{"title":"图形面搜索系统,以支持探索性搜索的概念理解","authors":"Mengtian Guo, Zhilan Zhou, D. Gotz, Yue Wang","doi":"10.1145/3588319","DOIUrl":null,"url":null,"abstract":"When people search for information about a new topic within large document collections, they implicitly construct a mental model of the unfamiliar information space to represent what they currently know and guide their exploration into the unknown. Building this mental model can be challenging as it requires not only finding relevant documents but also synthesizing important concepts and the relationships that connect those concepts both within and across documents. This article describes a novel interactive approach designed to help users construct a mental model of an unfamiliar information space during exploratory search. We propose a new semantic search system to organize and visualize important concepts and their relations for a set of search results. A user study (n=20) was conducted to compare the proposed approach against a baseline faceted search system on exploratory literature search tasks. Experimental results show that the proposed approach is more effective in helping users recognize relationships between key concepts, leading to a more sophisticated understanding of the search topic while maintaining similar functionality and usability as a faceted search system.","PeriodicalId":48574,"journal":{"name":"ACM Transactions on Interactive Intelligent Systems","volume":"22 1","pages":"1 - 36"},"PeriodicalIF":3.6000,"publicationDate":"2023-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"GRAFS: Graphical Faceted Search System to Support Conceptual Understanding in Exploratory Search\",\"authors\":\"Mengtian Guo, Zhilan Zhou, D. Gotz, Yue Wang\",\"doi\":\"10.1145/3588319\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"When people search for information about a new topic within large document collections, they implicitly construct a mental model of the unfamiliar information space to represent what they currently know and guide their exploration into the unknown. Building this mental model can be challenging as it requires not only finding relevant documents but also synthesizing important concepts and the relationships that connect those concepts both within and across documents. This article describes a novel interactive approach designed to help users construct a mental model of an unfamiliar information space during exploratory search. We propose a new semantic search system to organize and visualize important concepts and their relations for a set of search results. A user study (n=20) was conducted to compare the proposed approach against a baseline faceted search system on exploratory literature search tasks. Experimental results show that the proposed approach is more effective in helping users recognize relationships between key concepts, leading to a more sophisticated understanding of the search topic while maintaining similar functionality and usability as a faceted search system.\",\"PeriodicalId\":48574,\"journal\":{\"name\":\"ACM Transactions on Interactive Intelligent Systems\",\"volume\":\"22 1\",\"pages\":\"1 - 36\"},\"PeriodicalIF\":3.6000,\"publicationDate\":\"2023-02-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM Transactions on Interactive Intelligent Systems\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1145/3588319\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Transactions on Interactive Intelligent Systems","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1145/3588319","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
GRAFS: Graphical Faceted Search System to Support Conceptual Understanding in Exploratory Search
When people search for information about a new topic within large document collections, they implicitly construct a mental model of the unfamiliar information space to represent what they currently know and guide their exploration into the unknown. Building this mental model can be challenging as it requires not only finding relevant documents but also synthesizing important concepts and the relationships that connect those concepts both within and across documents. This article describes a novel interactive approach designed to help users construct a mental model of an unfamiliar information space during exploratory search. We propose a new semantic search system to organize and visualize important concepts and their relations for a set of search results. A user study (n=20) was conducted to compare the proposed approach against a baseline faceted search system on exploratory literature search tasks. Experimental results show that the proposed approach is more effective in helping users recognize relationships between key concepts, leading to a more sophisticated understanding of the search topic while maintaining similar functionality and usability as a faceted search system.
期刊介绍:
The ACM Transactions on Interactive Intelligent Systems (TiiS) publishes papers on research concerning the design, realization, or evaluation of interactive systems that incorporate some form of machine intelligence. TIIS articles come from a wide range of research areas and communities. An article can take any of several complementary views of interactive intelligent systems, focusing on:
the intelligent technology,
the interaction of users with the system, or
both aspects at once.