{"title":"开发活动数据的通用词汇","authors":"S. Israel","doi":"10.1109/AIPR.2012.6528217","DOIUrl":null,"url":null,"abstract":"Pattern recognition is easy. Doing it well is hard. Communicating across disciplines is even more difficult. This paper reports on efforts to reduce the communication issues across researchers. Currently, the social network data is being exploited by a number of academics to understand interactions among individuals. Assessing interactions among individuals is an application of pattern recognition, a science that for over 40 years has received a huge financial investment from the research and development community. This paper provides a lexicon that has been developed from the pattern recognition community and applies it to the current tasks of social network interactions. Two case studies will be used: reconnaissance imagery from the Cold War and text from social networks that includes both posting messages and instant messaging.","PeriodicalId":406942,"journal":{"name":"2012 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Toward a common lexicon for exploiting activity data\",\"authors\":\"S. Israel\",\"doi\":\"10.1109/AIPR.2012.6528217\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Pattern recognition is easy. Doing it well is hard. Communicating across disciplines is even more difficult. This paper reports on efforts to reduce the communication issues across researchers. Currently, the social network data is being exploited by a number of academics to understand interactions among individuals. Assessing interactions among individuals is an application of pattern recognition, a science that for over 40 years has received a huge financial investment from the research and development community. This paper provides a lexicon that has been developed from the pattern recognition community and applies it to the current tasks of social network interactions. Two case studies will be used: reconnaissance imagery from the Cold War and text from social networks that includes both posting messages and instant messaging.\",\"PeriodicalId\":406942,\"journal\":{\"name\":\"2012 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)\",\"volume\":\"58 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-10-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AIPR.2012.6528217\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AIPR.2012.6528217","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Toward a common lexicon for exploiting activity data
Pattern recognition is easy. Doing it well is hard. Communicating across disciplines is even more difficult. This paper reports on efforts to reduce the communication issues across researchers. Currently, the social network data is being exploited by a number of academics to understand interactions among individuals. Assessing interactions among individuals is an application of pattern recognition, a science that for over 40 years has received a huge financial investment from the research and development community. This paper provides a lexicon that has been developed from the pattern recognition community and applies it to the current tasks of social network interactions. Two case studies will be used: reconnaissance imagery from the Cold War and text from social networks that includes both posting messages and instant messaging.