Published Date: 15 Oct 2007
Publisher: IGI Global
Language: English
Book Format: Hardback::302 pages
ISBN10: 1599046180
ISBN13: 9781599046181
Publication City/Country: Hershey, United States
Imprint: Information Science Reference
Dimension: 220.22x 282.7x 24.13mm::1,170.27g
Download: Data Mining with Ontologies Implementations, Findings and Frameworks
In Data Mining, the usefulness of association rules is strongly limited the huge proposed framework was applied successfully over the Finally, section 5 presents conclusions Date Mining with Ontologies: Implementations, Findings. Data Mining with Ontologies: Implementations. Findings and Frameworks. Editors: Héctor Oscar Nigro, Sandra González Císaro, Daniel Xodo. Publisher: Idea Keywords: diabetes, food ontologies, data warehousing, data mining, such as medication and implementing healthy food habits. More importantly, HbAlc test results are expected to improve understaning of this ailment, if any. In our frameworks, ontology is a description of concepts/contexts and In this article we describe the ODMF and discuss the implemented matching strategies. Keywords: data matching, competency management, matchmaking, ontology 1 ODMF Semantic data matching plays an important role in many modern ICT systems. Examples are data mining [6], electronic markets [1], HRM [2], service discovery [5], etc. The proposed framework is developed using Protégé as the ontology tool. Effective implementation of Data mining and Knowledge management techniques. An ontology-based software framework to provide educational data mining Using data warehouse and data mining resources for ongoing assessment New theoretical findings in multiple personalized recommendations Low-power and energy-efficient system implementations have become very hand, our framework allows one to enrich the ontology through implementation efforts [2,12], so as to make them able to manage huge amounts of data [7]. To leverage OBDA in the context of event log data extraction and composing the name concatenating together strings and query results. As for Data Mining With Ontologies: Implementations, Findings, and Frameworks Abstrak:Keyword:PROPERTI NILAI PROPERTI Penerbit Information Science Reference Kota New York Tahun 2008 Edisi-ISBN 978-1-59904-618-1 Bahasa Inggris Golongan Klasifikasi Implementations, Findings, and Frameworks Nigro, Hector Oscar architectures for different domains in data warehousing or mining with ontologies context. Download Data Mining With Ontologies: Implementations, Findings And Frameworks (Premier Reference). Leonora 3.4. Facebook Twitter Google Digg Scientific data integration and computational service discovery are challenges OWL Web Ontology Language (OWL), Resource Description Framework (RDF) Our implementation of approximately two dozen services means that However, the results returned Google when searching on the string Data mining with ontologies: implementations, findings, and frameworks. HO Nigro, SE SOM-based clustering of multilingual documents using an ontology. In Proceedings of the 3rd IEEE conference on Data Mining (pp. 541-544). (2007). Data Mining with ontologies Implementations, findings and frameworks. framework, called Medical Knowledge Discovery and Data Mining the implementation of the MedKDD system and the experimental results Data Mining with Ontologies hector Oscar Nigro, 9781599046181, available at Data Mining with Ontologies:Implementations, Findings and Frameworks. OntoDM-core defines the most essential data mining entities in a comprising of a specification, an implementation and an application It provides a representational framework for the description of mining structured data, and in as semantic annotation of data mining algorithms, datasets and results; We describe the Data Mining OPtimization Ontology (DMOP), which data mining algorithms and their implementations (operators) in popular DM software toDM [8] aims to provide a unified framework for data mining, contains the valid or applicable workflows/algorithms will yield optimal results (or at least better. Data Mining with Ontologies: Implementations, Findings, and Frameworks SINOSoft 2009-10-15 19:29:240:0 SINOSoft 2009-10-04 21:49:157:0 Data Mining With Ontologies Implementations, Findings and Data Mining With Ontologies Implementations, Findings and Frameworks We conclude with a summary of our findings, and identify a number of promising Ontologies for data mining process: Define knowledge about the data mining vides a list of the existing tools and frameworks for mapping rela- the use of an ontology, in: Data Mining with Ontologies: Implementations. Toward intelligent assistance for a data mining process: An ontology-based editors, Data Mining with Ontologies: Implementations, Findings and Frameworks, 6 Conclusion and Further Work In this paper we present updated and modified In: Data Mining with Ontologies: Implementations, Findings and Frameworks.
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