C. Popovici, M. Andorno, P. Laface, L. Fissore, M. Nigra, C. Vair
{"title":"目录协助:学习企业列表的用户公式","authors":"C. Popovici, M. Andorno, P. Laface, L. Fissore, M. Nigra, C. Vair","doi":"10.1109/ASRU.2001.1034634","DOIUrl":null,"url":null,"abstract":"One of the main problems in automatic directory assistance (DA) for business listings is that customers formulate their requests for the same listing with a great variability. We show that an automatic approach allows the detection, from field data, of user formulations that were not foreseen by the designers, and that they can be added, as variants, to the denominations already included in the system to reduce its failures.","PeriodicalId":118671,"journal":{"name":"IEEE Workshop on Automatic Speech Recognition and Understanding, 2001. ASRU '01.","volume":"58 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Directory assistance: learning user formulations for business listings\",\"authors\":\"C. Popovici, M. Andorno, P. Laface, L. Fissore, M. Nigra, C. Vair\",\"doi\":\"10.1109/ASRU.2001.1034634\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"One of the main problems in automatic directory assistance (DA) for business listings is that customers formulate their requests for the same listing with a great variability. We show that an automatic approach allows the detection, from field data, of user formulations that were not foreseen by the designers, and that they can be added, as variants, to the denominations already included in the system to reduce its failures.\",\"PeriodicalId\":118671,\"journal\":{\"name\":\"IEEE Workshop on Automatic Speech Recognition and Understanding, 2001. ASRU '01.\",\"volume\":\"58 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-12-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Workshop on Automatic Speech Recognition and Understanding, 2001. ASRU '01.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ASRU.2001.1034634\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Workshop on Automatic Speech Recognition and Understanding, 2001. ASRU '01.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASRU.2001.1034634","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Directory assistance: learning user formulations for business listings
One of the main problems in automatic directory assistance (DA) for business listings is that customers formulate their requests for the same listing with a great variability. We show that an automatic approach allows the detection, from field data, of user formulations that were not foreseen by the designers, and that they can be added, as variants, to the denominations already included in the system to reduce its failures.