilistic model of phrase alignment. We propose and evalu- ate two nonparametric priors that successfully avoid the degenerate behavior noted in previ- ous work, where overly large phrases mem- orize the training data. Phrase …...