A Semantic Method to Information Extraction for Decision Support Systems

2006 | Americas Conference on Information Systems | Citations: 0

Authors: Ofoghi, Bahadorreza; Yearwood, John; Ghosh, Ranadhir

Abstract: In this paper, we describe a novel schema for a more semantic text mining proces ... Expand

Abstract: In this paper, we describe a novel schema for a more semantic text mining process which results in more comprehensive decision making activity by decision support systems via providing more effective and accurate textual information. The utility of two semantic lexical resources; FrameNet and WordNet, in extracting required text snippets from unstructured free texts yields a better and more accurate information extraction process to deliver more precise information either to a DSS or to a decision maker. We explain how the usage of these lexical resources could elevate a focused text mining process which could be applied to an information provider system in a decision support paradigm. The preliminary results obtained after a starter experiment show that the hybrid information extraction schema performs well on some semantic failure situations. Collapse

Topics: knowledge representation decision support system decision making Microsoft Windows decision support

Methods: information extraction question answering WordNet experiment FrameNet