{"title":"面向内容和结构的XML检索相关反馈方法","authors":"L. Hlaoua, M. Boughanem, K. Pinel-Sauvagnat","doi":"10.5555/1931390.1931460","DOIUrl":null,"url":null,"abstract":"As opposed to traditional Information Retrieval (IR) which views whole documents as atomic units of retrieval, XML IR processes XML elements as possible units of retrieval. Many open issues appear when considering Relevance Feedback (RF) in XML documents. They are mainly related to the form of XML documents that mix content and structure and to the new granularity of information processed by the Information Retrieval Systems (IRS). Most of the RF approaches proposed in XML retrieval are simple adaptations of traditional RF to the new granularity of information. They enrich queries by adding terms extracted from relevant elements instead of terms extracted from whole documents. In this paper, we propose to extend the initial query by adding both content and structural constraints. Experiments are carried out with the INEX evaluation campaign and results show the interest of our method.","PeriodicalId":120472,"journal":{"name":"RIAO Conference","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Using a Content-and-Structure Oriented Method for Relevance Feedback in XML Retrieval\",\"authors\":\"L. Hlaoua, M. Boughanem, K. Pinel-Sauvagnat\",\"doi\":\"10.5555/1931390.1931460\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As opposed to traditional Information Retrieval (IR) which views whole documents as atomic units of retrieval, XML IR processes XML elements as possible units of retrieval. Many open issues appear when considering Relevance Feedback (RF) in XML documents. They are mainly related to the form of XML documents that mix content and structure and to the new granularity of information processed by the Information Retrieval Systems (IRS). Most of the RF approaches proposed in XML retrieval are simple adaptations of traditional RF to the new granularity of information. They enrich queries by adding terms extracted from relevant elements instead of terms extracted from whole documents. In this paper, we propose to extend the initial query by adding both content and structural constraints. Experiments are carried out with the INEX evaluation campaign and results show the interest of our method.\",\"PeriodicalId\":120472,\"journal\":{\"name\":\"RIAO Conference\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-05-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"RIAO Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5555/1931390.1931460\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"RIAO Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5555/1931390.1931460","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Using a Content-and-Structure Oriented Method for Relevance Feedback in XML Retrieval
As opposed to traditional Information Retrieval (IR) which views whole documents as atomic units of retrieval, XML IR processes XML elements as possible units of retrieval. Many open issues appear when considering Relevance Feedback (RF) in XML documents. They are mainly related to the form of XML documents that mix content and structure and to the new granularity of information processed by the Information Retrieval Systems (IRS). Most of the RF approaches proposed in XML retrieval are simple adaptations of traditional RF to the new granularity of information. They enrich queries by adding terms extracted from relevant elements instead of terms extracted from whole documents. In this paper, we propose to extend the initial query by adding both content and structural constraints. Experiments are carried out with the INEX evaluation campaign and results show the interest of our method.