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MOTIVATION Automatic knowledge discovery and efficient information access such as named entity recognition and relation extraction between entities have recently become critical issues in the biomedical literature. However, the inherent difficulty of the relation extraction task, mainly caused by the diversity of natural language, is further compounded in(More)
Biomedical named entity recognition (NER) is a difficult problem in biomedical information processing due to the widespread ambiguity of terms out of context and extensive lexical variations. This paper presents a two-phase biomedical NER consisting of term boundary detection and semantic labeling. By dividing the problem, we can adopt an effective model(More)
The construction of interaction networks between proteins is central to understanding the underlying biological processes. However, since many useful relations are excluded in databases and remain hidden in raw text, a study on automatic interaction extraction from text is important in bioinformatics field. Here, we suggest two kinds of kernel methods for(More)
This document describes an ongoing project of developing a grammar of Korean, the Korean XTAG grammar, written in the TAG formalism and implemented for use with the XTAG system enriched with a Korean morphological analyzer. The Korean XTAG grammar described in this report is based on the TAG formalism (Joshi et al. (1975)), which has been extended to(More)
Compound noun analysis is one of the crucial problems in Korean language processing because a series of nouns in Korean may appear without white space in real texts, which makes it difficult to identify the morphological constituents. This paper presents an effective method of Korean compound noun segmen-tation based on lexical data extracted from corpus.(More)
The curtailment of disambiguation decisions is crucial for eecient and precise analysis of sentences in the view of parsing as making a sequence of disambiguation. In this paper we propose three types of chunking in Korean for purpose of the reduction of search space. We present the parsing method based on chunking and the association among chunks and words(More)
Translation selection is a process to select, from a set of target language words corresponding to a source language word, the most appropriate one that conveys the correct sense of a source word and makes the target language sentence more natural. In this paper, we propose a hybrid method for translation selection that exploits a bilingual dictionary and a(More)
When aligning texts in very different languages such as Korean and English, structural features beyond word or phrase give useful intbrmation. In this paper , we present a method for selecting struetm'al features of two languages, from which we construct a model that assigns the conditional probabilities to corresponding tag sequences in bilingual(More)