In this paper we propose a search approach that can process large volumes of textual data efficiently and effectively even in environments where computational resources are limited. The traditional search solution for large collections assumes availability of practically unlimited computational resources. For many applications and organization this assumption is not realistic. Empirical evaluat...

The rapid accumulation of data in social media (in million and billion scales) has imposed great challenges in information extraction, knowledge discovery, and data mining, and texts bearing sentiment and opinions are one of the major categories of user generated data in social media. Sentiment analysis is the main technology to quickly capture what people think from these text data, and is a r...

UNLABELLED Knowledge about biological effects of small molecules helps in the understanding of biological processes and supports the development of new therapeutic agents. DrugBank is a high quality database providing such information about drugs that contains annotation of drug effects and classification of therapeutic effects. However, to broaden the scope of such a database in classifying an...

Identifying Textual Entailment is the task of finding the relationship between the given hypothesis and text fragments. Developing a high-performance text paraphrasing system usually requires rich external knowledge such as syntactic parsing, thesaurus which is limited in Chinese since the Chinese word segmentation problem should be resolve first. By following last year, in this year, we contin...

Prominent biomedical literature search tools like ScienceDirect, PubMed Central or MEDLINE allow for efficient retrieval of resources based on key words. Due to vast amounts of data available in life sciences, key word search is not always sufficient, though. One would often welcome more intelligent search for knowledge, i.e., for concepts and their mutual relations. This is, however, still a m...

In this paper, we introduce our Recognizing Textual Entailment (RTE) system developed on the basis of Lexical Entailment between two text excerpts, namely the hypothesis and the text. To extract atomic parts of hypotheses and texts, we carry out syntactic parsing on the sentences. We then utilize WordNet and FrameNet lexical resources for estimating lexical coverage of the text on the hypothesi...

According to Hyland  (2000),  metadiscourse  is  recognized  as  an  important  means  of  facilitating  communication, supporting a writer's position, and building a relationship with an audience. This study aims to investigate the impact of explicit instruction of metadiscourse markers on EFL learners' listening comprehension. The participants of this study were 50 undergraduate students majo...

This study examined disciplinary rhetoric in research articles, focusing on different traditions in structuring text discourses from a metadiscourse-move analytic approach. The corpus consisted of 72 research article Introductions (RAIs): 36 in applied linguistics and 36 in chemistry. Swales’ CARS model (1990, 2004) and Hyland’s interpersonal model of metadiscourse (2005) were used as analytica...

In the medical field, it is now established that the maintenance of unambiguous thesauri goes through ontologies. Our research task is to help pneumologists code acts and diagnoses with a software that represents medical knowledge through a domain ontology. In this paper, we describe our general methodology aimed at knowledge engineers in order to build various types of medical ontologies based...

It is common knowledge that the creation of language resources for Language Engineering (LE) applications is a time-consuming, and hence expensive, enterprise. From this knowledge stems the demand for the re-usability of resources, which always remains essential. In this paper we will, however, concentrate on another, complementary, aspect, namely that of combining and extending existing resour...