{"title":"ParamMacros: Creating UI Automation Leveraging End-User Natural Language Parameterization","authors":"Rebecca Krosnick, Steve Oney","doi":"10.1109/vl/hcc53370.2022.9833005","DOIUrl":null,"url":null,"abstract":"—Prior work in programming-by-demonstration (PBD) has explored ways to enable end-users to create custom automation without needing to write code. We propose a new end-user specifcation model – asking the end-user to explicitly identify parts of their natural language query that can be generalized. We built a PBD system, ParamMacros, where users frst generalize a concrete natural language question – identifying parameters and their possible values – and then create a demonstration of how to answer the question on the website of interest. ParamMacros then infers a generalized program by using the user-provided parameter values to identify relevant patterns in the website’s structure. In a lab study we found that participants were able to meaningfully parameterize natural language queries and felt such a parameterization and demonstration process would be useful for creating custom automation.","PeriodicalId":351709,"journal":{"name":"2022 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/vl/hcc53370.2022.9833005","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
—Prior work in programming-by-demonstration (PBD) has explored ways to enable end-users to create custom automation without needing to write code. We propose a new end-user specifcation model – asking the end-user to explicitly identify parts of their natural language query that can be generalized. We built a PBD system, ParamMacros, where users frst generalize a concrete natural language question – identifying parameters and their possible values – and then create a demonstration of how to answer the question on the website of interest. ParamMacros then infers a generalized program by using the user-provided parameter values to identify relevant patterns in the website’s structure. In a lab study we found that participants were able to meaningfully parameterize natural language queries and felt such a parameterization and demonstration process would be useful for creating custom automation.