{"title":"基于上下文的基于关联规则挖掘的文本文档共享系统","authors":"Kundan A. Dhande, J. Umale, P. Kulkarni","doi":"10.1109/INDICON.2014.7030458","DOIUrl":null,"url":null,"abstract":"In today's document sharing environment, when documents are shared over a group of people, document context of document and context of user is not considered. Therefore sometimes it may happen that the document may get delivered to unintended user over the network. This leads to unnecessary transfer of document. To reduce this document transfer overhead, we are proposing a system that will consider document context as well as user context. By using these both of the contexts, document will get transferred to only intend user. This will also reduce time overhead to transfer a document to a group of peoples, because users belong to different context than document context will be eliminated. To identify document context and user context, we proposed two models Constant Weight Distribution Model and Common Words Probability Model. We also proposed a context dictionary to store different contexts and associated terms with them.","PeriodicalId":409794,"journal":{"name":"2014 Annual IEEE India Conference (INDICON)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Context based text document sharing system using association rule mining\",\"authors\":\"Kundan A. Dhande, J. Umale, P. Kulkarni\",\"doi\":\"10.1109/INDICON.2014.7030458\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In today's document sharing environment, when documents are shared over a group of people, document context of document and context of user is not considered. Therefore sometimes it may happen that the document may get delivered to unintended user over the network. This leads to unnecessary transfer of document. To reduce this document transfer overhead, we are proposing a system that will consider document context as well as user context. By using these both of the contexts, document will get transferred to only intend user. This will also reduce time overhead to transfer a document to a group of peoples, because users belong to different context than document context will be eliminated. To identify document context and user context, we proposed two models Constant Weight Distribution Model and Common Words Probability Model. We also proposed a context dictionary to store different contexts and associated terms with them.\",\"PeriodicalId\":409794,\"journal\":{\"name\":\"2014 Annual IEEE India Conference (INDICON)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 Annual IEEE India Conference (INDICON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INDICON.2014.7030458\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 Annual IEEE India Conference (INDICON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INDICON.2014.7030458","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Context based text document sharing system using association rule mining
In today's document sharing environment, when documents are shared over a group of people, document context of document and context of user is not considered. Therefore sometimes it may happen that the document may get delivered to unintended user over the network. This leads to unnecessary transfer of document. To reduce this document transfer overhead, we are proposing a system that will consider document context as well as user context. By using these both of the contexts, document will get transferred to only intend user. This will also reduce time overhead to transfer a document to a group of peoples, because users belong to different context than document context will be eliminated. To identify document context and user context, we proposed two models Constant Weight Distribution Model and Common Words Probability Model. We also proposed a context dictionary to store different contexts and associated terms with them.