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s In TREC-10, we participated in the web track (only ad-hoc task) and the QA track (only main task). In the QA track, our QA system (SiteQ) has general architecture with three processing steps: question processing, passage selection and answer processing. The key technique is LSP's (Lexico-Semantic Patterns) that are composed of linguistic entries and(More)
Schema and data conflicts between component databases are a crucial problem in building multidatabase systems. This article presents a comprehensive framework for classifying these conflicts. he proliferation of file systems, navigational database systems (hierarchical and network). and relational database systems during the past three decades has created(More)
A wide range of supervised learning algorithms has been applied to Text Categorization. However, the supervised learning approaches have some problems. One of them is that they require a large, often prohibitive, number of labeled training documents for accurate learning. Generally, acquiring class labels for training data is costly, while gathering a large(More)
In this paper, we present a new method of representing the Surface syntactic structure of a sentence. Trees have usually been used in linguistics and natural language processing to represent syntactic structures of a sentence. A tree structure shows only one possible syntactic parse of a sentence, but in order to choose a correct parse, we need to examine(More)
We propose a statistical dialogue analysis model to determine discourse structures as well as speech acts using maximum entropy model. The model can automatically acquire probabilistic discourse knowledge from a discourse tagged corpus to resolve ambiguities. We propose the idea of tagging discourse segment boundaries to represent the structural information(More)
In this paper, we propose a right-to-left dependency grammar parsing method for languages in which a governor appears after its modiier like Korean and Japanese. Unlike conventional left-to-right parsers, this parsing method can take advantage of the governor post-positioning property of such languages to reduce the size of search space by using the idea of(More)
Named Entity recognition, as a task of providing important semantic information, is a critical first step in Information Extraction and Question-Answering system. This paper proposes a hybrid method of the named entity recognition which combines maximum entropy model, neural network, and pattern-selection rules. The maximum entropy model is used for the(More)