Semantic Document Networks to Support Concept Retrieval-Reference-Cited by-同舟云学术

Semantic Document Networks to Support Concept Retrieval

Published:2014 Issue: Volume: Page:2135-2146
ISSN:
Container-title:Encyclopedia of Business Analytics and Optimization
language:
Short-container-title:

Author:

Boese Simon¹,Reiners Torsten²,Wood Lincoln C.³^ORCID

Affiliation:

1. University of Hamburg, Germany

2. Curtin University, Australia & University of Hamburg, Germany

3. University of Otago, New Zealand

Abstract

There are many unstructured documents created in many disciplines which need to be (pre-) processed in one way or another for further integration and use in IT systems. The predominance of the Internet and large corporate databases implies that there are large volumes of documents that need to be analysed and searched to retrieve information; particularly within the fields of machine translation, text analysis, semantic mining, information extraction and retrieval. We explicate a framework based on concept-based indexing that supports the analysis, storage, and retrieval of documents. Natural-language reduction is used to calculate semantic cores for concept-based indexing of stored concepts found within documents. The processed documents are stored within a semantic network enabling effective analysis of core concepts within documents and rapid retrieval of specific ideas from multiple documents based on provided concepts

Publisher

IGI Global

Reference28 articles.

1. Aust, T., & Sarnow, M. (2009). Entwurf und implementierung einer medien-datenbank-middleware mit integrierten semantischen netzen [English: Design and implementation of a media database middleware using semantic networks] (Diploma Thesis). University of Hamburg, Germany.

2. An Adapted Lesk Algorithm for Word Sense Disambiguation Using WordNet

3. Baziz, M., Boughanem, M., & Traboulsi, S. (2005). A concept-based approach for indexing documents in IR. Actes du XXIIIème Congrès INFORSID (pp. 489-504).

4. Boese, S., Reiners, T., & Wood, L. C. (2012). Design and construction of semantic document networks using concept extraction, School of Information Systems Working Paper Series, Curtin University of Technology, Australia.