Articles

Reordering model is important for the sta- tistical machine translation (SMT). Current phrase-based SMT technologies are good at capturing local reordering but not global reordering. This paper introduces syntactic knowledge to improve global reordering capability of SMT system. Syntactic know- ledge such as boundary words, POS infor- mation and dependencies …...

We propose a domain specific model for statistical machine translation. It is well- known that domain specific language mod- els perform well in automatic speech recog- nition. We show that domain specific lan- guage and translation models also benefit statistical machine translation. However, there are two problems with using domain …...

We address the problem of training the free parameters of a statistical machine transla- tion system. We show significant improve- ments over a state-of-the-art minimum er- ror rate training baseline on a large Chinese- English translation task. We present novel training criteria based on maximum likeli- hood estimation and expected …...

We consider the impact Active Learning (AL) has on effective and efficient text cor- pus annotation, and report on reduction rates for annotation efforts ranging up until 72%. We also address the issue whether a corpus annotated by means of AL – using a particu- lar classifier and a particular …...

We present results that show that incorporat- ing lexical and structural semantic informa- tion is effective for word sense disambigua- tion. We evaluated the method by using pre- cise information from a large treebank and an ontology automatically created from dic- tionary sentences. Exploiting rich semantic and structural information improves …...

A Bloom filter (BF) is a randomised data structure for set membership queries. Its space requirements fall significantly below lossless information-theoretic lower bounds but it produces false positives with some quantifiable probability. Here we present a general framework for deriving smoothed language model probabilities from BFs. We investigate how a …...

Textual records of business-oriented conver- sations between customers and agents need to be analyzed properly to acquire useful business insights that improve productivity. For such an analysis, it is critical to iden- tify appropriate textual segments and ex- pressions to focus on, especially when the textual data consists of complete …...

Morphological analysis and disambiguation are crucial stages in a variety of natural language processing applications, especially when languages with complex morphology are concerned. We present a system which disambiguates the output of a morphologi- cal analyzer for Hebrew. It consists of sev- eral simple classifiers and a module which combines …...

We present a new approach to automatic summarization based on neural nets, called NetSum. We extract a set of features from each sentence that helps identify its impor- tance in the document. We apply novel features based on news search query logs and Wikipedia entities. Using the RankNet learning algorithm, …...

In this paper, we proposed a novel prob- abilistic generative model to deal with ex- plicit multiple-topic documents: Parametric Dirichlet Mixture Model(PDMM). PDMM is an expansion of an existing probabilis- tic generative model: Parametric Mixture Model(PMM) by hierarchical Bayes model. PMM models multiple-topic documents by mixing model parameters of each …...

Most current word prediction systems make use of n-gram language models (LM) to es- timate the probability of the following word in a phrase. In the past years there have been many attempts to enrich such lan- guage models with further syntactic or se- mantic information. We want to explore …...

We present V-measure, an external entropy- based cluster evaluation measure. V- measure provides an elegant solution to many problems that affect previously de- fined cluster evaluation measures includ- ing 1) dependence on clustering algorithm or data set, 2) the “problem of matching”, where the clustering of only a portion of …...

In this paper, we consider the computational modelling of human plausibility judgements for verb-relation-argument triples, a task equivalent to the computation of selectional preferences. Such models have applications both in psycholinguistics and in computa- tional linguistics. By extending a recent model, we obtain a completely corpus-driven model for this task …...

We demonstrate an approach for inducing a tagger for historical languages based on ex- isting resources for their modern varieties. Tags from Present Day English source text are projected to Middle English text using alignments on parallel Biblical text. We explore the use of multiple alignment ap- proaches and a …...

In this paper we explore the use of se- lectional preferences for detecting non- compositional verb-object combinations. To characterise the arguments in a given gram- matical relationship we experiment with three models of selectional preference. Two use WordNet and one uses the entries from a distributional thesaurus as classes for …...

Most of the text summarization research car- ried out to date has been concerned with the summarization of short documents (e.g., news stories, technical reports), and very lit- tle work if any has been done on the sum- marization of very long documents. In this paper, we try to address …...

We investigate methods to improve the re- call in coreference resolution by also trying to resolve those definite descriptions where no earlier mention of the referent shares the same lexical head (coreferent bridging). The problem, which is notably harder than iden- tifying coreference relations among men- tions which have the …...

Parallel corpus is an indispensable resource for translation model training in statistical machine translation (SMT). Instead of col- lecting more and more parallel training corpora, this paper aims to improve SMT performance by exploiting full potential of the existing parallel corpora. Two kinds of methods are proposed: offline data optimi- …...

Product reviews posted at online shopping sites vary greatly in quality. This paper ad- dresses the problem of detecting low- quality product reviews. Three types of bi- ases in the existing evaluation standard of product reviews are discovered. To assess the quality of product reviews, a set of spe- cifications …...

In this paper, we address a unique problem in Chinese language processing and report on our study on extending a Chinese the- saurus with region-specific words, mostly from the financial domain, from various Chinese speech communities. With the larger goal of automatically constructing a Pan-Chinese lexical resource, this work aims …...