Articles

In this paper, we explore the use of keyboard strokes as a means to access the real-time writ- ing process of online authors, analogously to prosody in speech analysis, in the context of deception detection. We show that differences in keystroke patterns like editing maneuvers and duration of pauses can …...

Statistical language modeling (LM) that purports to quantify the acceptability of a given piece of text has long been an in- teresting yet challenging research area. In particular, language modeling for infor- mation retrieval (IR) has enjoyed re- markable empirical success; one emerg- ing stream of the LM approach for …...

Several recent papers on Arabic dialect identi- fication have hinted that using a word unigram model is sufficient and effective for the task. However, most previous work was done on a standard fairly homogeneous dataset of dialec- tal user comments. In this paper, we show that training on the standard …...

When it is not possible to compare the suspi- cious document to the source document(s) plagiarism has been committed from, the evi- dence of plagiarism has to be looked for in- trinsically in the document itself. In this pa- per, we introduce a novel language- independent intrinsic plagiarism detection method …...

Connecting words with senses, namely, sight, hearing, taste, smell and touch, to comprehend the sensorial information in language is a straightforward task for hu- mans by using commonsense knowledge. With this in mind, a lexicon associating words with senses would be crucial for the computational tasks aiming at interpreta- tion …...

This paper proposes to apply the contin- uous vector representations of words for discovering keywords from a financial sen- timent lexicon. In order to capture more keywords, we also incorporate syntactic information into the Continuous Bag-of- Words (CBOW) model. Experimental re- sults on a task of financial risk prediction using …...

We propose to use coreference chains ex- tracted from a large corpus as a resource for semantic tasks. We extract three mil- lion coreference chains and train word embeddings on them. Then, we com- pare these embeddings to word vectors de- rived from raw text data and show that coreference-based …...

Given the large amounts of online textual documents available these days, e.g., news articles, weblogs, and scientific papers, ef- fective methods for extracting keyphrases, which provide a high-level topic descrip- tion of a document, are greatly needed. In this paper, we propose a supervised model for keyphrase extraction from research …...

Automatically identifying related special- ist terms is a difficult and important task required to understand the lexical struc- ture of language. This paper develops a corpus-based method of extracting co- herent clusters of satellite terminology — terms on the edge of the lexicon — us- ing co-occurrence networks of unstruc- …...

It has been shown that news events influ- ence the trends of stock price movements. However, previous work on news-driven stock market prediction rely on shallow features (such as bags-of-words, named entities and noun phrases), which do not capture structured entity-relation informa- tion, and hence cannot represent complete and exact …...

Readability is used to provide users with high- quality service in text recommendation or text visualization. With the increasing use of hand- held devices, reading device is regarded as an important factor for readability. There- fore, this paper investigates the relationship between readability and reading devices such as a smart …...

We propose a new Chinese abbreviation prediction method which can incorporate rich local information while generating the abbreviation globally. Different to previ- ous character tagging methods, we intro- duce the minimum semantic unit, which is more fine-grained than character but more coarse-grained than word, to capture word level information in …...

Language transfer, the characteristic sec- ond language usage patterns caused by na- tive language interference, is investigated by Second Language Acquisition (SLA) researchers seeking to find overused and underused linguistic features. In this pa- per we develop and present a methodology for deriving ranked lists of such features. Using very …...

Languages spoken by immigrants change due to contact with the local languages. Capturing these changes is problematic for current language technologies, which are typically developed for speakers of the standard dialect only. Even when dialec- tal variants are available for such technolo- gies, we still need to predict which di- …...

Predicting vocabulary of second language learners is essential to support their lan- guage learning; however, because of the large size of language vocabularies, we cannot collect information on the entire vocabulary. For practical measurements, we need to sample a small portion of words from the entire vocabulary and pre- dict …...

A common approach in text mining tasks such as text categorization, authorship identification or plagiarism detection is to rely on features like words, part-of-speech tags, stems, or some other high-level lin- guistic features. In this work, an approach that uses character n-grams as features is proposed for the task of …...

The task of unsupervised induction of probabilistic context-free grammars (PCFGs) has attracted a lot of attention in the field of computational linguistics. Although it is a difficult task, work in this area is still very much in demand since it can contribute to the advancement of language parsing and modelling. …...

We generalize contrastive estimation in two ways that permit adding more knowl- edge to unsupervised learning. The first allows the modeler to specify not only the set of corrupted inputs for each observa- tion, but also how bad each one is. The second allows specifying structural prefer- ences on the …...

We introduce a reinforcement learning- based approach to simultaneous ma- chine translation—producing a trans- lation while receiving input words— between languages with drastically dif- ferent word orders: from verb-final lan- guages (e.g., German) to verb-medial languages (English). In traditional ma- chine translation, a translator must “wait” for source material to …...

We propose a novel model for parsing natural language sentences into their for- mal semantic representations. The model is able to perform integrated lexicon ac- quisition and semantic parsing, mapping each atomic element in a complete seman- tic representation to a contiguous word sequence in the input sentence in a …...