Articles

This paper proposes a novel approach to re- solve the English article error correction prob- lem, which accounts for a large proportion in grammatical errors. Most previous machine learning based researches empirically collect- ed features which may bring about noises and increase the computational complexity. Meanwhile, the predicted result is …...

We propose a new rule-based pre-ordering method for Japanese-to-English statistical machine translation that employs heuristic rules in two-stages. This two-stage frame- work contributes to experimental results that our method outperforms conventional rule-based methods in BLEU and RIBES. 1...

A variety of methods have been proposed for attribute-value extraction from semi- structured text with consistent templates (strict semi-text). However, when the tem- plates in semi-structured text are inconsis- tent (weak semi-text), these methods will work poorly. To overcome the template- inconsistent problem, in this paper, we proposed a novel …...

A novel method is proposed for measuring contextual similarity by “weighted overlap- ping ratio (WOR)” to construct a bilingual dic- tionary of a new language pair from two bilin- gual dictionaries sharing one language. The WOR alleviates the effect of a noisy seed dic- tionary resulting from merger of two …...

Integrating language resources is a critical part in building natural language process- ing applications. Processing pipeline and service composition are two approaches for sharing and combining language re- sources. However, each approach has its drawback. While the former lacks con- sideration about property rights of lan- guage resources, the later …...

In statistical machine translation, data sparsity is a challenging problem espe- cially for languages with rich morphology and inconsistent orthography, such as Per- sian. We show that orthographic prepro- cessing and morphological segmentation of Persian verbs in particular improves the translation quality of Persian-English by 1.9 BLEU points on a …...

Beside the word order problem, word choice is another major obstacle for ma- chine translation. Though phrase-based statistical machine translation (SMT) has an advantage of word choice based on lo- cal context, exploiting larger context is an interesting research topic. Recently, there have been a number of studies on inte- …...

We focus on improving the translation of the English pronoun it and English reflex- ive pronouns in an English-Czech syntax- based machine translation framework. Our evaluation both from intrinsic and ex- trinsic perspective shows that adding spe- cialized syntactic and coreference-related features leads to an improvement in trans- lation quality. …...

Simultaneous translation is the challeng- ing task of listening to source language speech, and at the same time, produc- ing target language speech. Human inter- preters achieve this task routinely and ef- fortlessly, using different strategies in or- der to minimize the latency in produc- ing target language. Toward modeling …...

In this paper, we propose a new semi- supervised approach for Arabic word sense disambiguation. Using the corpus and Arabic Wordnet1, we define a method to cluster the sentences containing ambiguous words. For each sense, we generate a cluster that we use to construct a semantic tree. Furthermore, we construct …...

Bilingual lexicons of proper names play a vital role in machine translation and cross-language information retrieval. Word alignment ap- proaches are generally used to construct bilin- gual lexicons automatically from parallel cor- pora. Aligning proper names is a task particu- larly difficult when the source and target lan- guages of …...

Finding contradiction text is a fundamen- tal problem in natural language under- standing. Previous work on finding contra- diction in text incorporate information de- rived from predicate-argument structures as features in supervised machine learning frameworks. In contrast to previous work, we combine shallow semantic representa- tions derived from semantic role …...

We propose an unsupervised approach to learning non-concatenative morphology, which we apply to induce a lexicon of Arabic roots and pattern templates. The approach is based on the idea that roots and patterns may be revealed through mutually recursive scoring based on hypothesized pattern and root frequencies. After a further …...

Morphology is the study of internal struc- ture of words and is an essential early step in many NLP applications such as pars- ing and machine translation. Researchers working in Hindi NLP have either used the widely popular paradigm based analyzer (PBA) or extensions of it. In this work, we …...

Rare term vector replacement (RTVR) is a novel technique for dimensionality reduc- tion. In this paper, we introduce an up- dating algorithm for RTVR. It is capable of updating both the projection matrix for the reduction and the reduced corpus ma- trix directly, without having to recompute the expensive projection …...

Deciding whether a word serves a dis- course function in context is a prerequi- site for discourse processing, and the per- formance of this subtask bounds perfor- mance on subsequent tasks. Pitler and Nenkova (2009) report 96.29% accuracy (F1 94.19%) relying on features extracted from gold-standard parse trees. This fig- …...

In this paper, we address the problem of the morphological analysis of an Arabic dialect. We propose a method to adapt an Arabic mor- phological analyzer for the Tunisian dialect (TD). In order to do that, we create a lexicon for the TD. The creation of the lexicon is done …...

We consider the problem of learning how to rank answers across domains in com- munity question answering using stylistic features. Our main contribution is an im- portance sampling technique for selecting training data per answer thread. Our ap- proach is evaluated across 30 community sites and shown to be significantly …...

We propose a structure cognizant frame- work for pseudo relevance feedback (PRF). This has an application, for ex- ample, in selecting expansion terms for general search from subsets such as Wikipedia, wherein documents typically have a minimally fixed set of fields, viz., Title, Body, Infobox and Categories. In existing approaches …...

In this paper we present a hybrid approach to resolve Entity-pronoun references in Hindi. While most of the existing ap- proaches, syntactic as well as data-driven, use phrase-structure syntax for anaphora resolution, we explore use of dependency structures as a source of syntactic informa- tion. In our approach, dependency struc- …...