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Full-Text Articles in Science and Technology Studies
Ranking Complex Relationships On The Semantic Web, Boanerges Aleman-Meza, Christian Halaschek-Wiener, I. Budak Arpinar, Cartic Ramakrishnan, Amit P. Sheth
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.
From Semantic Search & Integration To Analytics, Amit P. Sheth
From Semantic Search & Integration To Analytics, Amit P. Sheth
Kno.e.sis Publications
Semantics is seen as the key ingredient in the next phase of the Web infrastructure as well as the next generation of enterprise content management. Ontology is the centerpiece of the most prevalent semantic technologies and provides the basis of representing, acquiring, and utilizing knowledge. With the availability of several commercial products and many research tools, specifications and increasing adoption of Semantic Web standards such as RDF for metadata and OWL for ontology representation, ontology-driven techniques and systems have already enabled a new generation of industry strength semantic applications. In particular, Semagix's Freedom has powered applications in leading verticals such …
Discovering Informative Subgraphs In Rdf Graphs, William H. Milnor, Cartic Ramakrishnan, Matthew Perry, Amit P. Sheth, John A. Miller, Krzysztof Kochut
Discovering Informative Subgraphs In Rdf Graphs, William H. Milnor, Cartic Ramakrishnan, Matthew Perry, Amit P. Sheth, John A. Miller, Krzysztof Kochut
Kno.e.sis Publications
Discovering patterns in graphs has long been an area of interest. In most contemporary approaches to such pattern discovery either quantitative anomalies or frequency of substructure is used to measure the interestingness of a pattern. In this paper we address the issue of discovering informative sub-graphs within RDF graphs. We motivate our work with an example related to Semantic Search. A user might pose a question of the form: ' What are the most relevant ways in which entity X is related to entity Y?' the response to which is a subgraph connecting X to Y. Relevance of the …