{"title":"面向个性化Web信息采集的本体挖掘","authors":"Xiaohui Tao, Yuefeng Li, N. Zhong, R. Nayak","doi":"10.1109/WI.2007.82","DOIUrl":null,"url":null,"abstract":"It is well accepted that ontology is useful for personalized Web information gathering. However, it is challenging to use semantic relations of \"kind-of\", \"part-of\", and \"related-to\" and synthesize commonsense and expert knowledge in a single computational model. In this paper, a personalized ontology model is proposed attempting to answer this challenge. A two-dimensional (Exhaustivity and Specificity) method is also presented to quantitatively analyze these semantic relations in a single framework. The proposals are successfully evaluated by applying the model to a Web information gathering system. The model is a significant contribution to personalized ontology engineering and concept-based Web information gathering in Web Intelligence.","PeriodicalId":192501,"journal":{"name":"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"140","resultStr":"{\"title\":\"Ontology Mining for Personalized Web Information Gathering\",\"authors\":\"Xiaohui Tao, Yuefeng Li, N. Zhong, R. Nayak\",\"doi\":\"10.1109/WI.2007.82\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"It is well accepted that ontology is useful for personalized Web information gathering. However, it is challenging to use semantic relations of \\\"kind-of\\\", \\\"part-of\\\", and \\\"related-to\\\" and synthesize commonsense and expert knowledge in a single computational model. In this paper, a personalized ontology model is proposed attempting to answer this challenge. A two-dimensional (Exhaustivity and Specificity) method is also presented to quantitatively analyze these semantic relations in a single framework. The proposals are successfully evaluated by applying the model to a Web information gathering system. The model is a significant contribution to personalized ontology engineering and concept-based Web information gathering in Web Intelligence.\",\"PeriodicalId\":192501,\"journal\":{\"name\":\"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-11-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"140\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WI.2007.82\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WI.2007.82","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Ontology Mining for Personalized Web Information Gathering
It is well accepted that ontology is useful for personalized Web information gathering. However, it is challenging to use semantic relations of "kind-of", "part-of", and "related-to" and synthesize commonsense and expert knowledge in a single computational model. In this paper, a personalized ontology model is proposed attempting to answer this challenge. A two-dimensional (Exhaustivity and Specificity) method is also presented to quantitatively analyze these semantic relations in a single framework. The proposals are successfully evaluated by applying the model to a Web information gathering system. The model is a significant contribution to personalized ontology engineering and concept-based Web information gathering in Web Intelligence.