{"title":"在视觉分析中推断未明确的自然语言话语","authors":"V. Setlur, Melanie Tory, Alex Djalali","doi":"10.1145/3301275.3302270","DOIUrl":null,"url":null,"abstract":"Handling ambiguity and underspecification of users' utterances is challenging, particularly for natural language interfaces that help with visual analytical tasks. Constraints in the underlying analytical platform and the users' expectations of high precision and recall require thoughtful inferencing to help generate useful responses. In this paper, we introduce a system to resolve partial utterances based on syntactic and semantic constraints of the underlying analytical expressions. We extend inferencing based on best practices in information visualization to generate useful visualization responses. We employ heuristics to help constrain the solution space of possible inferences, and apply ranking logic to the interpretations based on relevancy. We evaluate the quality of inferred interpretations based on relevancy and analytical usefulness.","PeriodicalId":153096,"journal":{"name":"Proceedings of the 24th International Conference on Intelligent User Interfaces","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"50","resultStr":"{\"title\":\"Inferencing underspecified natural language utterances in visual analysis\",\"authors\":\"V. Setlur, Melanie Tory, Alex Djalali\",\"doi\":\"10.1145/3301275.3302270\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Handling ambiguity and underspecification of users' utterances is challenging, particularly for natural language interfaces that help with visual analytical tasks. Constraints in the underlying analytical platform and the users' expectations of high precision and recall require thoughtful inferencing to help generate useful responses. In this paper, we introduce a system to resolve partial utterances based on syntactic and semantic constraints of the underlying analytical expressions. We extend inferencing based on best practices in information visualization to generate useful visualization responses. We employ heuristics to help constrain the solution space of possible inferences, and apply ranking logic to the interpretations based on relevancy. We evaluate the quality of inferred interpretations based on relevancy and analytical usefulness.\",\"PeriodicalId\":153096,\"journal\":{\"name\":\"Proceedings of the 24th International Conference on Intelligent User Interfaces\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-03-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"50\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 24th International Conference on Intelligent User Interfaces\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3301275.3302270\",\"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 24th International Conference on Intelligent User Interfaces","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3301275.3302270","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Inferencing underspecified natural language utterances in visual analysis
Handling ambiguity and underspecification of users' utterances is challenging, particularly for natural language interfaces that help with visual analytical tasks. Constraints in the underlying analytical platform and the users' expectations of high precision and recall require thoughtful inferencing to help generate useful responses. In this paper, we introduce a system to resolve partial utterances based on syntactic and semantic constraints of the underlying analytical expressions. We extend inferencing based on best practices in information visualization to generate useful visualization responses. We employ heuristics to help constrain the solution space of possible inferences, and apply ranking logic to the interpretations based on relevancy. We evaluate the quality of inferred interpretations based on relevancy and analytical usefulness.