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Full-Text Articles in Databases and Information Systems
A Model For Anticipatory Event Detection, Qi He, Kuiyu Chang, Ee Peng Lim
A Model For Anticipatory Event Detection, Qi He, Kuiyu Chang, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Event detection is a very important area of research that discovers new events reported in a stream of text documents. Previous research in event detection has largely focused on finding the first story and tracking the events of a specific topic. A topic is simply a set of related events defined by user supplied keywords with no associated semantics and little domain knowledge. We therefore introduce the Anticipatory Event Detection (AED) problem: given some user preferred event transition in a topic, detect the occurence of the transition for the stream of news covering the topic. We confine the events to …
Ontosearch: A Full-Text Search Engine For The Semantic Web, Xing Jiang, Ah-Hwee Tan
Ontosearch: A Full-Text Search Engine For The Semantic Web, Xing Jiang, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
OntoSearch, a full-text search engine that exploits ontological knowledge for document retrieval, is presented in this paper. Different from other ontology based search engines, OntoSearch does not require a user to specify the associated concepts of his/her queries. Domain ontology in OntoSearch is in the form of a semantic network. Given a keyword based query, OntoSearch infers the related concepts through a spreading activation process in the domain ontology. To provide personalized information access, we further develop algorithms to learn and exploit user ontology model based on a customized view of the domain ontology. The proposed system has been applied …
Data Processing In Space, Time, And Semantics Dimensions, Farshad Hakimpour, Boanerges Aleman-Meza, Matthew Perry, Amit P. Sheth
Data Processing In Space, Time, And Semantics Dimensions, Farshad Hakimpour, Boanerges Aleman-Meza, Matthew Perry, Amit P. Sheth
Kno.e.sis Publications
This work presents an experimental system for data processing in space, time and semantics dimensions using current Semantic Web technologies. The paper describes how we obtain geographic and event data from Internet sources and also how we integrate them into an RDF store. We briefly introduce a set of functionalities in space, time and semantics dimensions. These functionalities are implemented based on our existing technology for main-memory based RDF data processing developed in the LSDIS Lab. A number of these functionalities are exposed as REST Web services. We present two sample client side applications that are developed using a combination …
Ontological Implications Of The Levels Of Conceptual Interoperability Model, Andreas Tolk, Charles D. Turnitsa, Saikou Y. Diallo
Ontological Implications Of The Levels Of Conceptual Interoperability Model, Andreas Tolk, Charles D. Turnitsa, Saikou Y. Diallo
Computational Modeling & Simulation Engineering Faculty Publications
The Levels of Conceptual Interoperability Model (LCIM) was developed to cope with the different layers of interoperation of modeling & simulation applications. It introduced technical, syntactic, semantic, pragmatic, dynamic, and conceptual layers of interoperation and showed how they are related to the ideas of integratability, interoperability, and composability. This paper will be presented in the invited session "Ontology Driven Interoperability for Agile Applications using Information Systems: Requirements and Applications for Agent Mediated Decision Support" at WMSCI 2006.
Dynamic Generation Of A Table Of Contents With Consumer-Friendly Labels, Trudi Miller '08, Gondy Leroy, Elizabeth Wood
Dynamic Generation Of A Table Of Contents With Consumer-Friendly Labels, Trudi Miller '08, Gondy Leroy, Elizabeth Wood
CGU Faculty Publications and Research
Consumers increasingly look to the Internet for health information, but available resources are too difficult for the majority to understand. Interactive tables of contents (TOC) can help consumers access health information by providing an easy to understand structure. Using natural language processing and the Unified Medical Language System (UMLS), we have automatically generated TOCs for consumer health information. The TOC are categorized according to consumer-friendly labels for the UMLS semantic types and semantic groups. Categorizing phrases by semantic types is significantly more correct and relevant. Greater correctness and relevance was achieved with documents that are difficult to read than with …