Articles

This paper presents the system SSMT measuring the semantic similarity between a paragraph and a sentence submitted to the SemEval 2014 task3: Cross-level Se- mantic Similarity. The special difficulty of this task is the length disparity between the two semantic comparison texts. We adapt several machine translation evalua- tion metrics …...

This paper describes the SNAP system, which participated in Task 4 of SemEval- 2014: Aspect Based Sentiment Analysis. We use an XML-based pipeline that com- bines several independent components to perform each subtask. Key resources used by the system are Bing Liu’s senti- ment lexicon, Stanford CoreNLP, RFTag- ger, several …...

This article presents the participation of the SINAI research group in the task Sen- timent Analysis in Twitter of the SemEval Workshop. Our proposal consists of a voting system of three polarity classifiers which follow a lexicon-based approach. 1...

This paper introduces our contribution to the SemEval-2014 Task 7 on ”Analysis of Clinical Text”. We implemented a sys- tem which combines MetaMap taggings and Illinois NER Tagger. MetaMap is de- veloped to link the text of medical doc- uments to the knowledge embedded in UMLS Metathesaurus. The UMLS con- …...

Long-time average spectrum (LTAS) was used to analyze the cry phonations of 26 infants under four months old; 16 of them are full-term and the other 10 infants are preterm. The results of first spectral peak, mean spectral energy, spectral tilt, high frequency energy were used to compare the cry …...

This paper presents a wordlist-based lexical richness approach to testing distributional hypothesis for genre analysis in translation studies. In recent years, there has been continuing interest in patent translation. However, there are only a few lay their interests on comparison between native and non-native writing. The proposed approach to terms …...

In this paper, we present an unsupervised two-phase approach to extract keywords from Arabic documents that combines statistical analysis and linguistic information. The first phase detects all the N-grams that may be considered keywords. In the second phase, the N-grams are analyzed using a morphological analyzer to replace the words …...

AbstractThis paper deals with information retrieval on semantically enriched web-scale document collections. It particularly focuses on web-crawled content in which mentions of entities appearing in Freebase, DBpedia and other Linked Open Data resources have been identified. A special attention is paid to indexing structures and advanced query mechanisms that have …...

This article answers the question what is and what is not ellipsis and specifies criteria for identification of elliptical sentences. It reports on an analysis of types of ellipsis from the point of view of semantic representation of sentences. It does not deal with conditions and causes of the constitution …...

We proposes a language resource by automatically sketching grammatical relations of words based on dependency parses from untagged texts. The advantage of word sketch based on parsed corpora is, compared to Sketch Engine (Kilgarriff, Rychly, Smrz, & Tugwell, 2004), to provide more details about the different usage of each word …...

Automatic keyphrase extraction methods have generally taken either supervised or unsupervised approaches. Supervised methods extract keyphrases by using a training document set, thus acquiring knowledge from a global collection of texts. Conversely, unsupervised methods extract keyphrases by determining their relevance in a single-document context, without prior learning. We present a …...

In this paper we propose an approach for the automatic enrichment of standardized electronic dictionaries by the semantic classes. This approach consists of three phases. The first phase treat the semantic classification process founded on the studies of Gaston Gross. The second phase profites from the existed subject fields in …...

In Corpus-Based Machine Translation, the search space of the translation candidates for a given input sentence is often defined by a set of (cycle- free) context-free grammar rules. This happens naturally in Syntax-Based Machine Translation and Hierarchi- cal Phrase-Based Machine Translation (where the representation will be the set of the …...

Inspired by previous work, where decipher- ment is used to improve machine translation, we propose a new idea to combine word align- ment and decipherment into a single learning process. We use EM to estimate the model pa- rameters, not only to maximize the probabil- ity of parallel corpus, but …...

This paper presents a novel approach to learning to solve simple arithmetic word problems. Our system, ARIS, analyzes each of the sentences in the problem state- ment to identify the relevant variables and their values. ARIS then maps this infor- mation into an equation that represents the problem, and enables …...

Shell nouns, such as fact and problem, oc- cur frequently in all kinds of texts. These nouns themselves are unspecific, and can only be interpreted together with the shell content. We propose a general approach to automatically identify shell content of shell nouns. Our approach exploits lexico- syntactic knowledge derived …...

Deceptive reviews detection has attract- ed significant attention from both business and research communities. However, due to the difficulty of human labeling need- ed for supervised learning, the problem re- mains to be highly challenging. This pa- per proposed a novel angle to the prob- lem by modeling PU (positive …...

In this paper, we propose a joint segmenta- tion and classification framework for sen- timent analysis. Existing sentiment clas- sification algorithms typically split a sen- tence as a word sequence, which does not effectively handle the inconsistent senti- ment polarity between a phrase and the words it contains, such as …...

We propose a semi-supervised bootstrap- ping algorithm for analyzing China’s for- eign relations from the People’s Daily. Our approach addresses sentiment tar- get clustering, subjective lexicons extrac- tion and sentiment prediction in a unified framework. Different from existing algo- rithms in the literature, time information is considered in our algorithm …...

Term translation is of great importance for statistical machine translation (SMT), es- pecially document-informed SMT. In this paper, we investigate three issues of term translation in the context of document- informed SMT and propose three cor- responding models: (a) a term trans- lation disambiguation model which se- lects desirable translations …...