{"title":"A Multiple-Perspective, Interactive Approach for Web Information Extraction and Exploration","authors":"N. Moon, Yahsin. Hsu, Rahul Singh","doi":"10.1109/ICDEW.2006.11","DOIUrl":null,"url":null,"abstract":"While increasing amounts of complex information are becoming available on the web, there is, beyond keywordbased search and listing of results, a paucity of user interface paradigms and implementations that support interaction, exploration, and assimilation of information. This paper describes our design of a novel framework to address this deficiency. The proposed framework supports both direct search behavior as well as more exploratory search strategies through multiple-perspective visualization and interaction with search results. The approach is developed around the twin themes of supporting data context and facilitating effective interactions between users and data. The system supports data context through determination of semantic correlations between web pages and extraction of the spatio-temporal data contained therein. A multipleperspective environment is then used to display semantic and spatio-temporal relationships as well as to provide intuitive views of the data, specifically through web page thumbnail, map, and timeline modules. The environment supports direct interactions with the data through a reflective interface by which user selections in any one panel highlight the corresponding information in other panels. In this environment, visual cues and explicit facilities to model space and time aid in recognition, querying, and exploration of information as well as in representation and reasoning with complex relationships (such as spatio-temporal, causal, evolutionary) in the data. Experimental studies of a quantitative and qualitative nature demonstrate the efficacy of the system in facilitating both information extraction and discovery.","PeriodicalId":331953,"journal":{"name":"22nd International Conference on Data Engineering Workshops (ICDEW'06)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2006-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"22nd International Conference on Data Engineering Workshops (ICDEW'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDEW.2006.11","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
While increasing amounts of complex information are becoming available on the web, there is, beyond keywordbased search and listing of results, a paucity of user interface paradigms and implementations that support interaction, exploration, and assimilation of information. This paper describes our design of a novel framework to address this deficiency. The proposed framework supports both direct search behavior as well as more exploratory search strategies through multiple-perspective visualization and interaction with search results. The approach is developed around the twin themes of supporting data context and facilitating effective interactions between users and data. The system supports data context through determination of semantic correlations between web pages and extraction of the spatio-temporal data contained therein. A multipleperspective environment is then used to display semantic and spatio-temporal relationships as well as to provide intuitive views of the data, specifically through web page thumbnail, map, and timeline modules. The environment supports direct interactions with the data through a reflective interface by which user selections in any one panel highlight the corresponding information in other panels. In this environment, visual cues and explicit facilities to model space and time aid in recognition, querying, and exploration of information as well as in representation and reasoning with complex relationships (such as spatio-temporal, causal, evolutionary) in the data. Experimental studies of a quantitative and qualitative nature demonstrate the efficacy of the system in facilitating both information extraction and discovery.