Articles

Nowadays in tunisia, the arabic Tunisian Dialect (TD) has become progressively used in interviews, news and debate programs instead of Modern Standard Arabic (MSA). Thus, this gave birth to a new kind of language. Indeed, the majority of speech is no longer made in MSA but alternates between MSA and …...

We present a Variational-Bayes model for learning rules for the Hierarchical phrase- based model directly from the phrasal alignments. Our model is an alternative to heuristic rule extraction in hierarchical phrase-based translation (Chiang, 2007), which uniformly distributes the probabil- ity mass to the extracted rules locally. In contrast, in our …...

We introduce a novel modality scheme where triggers are words and phrases that convey modality meanings and subcategorize for clauses and verbal phrases. This semantic- syntactic working definition of modality ena- bles us to design practical and replicable anno- tation guidelines and procedures that alleviate some shortcomings of current purely …...

Domain-specific bilingual lexicons ex- tracted from domain-specific comparable corpora provide for one term a list of ranked translation candidates. This study proposes to re-rank these translation can- didates. We suggest that a term and its translation appear in comparable sen- tences that can be extracted from domain- specific comparable corpora. …...

This paper presents a methodology to ex- ploit the potential of Arabic Wikipedia to as- sist in the automatic development of a large Fine-grained Named Entity (NE) corpus and gazetteer. The corner stone of this approach is efficient classification of Wikipedia articles to target NE classes. The resources developed were …...

Uncertainty is an important linguistic phenomenon that is relevant in many areas of language processing. While earlier research mostly concentrated on the semantic aspects of uncertainty, here we focus on discourse- and pragmatics- related aspects of uncertainty. We present a classification of such linguistic phenom- ena and introduce a corpus …...

This paper addresses the problem of automatic evaluation of text simplifica- tion systems for Spanish. We test whether already-existing readability for- mulae would be suitable for this task. We adapt three existing readability indices (two measuring lexical complexity and one measuring syntactic complexity) to be computed automatically, which are then …...

In this paper, we present an automatic sys- tem to rank participants of an interaction in terms of their relative power. We find several linguistic and structural features to be effective in predicting these rank- ings. We conduct our study in the domain of political debates, specifically the 2012 Republican …...

While various claims have been made about text in social media text being noisy, there has never been a systematic study to investigate just how linguistically noisy or otherwise it is over a range of social media sources. We explore this question empirically over popular social media text types, in …...

Using large corpora of chronologically or- dered language, it is possible to explore diachronic phenomena, identifying previ- ously unknown correlations between lan- guage usage and time periods, or epochs. We focused on a statistical approach to epoch delimitation and introduced the task of epoch characterization. We investi- gated the significant …...

We propose using profile compatibility to differentiate genuine and fake product re- views. For each product, a collective profile is derived from a separate col- lection of reviews. Such a profile con- tains a number of aspects of the prod- uct, together with their descriptions. For a given unseen review …...

Normalizing named entity abbreviations to their standard forms is an important preprocessing task for question answering, entity retrieval, event detection, microblog processing, and many other applications. Along with the quick expansion of mi- croblogs, this task has received more and more attentions in recent years. In this pa- per, we …...

The identification of light verb construc- tions (LVC) is an important task for sev- eral applications. Previous studies focused on some limited set of light verb construc- tions. Here, we address the full coverage of LVCs. We investigate the performance of different candidate extraction methods on two English full-coverage LVC …...

 Traditional Event Extraction mainly focuses on event type identification and event partici- pants extraction based on pre-specified event type annotations. However, different domains have different event type paradigms. When transferring to a new domain, we have to build a new event type paradigm. It is a costly task to …...

Event detection on Twitter is an important and challenging research topic. On the one hand, Twitter provides first-hand informa- tion and fast broadcasting. On the oth- er, challenges include short and noisy con- tent, big volume data and fast-changing topics. Dominant approaches for Twit- ter event detection model events by …...

Automatically mining named entities (NE) is an important but challenging task, pattern-based and bootstrapping strategy is the most widely accepted solution. In this paper, we propose a novel method for NE mining using web document titles. In addition to the traditional text patterns, we propose to use url-text hybrid patterns …...

Discovering parallel data in comparable corpora is a promising approach for over- coming the lack of parallel texts in statis- tical machine translation and other NLP applications. In this paper we propose an alternative to comparable corpora of texts as resources for extracting parallel data: a multimodal comparable corpus of …...

In this paper, we consider the tuning of sta- tistical machine translation (SMT) mod- els employing a large number of features. We argue that existing tuning methods for these models suffer serious sparsity prob- lems, in which features appearing in the tuning data may not appear in the test- ing …...

We present a novel system combination of machine translation and text summariza- tion which provides high quality summary translations superior to the baseline trans- lation of the entire document. We first use supervised learning and build a classifier that predicts if the translation of a sentence has high or low …...

We present a high-precision, language- independent transliteration framework applicable to bilingual lexicon extrac- tion. Our approach is to employ a bilingual topic model to enhance the output of a state-of-the-art grapheme- based transliteration baseline. We demonstrate that this method is able to extract a high-quality bilingual lexi- con from a …...