{"title":"一种改进的基于本体的语义web搜索系统","authors":"Yi Liu, Yu Wang, Deli Yang","doi":"10.1109/ICICIP.2014.7010300","DOIUrl":null,"url":null,"abstract":"Semantic Web search based on ontology is a relatively new promising search technology in Web search. The quality of the result ranking is crucial for the success of a search system and depends mainly on the domain ontology in semantic search. However, the domain ontology usually fail to be updated in time and still stay in the initial state that does not contain enough semantics to provide the powerful support for semantic search. As a result, the quality of the result ranking was often poor. This paper proposes an improved ontology-based semantic search system that combines the semantic search with ontology evolution. The aim of this modification is to efficiently enhance the performance of the result ranking by periodically automated ontology evolution, which can enrich the domain ontology by adding more semantics into it. Moreover, a novel algorithm of result ranking is presented in this paper in order to ensure achieving the high-quality ranking results. The performance of the proposed system is evaluated with three experiments, and the experimental results show that the improved semantic search system has a much better performance than the one without ontology evolution.","PeriodicalId":408041,"journal":{"name":"Fifth International Conference on Intelligent Control and Information Processing","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"DLOSSS: An improved ontology-based semantic web search system\",\"authors\":\"Yi Liu, Yu Wang, Deli Yang\",\"doi\":\"10.1109/ICICIP.2014.7010300\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Semantic Web search based on ontology is a relatively new promising search technology in Web search. The quality of the result ranking is crucial for the success of a search system and depends mainly on the domain ontology in semantic search. However, the domain ontology usually fail to be updated in time and still stay in the initial state that does not contain enough semantics to provide the powerful support for semantic search. As a result, the quality of the result ranking was often poor. This paper proposes an improved ontology-based semantic search system that combines the semantic search with ontology evolution. The aim of this modification is to efficiently enhance the performance of the result ranking by periodically automated ontology evolution, which can enrich the domain ontology by adding more semantics into it. Moreover, a novel algorithm of result ranking is presented in this paper in order to ensure achieving the high-quality ranking results. The performance of the proposed system is evaluated with three experiments, and the experimental results show that the improved semantic search system has a much better performance than the one without ontology evolution.\",\"PeriodicalId\":408041,\"journal\":{\"name\":\"Fifth International Conference on Intelligent Control and Information Processing\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Fifth International Conference on Intelligent Control and Information Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICICIP.2014.7010300\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fifth International Conference on Intelligent Control and Information Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICIP.2014.7010300","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
DLOSSS: An improved ontology-based semantic web search system
Semantic Web search based on ontology is a relatively new promising search technology in Web search. The quality of the result ranking is crucial for the success of a search system and depends mainly on the domain ontology in semantic search. However, the domain ontology usually fail to be updated in time and still stay in the initial state that does not contain enough semantics to provide the powerful support for semantic search. As a result, the quality of the result ranking was often poor. This paper proposes an improved ontology-based semantic search system that combines the semantic search with ontology evolution. The aim of this modification is to efficiently enhance the performance of the result ranking by periodically automated ontology evolution, which can enrich the domain ontology by adding more semantics into it. Moreover, a novel algorithm of result ranking is presented in this paper in order to ensure achieving the high-quality ranking results. The performance of the proposed system is evaluated with three experiments, and the experimental results show that the improved semantic search system has a much better performance than the one without ontology evolution.