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We describe a framework incorporating several information extraction methods for the NTCIR-9 One Click Access Task. Our framework first classifies a given query into pre-defined query classes, then extracts information from several Web resources by using a method suitable for the query type, and finally aggregates pieces of information into a short text.
This paper describes a wiki-based collective intelligence approach to provide a system environment that enables users to formulate a body of knowledge (BOK) for a new discipline, such as social informatics. When the targeted discipline is mature, for example, computer science, its BOK can be straightforwardly formulated by a task force using a top-down… (More)
The greater part of our methods seems effective for CELEBRITY queries. Our methods are ineffective for GEO queries which are for retrieving object sets. Score'(u) = c t, e Score(u), where t is the query type and e is the extraction method
This presentation shows a collective intelligence approach for formulating a body of knowledge (BOK) of social informatics (SI), a relatively new interdisciplinary field of study, by implementing a BOK constructor based on Semantic MediaWiki.
This paper surveys cost-sensitive fuzzy rule-based systems for pattern classification. Weighted training patterns are used to construct cost-sensitive fuzzy rule-based systems. A fuzzy classification system is constructed from a given set of training patterns. It is assumed that a weight is assigned to each training pattern a priori. The weight of training… (More)
This paper proposes a query classification system for a one-click search system that uses feature vectors based on snippet similarity. The proposed system targets the NTCIR-10 1CLICK-2 query classification subtask and classifies queries in Japanese and English into eight predefined classes by using support vector machines (SVMs). In the NTCIR-9 and NTCIR-10… (More)