{"title":"测量文件的通用性","authors":"H. Shin, E. Hovy, D. McLeod, Larry Pryor","doi":"10.1109/ICDEW.2006.77","DOIUrl":null,"url":null,"abstract":"Most traditional Information Retrieval (IR) systems, including web search engines, operationalize \"relevant\" as the word frequency in a document of a set of keywords. Because of this limitation, traditional IR systems frequently retrieve irrelevant documents in response to a user’s request. In this paper, we propose a new criterion, \"generality,\" that provides an additional basis on which to rank retrieved documents. The generality is a level of abstraction to retrieve results based on desired generality appropriate for a user’s knowledge and interests. We compared our generality quantification algorithm with human judges’ weighting of values to show that the developed algorithm is significantly correlated.","PeriodicalId":331953,"journal":{"name":"22nd International Conference on Data Engineering Workshops (ICDEW'06)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2006-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Measuring Generality of Documents\",\"authors\":\"H. Shin, E. Hovy, D. McLeod, Larry Pryor\",\"doi\":\"10.1109/ICDEW.2006.77\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Most traditional Information Retrieval (IR) systems, including web search engines, operationalize \\\"relevant\\\" as the word frequency in a document of a set of keywords. Because of this limitation, traditional IR systems frequently retrieve irrelevant documents in response to a user’s request. In this paper, we propose a new criterion, \\\"generality,\\\" that provides an additional basis on which to rank retrieved documents. The generality is a level of abstraction to retrieve results based on desired generality appropriate for a user’s knowledge and interests. We compared our generality quantification algorithm with human judges’ weighting of values to show that the developed algorithm is significantly correlated.\",\"PeriodicalId\":331953,\"journal\":{\"name\":\"22nd International Conference on Data Engineering Workshops (ICDEW'06)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-04-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"22nd International Conference on Data Engineering Workshops (ICDEW'06)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDEW.2006.77\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"22nd International Conference on Data Engineering Workshops (ICDEW'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDEW.2006.77","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Most traditional Information Retrieval (IR) systems, including web search engines, operationalize "relevant" as the word frequency in a document of a set of keywords. Because of this limitation, traditional IR systems frequently retrieve irrelevant documents in response to a user’s request. In this paper, we propose a new criterion, "generality," that provides an additional basis on which to rank retrieved documents. The generality is a level of abstraction to retrieve results based on desired generality appropriate for a user’s knowledge and interests. We compared our generality quantification algorithm with human judges’ weighting of values to show that the developed algorithm is significantly correlated.