{"title":"从社交网络中识别地方实体的短名称","authors":"Faizan Wajid, Hong Wei, H. Samet","doi":"10.1145/3148150.3148157","DOIUrl":null,"url":null,"abstract":"Organizations can be identified by a myriad of terms apart from their official names. While abbreviations remain a common \"short-name\" to reference organizations, the prevalence of other short-names has risen in conjunction with social networks. When a user enters a short-name as a locational search query, it remains a challenge to infer the relationship between the short-name and the organization it ostensibly represents. For a number of organizations around the Washington D.C., Maryland, and Virginia area, we first generate a list of possible short-names for each of them. We then search through their tweets to build a corpus of short-names associated with each organization. By measuring our list against the corpus, we can identify potential short-names, and return the location of the organization.","PeriodicalId":176579,"journal":{"name":"Proceedings of the 1st ACM SIGSPATIAL Workshop on Recommendations for Location-based Services and Social Networks","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Identifying Short-Names for Place Entities from Social Networks\",\"authors\":\"Faizan Wajid, Hong Wei, H. Samet\",\"doi\":\"10.1145/3148150.3148157\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Organizations can be identified by a myriad of terms apart from their official names. While abbreviations remain a common \\\"short-name\\\" to reference organizations, the prevalence of other short-names has risen in conjunction with social networks. When a user enters a short-name as a locational search query, it remains a challenge to infer the relationship between the short-name and the organization it ostensibly represents. For a number of organizations around the Washington D.C., Maryland, and Virginia area, we first generate a list of possible short-names for each of them. We then search through their tweets to build a corpus of short-names associated with each organization. By measuring our list against the corpus, we can identify potential short-names, and return the location of the organization.\",\"PeriodicalId\":176579,\"journal\":{\"name\":\"Proceedings of the 1st ACM SIGSPATIAL Workshop on Recommendations for Location-based Services and Social Networks\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-11-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 1st ACM SIGSPATIAL Workshop on Recommendations for Location-based Services and Social Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3148150.3148157\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 1st ACM SIGSPATIAL Workshop on Recommendations for Location-based Services and Social Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3148150.3148157","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Identifying Short-Names for Place Entities from Social Networks
Organizations can be identified by a myriad of terms apart from their official names. While abbreviations remain a common "short-name" to reference organizations, the prevalence of other short-names has risen in conjunction with social networks. When a user enters a short-name as a locational search query, it remains a challenge to infer the relationship between the short-name and the organization it ostensibly represents. For a number of organizations around the Washington D.C., Maryland, and Virginia area, we first generate a list of possible short-names for each of them. We then search through their tweets to build a corpus of short-names associated with each organization. By measuring our list against the corpus, we can identify potential short-names, and return the location of the organization.