Articles

Non-standard language as it appears in user-generated content has recently at- tracted much attention. This paper pro- poses that non-standardness comes in two basic varieties, technical and linguistic, and develops a machine-learning method to discriminate between standard and non- standard texts in these two dimensions. We describe the manual annotation …...

Existing semantic parsing research has steadily improved accuracy on a few do- mains and their corresponding meaning representations. In this paper, we present a novel supervised semantic parsing algo- rithm, which includes the lexicon exten- sion and the syntactic supervision. This algorithm adopts a large-scale knowl- edge base from the …...

In this paper, we explore the IBM Model with a ℓ0-norm prior to the se- mantic parsing which parses a sentence to its corresponding meaning representa- tion, and compare two supervised proba- bilistic Combinatory Categorial Grammar (PCCG) online learning approaches that are Unification-Based Learning (UBL) method and Factored Unification-Based Learning …...

We present extensive evaluations compar- ing the performance of taxonomy-based and corpus-based approaches on SimLex- 999. The results confirm our hypothesis that taxonomy-based approaches are more suitable to identify similarity. We intro- duce two new measures of evaluation that show that all measures perform well on a coarse-grained evaluation and …...

In medical imaging domain, digitized da- ta is rapidly expanding Therefore it is of major interest for radiologists to be able to do an efficient and accurate extraction of imaging and clinical data (radiology reports) which are essential for a rigorous diagnosis and for a better management of patients. In …...

Sentiment analysis from a text requires amongst others having a polarity lexical resource. We designed LikeIt, a GWAP (Game With A Purpose) that allows to at- tribute a positive, negative or neutral value to a term, and thus obtain a resulting polar- ity for most of the terms of the …...

This paper revisits the work of (Kuncham et al., 2015) which developed a statistical sandhi splitter (SSS) for agglutinative languages that was tested for Telugu and Malayalam lan- guages. Handling compound words is a major challenge for Natural Language Processing (NLP) applications for agglutinative lan- guages. Hence, in this paper …...

This paper reports on the task of Native Language Identification (NLI). We devel- oped a machine learning system to identify the native language of authors of English texts written by non-native English speak- ers. Our system is based on the language modeling approach and employs cross- entropy scores as features …...

We developed a system to extract Japanese anime-related words, i.e., Japanese NEs (named entities) in the anime-related do- main. Since the NEs in the area, such as the titles of anime or the names of charac- ters, were domain-specific, we started by building a tagged corpus and then used it …...

In this article we present the result of the recent research in the recognition of Polish temporal expressions. The tem- poral information extracted from the text plays major role in many information ex- traction systems, like question answering, event recognition or discourse analysis. We prepared a broad description of Pol- …...

There tends to be a substantial propor- tion of reviews that include explicit textual comparisons between the reviewed item and another product. To the extent that such comparisons can be captured reliably by automatic means, they can provide an extremely helpful input to support a pro- cess of choice. As …...

We present a system for fine-grained senti- ment analysis in Bulgarian movie reviews. As this is pioneering work for this com- bination of language and sentiment gran- ularity, we create suitable, freely available resources: a dataset of movie reviews with fine-grained scores, and a sentiment po- larity lexicon. We further …...

Many events referred to on Twitter are of a periodic nature, characterized by roughly constant time intervals in between occur- rences. Examples are annual music fes- tivals, weekly television programs, and the full moon cycle. We propose a sys- tem that can automatically identify peri- odic events from Twitter in …...

In this paper we present an approach for anal- ysis of sentiments and emotions in image tag- ging using SentiWordNet as an external lin- guistic resource of emotional words. Our aim is to design and implement algorithms that as- sess the emotions and polarity given a set of image tags. …...

We present work on sentiment analysis in Twitter for Macedonian. As this is pio- neering work for this combination of lan- guage and genre, we created suitable re- sources for training and evaluating a sys- tem for sentiment analysis of Macedonian tweets. In particular, we developed a cor- pus of …...

The paper reports work on collecting and annotating code-mixed English-Hindi so- cial media text (Twitter and Facebook messages), and experiments on automatic tagging of these corpora, using both a coarse-grained and a fine-grained part-of- speech tag set. We compare the perfor- mance of a combination of language spe- cific taggers …...

This article describes a method which al- lows acquiring artifact nouns in French automatically by extracting predicate- argument structures. Two strategies are presented: the supervised strategy and the semi-supervised strategy. In the super- vised method, the semantic classes of ar- tifact nouns are recognized by identifying the predicate-argument structures with …...

This paper describes the implementation, im- provement and evaluation of the machine translation (MT) system proposed by Jackov (2014) when used as a feature-rich part-of- speech (POS) tagger for Bulgarian. The sys- tem does not rely on POS tagging for mor- phological disambiguation. Instead, all ambi- guities are considered in …...

In this paper, we show an approach to ex- tracting different types of constraint rules from a dependency treebank. Also, we show an approach to integrating these con- straint rules into a dependency data-driven parser, where these constraint rules in- form parsing decisions in specific situa- tions where a set …...

Vector-space models derived from corpora are an effective way to learn a representa- tion of word meaning directly from data, and these models have many uses in prac- tical applications. A number of unsu- pervised approaches have been proposed to automatically learn representations of word senses directly from corpora, but …...