Paraphrase generation is useful for various NLP tasks. But pivoting techniques for paraphrasing have limited applicability due to their reliance on parallel texts, although they benefit from linguistic knowledge implicit in the sentence alignment. Distributional paraphrasing has wider applicability, but doesn’t benefit from any linguistic knowledge. We combine a distributional semantic distance...

Lexicographical and terminological work is increasingly dependent on the analysis of texts, particularly texts organised in a corpus and being made available through computer systems. We argue that the developments in corpus linguistics, artificial intelligence, connection sciences, and lexicography and terminology, can be conjoined together to analyse the various facets of a text. In particula...

This paper describes an Example-Based Machine Translation prototype and presents an evaluation of the impact of using a domainspecific vocabulary on its performance. This prototype is based on a hybrid approach which needs only monolingual texts in the target language and consists to combine translation candidates returned by a cross-language search engine with translation hypotheses provided b...

This paper presents a novel hybrid system, which combines rule-based machine translation (RBMT) with phrase-based statistical machine translation (SMT), to translate Chinese patent texts into English. The hybrid architecture is basically guided by the RBMT engine which processes source language parsing and transformation, generating proper syntactic trees for the target language. In the generat...

 The present study is a theoretical attempt to illustrate how Fillmore's Scenes and Frames Semantics (SFS) could be employed as a framework to portray the process of understanding and translating hybrid texts. It first reviews the origin of SFS; then it maps SFS onto Nida’s linguistic model of translation process and the Interpretive Theory of Translation; it examines in the next section, withi...

this paper presents, a hybrid method, low-resolution and high-resolution, for persian page segmentation. in the low-resolution page segmentation, a pyramidal image structure is constructed for multiscale analysis and segments document image to a set of regions. by high-resolution page segmentation, by connected components analysis, each region is segmented to homogeneous regions and identifying...

Retrieval practice improves meaningful learning, and the most frequent way of implementing retrieval practice in classrooms is to have students answer questions. In four experiments (N=372) we investigated the effects of different question formats on learning. Students read educational texts and practised retrieval by answering short-answer, multiple-choice, or hybrid questions. In hybrid condi...

In this paper we present an overview of the PhD thesis, which aims to show the feasibility of a legal knowledge modeling based on the definitions included into legal texts using Semantic Web techniques in order to check compliance of tender documents to EU Directives. We show a hybrid approach, i.e. a theory and a system that combine the use of Akoma-Ntoso standard to describe legal texts, OWL ...

Medical Entity Recognition is a crucial step towards efficient medical texts analysis. In this paper we present and compare three methods based on domain-knowledge and machine-learning techniques. We study two research directions through these approaches: (i) a first direction where noun phrases are extracted in a first step with a chunker before the final classification step and (ii) a second ...

We present a method of chunking in Korean texts using conditional random fields (CRFs), a recently introduced probabilistic model for labeling and segmenting sequence of data. In agglutinative languages such as Korean and Japanese, a rule-based chunking method is predominantly used for its simplicity and efficiency. A hybrid of a rule-based and machine learning method was also proposed to handl...