Yahoo! as an ontology: using Yahoo! categories to describe documents
Proceedings of the eighth international conference on Information and knowledge management
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Using ODP metadata to personalize search
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Communications of the ACM - Supporting exploratory search
Web search personalization with ontological user profiles
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Toward a New Generation of Semantic Web Applications
IEEE Intelligent Systems
Optimal meta search results clustering
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Invited paper: Sig.ma: Live views on the Web of Data
Web Semantics: Science, Services and Agents on the World Wide Web
Proceedings of the 22nd ACM conference on Hypertext and hypermedia
Searching web data: An entity retrieval and high-performance indexing model
Web Semantics: Science, Services and Agents on the World Wide Web
Facet graphs: complex semantic querying made easy
ESWC'10 Proceedings of the 7th international conference on The Semantic Web: research and Applications - Volume Part I
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As the size of Linked Open Data (LOD) increases, the search and access to the relevant LOD resources becomes more challenging. To overcome search difficulties, we propose a novel concept-based search mechanism for the Web of Data (WoD) based on UMBEL concept hierarchy and fuzzy-based retrieval model. The proposed search mechanism groups LOD resources with the same concepts to form categories, which is called conceptlenses, for more efficient access to the WoD. To achieve concept-based search, we use UMBEL concept hierarchy for representing context of LOD resources. A semantic indexing model is applied for efficient representation of UMBEL concept descriptions and a novel fuzzy-based categorization algorithm is introduced for classification of LOD resources to UMBEL concepts. The proposed fuzzy-based model was evaluated on a particular benchmark (~10,000 mappings). The evaluation results show that we can achieve highly acceptable categorization accuracy and perform better than the vector space model.