OGIR: an ontology-based grid information retrieval framework

محفوظ في:
التفاصيل البيبلوغرافية
الحاوية / القاعدة:Online Information Review vol. 36, no. 6 (2012), p. 807
المؤلف الرئيسي: Hung, Chihli
مؤلفون آخرون: Chih-Fong Tsai, Shin-Yuan, Hung, Chang-Jiang, Ku
منشور في:
Emerald Group Publishing Limited
الموضوعات:
الوصول للمادة أونلاين:Citation/Abstract
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100 1 |a Hung, Chihli 
245 1 |a OGIR: an ontology-based grid information retrieval framework 
260 |b Emerald Group Publishing Limited  |c 2012 
513 |a Feature 
520 3 |a Purpose - A grid information retrieval model has benefits for sharing resources and processing mass information, but cannot handle conceptual heterogeneity without integration of semantic information. The purpose of this research is to propose a concept-based retrieval mechanism to catch the user's query intentions in a grid environment. This research re-ranks documents over distributed data sources and evaluates performance based on the user judgment and processing time. Design/methodology/approach - This research uses the ontology lookup service to build the concept set in the ontology and captures the user's query intentions as a means of query expansion for searching. The Globus toolkit is used to implement the grid service. The modification of the collection retrieval inference (CORI) algorithm is used for re-ranking documents over distributed data sources. Findings - The experiments demonstrate that this proposed approach successfully describes the user's query intentions evaluated by user judgment. For processing time, building a grid information retrieval model is a suitable strategy for the ontology-based retrieval model. Originality/value - Most current semantic grid models focus on construction of the semantic grid, and do not consider re-ranking search results from distributed data sources. The significance of evaluation from the user's viewpoint is also ignored. This research proposes a method that captures the user's query intentions and re-ranks documents in a grid based on the CORI algorithm. This proposed ontology-based retrieval mechanism calculates the global relevance score of all documents in a grid and displays those documents with higher relevance to users. 
653 |a Information retrieval 
653 |a Studies 
653 |a Search engines 
653 |a Internet 
653 |a Ontology 
653 |a Research 
653 |a Digital libraries 
653 |a Remote sensing 
653 |a Query expansion 
653 |a Image retrieval 
653 |a Relevance feedback 
653 |a Keywords 
653 |a Retrieval performance measures 
653 |a Semantics 
653 |a Distributed processing 
653 |a Documents 
653 |a Data processing 
653 |a Judgment 
653 |a Ratings & rankings 
653 |a Experiments 
653 |a Data mining 
653 |a Algorithms 
653 |a Models 
653 |a Retrieval 
653 |a Research methodology 
653 |a Information 
653 |a Data sources 
653 |a Inference 
653 |a Electronic Libraries 
653 |a Educational Environment 
700 1 |a Chih-Fong Tsai 
700 1 |a Shin-Yuan, Hung 
700 1 |a Chang-Jiang, Ku 
773 0 |t Online Information Review  |g vol. 36, no. 6 (2012), p. 807 
786 0 |d ProQuest  |t ABI/INFORM Global 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/1193950738/abstract/embedded/ZKJTFFSVAI7CB62C?source=fedsrch 
856 4 0 |3 Full Text  |u https://www.proquest.com/docview/1193950738/fulltext/embedded/ZKJTFFSVAI7CB62C?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/1193950738/fulltextPDF/embedded/ZKJTFFSVAI7CB62C?source=fedsrch