Data Mining with Ontologies: Implementations, Findings, and Frameworks, 1st Edition

  • Published By:
  • ISBN-10: 1599046202
  • ISBN-13: 9781599046204
  • Grade Level Range: College Freshman - College Senior
  • 289 Pages | eBook
  • Original Copyright 2007 | Published/Released December 2007
  • This publication's content originally published in print form: 2007

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About

Overview

One of the most important and challenging problems in data mining is the definition of prior knowledge either from the process or the domain. Prior knowledge is helpful for selecting suitable data and mining techniques, pruning the space of hypothesis, representing the output in a comprehensible way, and improving the overall method.

Data Mining with Ontologies: Implementations, Findings and Frameworks provides a comprehensive set of methodologies and tools for the development of ontological foundations for data mining in diverse domains ranging from biomedicine to marketing. Forming a benchmark reference for future efforts to enhance capabilities in ontology utilization and design, this reference source will be an invaluable addition to libraries worldwide.

Table of Contents

Front Cover.
Title Page.
Copyright Page.
Table of Contents.
Detailed Table of Contents.
Preface.
Acknowledgment.
1: Implementations.
2: TODE: An Ontology-Based Model for the Dynamic Population of Web Directories.
3: Raising, to Enhance Rule Mining in Web Marketing with the Use of an Ontology.
4: Web Usage Mining for Ontology Management.
5: SOM-Based Clustering of Multilingual Documents Using an Ontology.
6: Findings.
7: Ontology-Based Interpretation and Validation of Mined Knowledge: Normative and Cognitive Factors in Data Mining.
8: Data Integration Through Protein Ontology.
9: TtoO: Mining a Thesaurus and Texts to Build and Update a Domain Ontology.
10: Evaluating the Construction of Domain Ontologies for Recommender Systems Based on Texts.
11: Frameworks.
12: Enhancing the Process of Knowledge Discovery in Geographic Databases Using Geo-Ontologies.
13: Ontology-Based Construction of Grid Data Mining Workflows.
14: Ontology-Based Data Warehousing and Mining Approaches in Petroleum Industries.
15: A Framework for Integrating Ontologies and Pattern-Bases.
Compilation of References.
About the Contributors.
Index.