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Full-Text Articles in Science and Technology Studies
Semantic Analytics Visualization, Leonidas Deligiannidis, Amit P. Sheth, Boanerges Aleman-Meza
Semantic Analytics Visualization, Leonidas Deligiannidis, Amit P. Sheth, Boanerges Aleman-Meza
Kno.e.sis Publications
In this paper we present a new tool for semantic analytics through 3D visualization called “Semantic Analytics Visualization” (SAV). It has the capability for visualizing ontologies and meta-data including annotated web-documents, images, and digital media such as audio and video clips in a synthetic three-dimensional semi-immersive environment. More importantly, SAV supports visual semantic analytics, whereby an analyst can interactively investigate complex relationships between heterogeneous information. The tool is built using Virtual Reality technology which makes SAV a highly interactive system. The backend of SAV consists of a Semantic Analytics system that supports query processing and semantic association discovery. Using a …
Peer-To-Peer Discovery Of Semantic Associations, Matthew Perry, Maciej Janik, Cartic Ramakrishnan, Conrad Ibanez, I. Budak Arpinar, Amit P. Sheth
Peer-To-Peer Discovery Of Semantic Associations, Matthew Perry, Maciej Janik, Cartic Ramakrishnan, Conrad Ibanez, I. Budak Arpinar, Amit P. Sheth
Kno.e.sis Publications
The Semantic Web vision promises an extension of the current Web in which all data is annotated with machine understandable metadata. The relationship-centric nature of this data has led to the definition of Semantic Associations, which are complex relationships between resources. Semantic Associations attempt to answer queries of the form “how are resource A and resource B related?” Knowing how two entities are related is a crucial question in knowledge discovery applications. Much the same way humans collaborate and interact to form new knowledge, discovery of Semantic Associations across repositories on a peer-to-peer network can allow peers to share their …
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 …
Discovering And Ranking Semantic Associations Over A Large Rdf Metabase, Christian Halaschek-Wiener, Boanerges Aleman-Meza, I. Budak Arpinar, Amit P. Sheth
Discovering And Ranking Semantic Associations Over A Large Rdf Metabase, Christian Halaschek-Wiener, Boanerges Aleman-Meza, I. Budak Arpinar, Amit P. Sheth
Kno.e.sis Publications
Information retrieval over semantic metadata has recently received a great amount of interest in both industry and academia. In particular, discovering complex and meaningful relationships among this data is becoming an active research topic. Just as ranking of documents is a critical component of today's search engines, the ranking of relationships will be essential in tomorrow's semantic analytics engines. Building upon our recent work on specifying these semantic relationships, which we refer to as Semantic Associations, we demonstrate a system where these associations are discovered among a large semantic metabase represented in RDF. Additionally we employ ranking techniques to provide …
Ρ-Queries: Enabling Querying For Semantic Associations On The Semantic Web, Kemafor Anyanwu, Amit P. Sheth
Ρ-Queries: Enabling Querying For Semantic Associations On The Semantic Web, Kemafor Anyanwu, Amit P. Sheth
Kno.e.sis Publications
This paper presents the notion of Semantic Associations as complex relationships between resource entities. These relationships capture both a connectivity of entities as well as similarity of entities based on a specific notion of similarity called ρ-isomorphism. It formalizes these notions for the RDF data model, by introducing a notion of a Property Sequence as a type. In the context of a graph model such as that for RDF, Semantic Associations amount to specific certain graph signatures. Specifically, they refer to sequences (i.e. directed paths) here called Property Sequences, between entities, networks of Property Sequences (i.e. undirected paths), or subgraphs …