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Physical Sciences and Mathematics Commons

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Communication

Wright State University

Series

2005

Semantic Association

Articles 1 - 2 of 2

Full-Text Articles in Physical Sciences and Mathematics

An Ontological Approach To The Document Access Problem Of Insider Threat, Boanerges Aleman-Meza, Phillip Burns, Matthew Eavenson, Devanand Palanswami, Amit P. Sheth May 2005

An Ontological Approach To The Document Access Problem Of Insider Threat, Boanerges Aleman-Meza, Phillip Burns, Matthew Eavenson, Devanand Palanswami, Amit P. Sheth

Kno.e.sis Publications

Verification of legitimate access of documents, which is one aspect of the umbrella of problems in the Insider Threat category, is a challenging problem. This paper describes the research and prototyping of a system that takes an ontological approach, and is primarily targeted for use by theintelligence community. Our approach utilizes the notion of semantic associations and their discovery among a collection of heterogeneous documents. We highlight our contributions in (graphically) capturing the scope of the investigation assignment of an intelligence analyst by referring to classes and relationships of an ontology; in computing a measure of the relevance …


Ranking Complex Relationships On The Semantic Web, Boanerges Aleman-Meza, Christian Halaschek-Wiener, I. Budak Arpinar, Cartic Ramakrishnan, Amit P. Sheth Jan 2005

Ranking Complex Relationships On The Semantic Web, Boanerges Aleman-Meza, Christian Halaschek-Wiener, I. Budak Arpinar, Cartic Ramakrishnan, Amit P. Sheth

Kno.e.sis Publications

Industry and academia are both focusing their attention on information retrieval over semantic metadata extracted from the Web, and it is increasingly possible to analyze such metadata to discover interesting relationships. However, just as document ranking is a critical component in today's search engines, the ranking of complex relationships would be an important component in tomorrow's semantic Web engines. This article presents a flexible ranking approach to identify interesting and relevant relationships in the semantic Web. The authors demonstrate the scheme's effectiveness through an empirical evaluation over a real-world data set.