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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)
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)
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)
This document describes an on-going 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)
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)
This paper presents a new parsing method using statistical information extracted from corpus, especially for Korean. The structural ambiguities are occurred in deciding the dependency relation between words in Korean. While guring out the correct dependency, the lexical associations play an important role in resolving the ambiguities. Our parser uses(More)
When aligning texts in very di erent languages such as Korean and English, structural features beyond word or phrase give useful information. In this paper, we present a method for selecting structural features of two languages, from which we construct a model that assigns the conditional probabilities to corresponding tag sequences in bilingual(More)