{"title":"Automatic Hint Generation","authors":"A. Jatowt, Calvin Gehrer, Michael Färber","doi":"10.1145/3578337.3605119","DOIUrl":null,"url":null,"abstract":"At times when answers to user questions are readily and easily available (at essentially zero cost), it is important for humans to maintain their knowledge and strong reasoning capabilities. We believe that in many cases providing hints rather than final answers should be sufficient and beneficial for users as it requires thinking and stimulates learning as well as remembering processes. We propose in this paper a novel task of automatic hint generation that supports users in finding the correct answers to their questions without the need of looking the answers up. As the first attempt towards this new task, we design and implement an approach that uses Wikipedia to automatically provide hints for any input question-answer pair. We then evaluate our approach with a user group of 10 persons and demonstrate that the generated hints help users successfully answer more questions than when provided with baseline hints.","PeriodicalId":415621,"journal":{"name":"Proceedings of the 2023 ACM SIGIR International Conference on Theory of Information Retrieval","volume":"265 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2023 ACM SIGIR International Conference on Theory of Information Retrieval","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3578337.3605119","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
At times when answers to user questions are readily and easily available (at essentially zero cost), it is important for humans to maintain their knowledge and strong reasoning capabilities. We believe that in many cases providing hints rather than final answers should be sufficient and beneficial for users as it requires thinking and stimulates learning as well as remembering processes. We propose in this paper a novel task of automatic hint generation that supports users in finding the correct answers to their questions without the need of looking the answers up. As the first attempt towards this new task, we design and implement an approach that uses Wikipedia to automatically provide hints for any input question-answer pair. We then evaluate our approach with a user group of 10 persons and demonstrate that the generated hints help users successfully answer more questions than when provided with baseline hints.