Ontology based user query interpretation for semantic multimedia contents retrieval

• Published in: Multimedia tools and applications Vol. 73; no. 2; pp. 901 - 915
• Main Authors: Lee, Moo-Hun, Rho, Seungmin, Choi, Eui-In
• Format: Journal Article
• Language: English
• Published: Boston Springer US 01.11.2014; Springer Nature B.V
• Subjects: Accuracy; Analysis; Computer Communication Networks; Computer Science; Constraining; Construction; Data Structures and Information Theory; Information retrieval; Keywords; Knowledge; Language; Multimedia; Multimedia communications; Multimedia Information Systems; Ontology; Queries; Query expansion; Query processing; Retrieval; Searches; Searching; Semantic analysis; Semantics; Special Purpose and Application-Based Systems; Studies; Knowledge base; Semantic search; Query interpretation; Ontology
• ISSN: 1380-7501; 1573-7721
• DOI: 10.1007/s11042-013-1383-2

Users who are familiar with the existing keyword-based search have problems of not being able to configure the formal query because they don’t have generic knowledge on knowledge base when using the semantic-based retrieval system. User wants the search results which are more accurate and match the user’s search intents with the existing keyword-based search and the same search keyword without the need to recognize what technology the currently used retrieval system is based on to provide the search results. In order to do the semantic analysis of the ambiguous search keyword entered by users who are familiar with the existing keyword-based search, ontological knowledge base constructed based on refined meta-data is necessary, and the keyword semantic analysis technique which reflects user’s search intents from the well-established knowledge base and can generate accurate search results is necessary. In this paper, therefore, by limiting the knowledge base construction to multimedia contents meta-data, the applicable prototype has been implemented and its performance in the same environment as Smart TV has been evaluated. Semantic analysis of user’s search keyword is done, evaluated and recommended through the proposed ontological knowledge base framework so that accurate search results that match user’s search intents can be provided.