In this paper, we propose a lexical senses representation system called E-HowNet, in which the lexical senses are defined by basic concepts. As a result, the meanings of expressio...
Honorifics in Japanese plays an incredibly important role in all walks of social life. The demand to transform regular expressions in Japanese into honorifics automatically has in...
This demonstration presents a highperformance syntactic and semantic dependency parser. The system consists of a pipeline of modules that carry out the tokenization, lemmatization...
The presentation will mainly cover (1) What is HowNet? HowNet is an on-line common-sense knowledgebase unveiling inter-conceptual relationships and interattribute relationships of...
Due to the lack of annotated data sets, there are few studies on machine learning based approaches to extract named entities (NEs) in clinical text. The 2009 i2b2 NLP challenge is...
This article delves into the scoring function of the statistical paraphrase generation model. It presents an algorithm for exact computation and two applicative experiments. The f...
Position information has been proved to be very effective in document summarization, especially in generic summarization. Existing approaches mostly consider the information of se...
In this paper, we present an unsupervised hybrid model which combines statistical, lexical, linguistic, contextual, and temporal features in a generic EMbased framework to harvest...
We present an adaptation technique for statistical machine translation, which applies the well-known Bayesian learning paradigm for adapting the model parameters. Since state-of-t...
In the field of multi-document summarization, the Pyramid method has become an important approach for evaluating machine-generated summaries. The method is based on the manual ann...
Leonhard Hennig, Ernesto William De Luca, Sahin Al...