Title :
Visual knowledge exploration and discovery from different points of view
Author :
Dadzie, Aba-Sah ; Petrelli, Daniela
Author_Institution :
Dept. of Inf. Studies, Univ. of Sheffield, Sheffield, UK
Abstract :
Complex scenario analysis requires the exploration of multiple hypotheses and supporting evidence for each argument posed. Knowledge-intensive organisations typically analyse large amounts of inter-related, heterogeneous data to retrieve the knowledge this contains and use it to support effective decision-making. We demonstrate the use of interactive graph visualisation to support hierarchical, task-driven, hypothesis investigation. The visual investigative analysis is guided by task and domain ontologies used to capture the structure of the investigation process and the experience gained and knowledge created in previous, related investigations.
Keywords :
data mining; data visualisation; decision making; information retrieval; ontologies (artificial intelligence); decision making; domain ontologies; heterogeneous data analysis; interactive graph visualisation; knowledge retrieval; knowledge-intensive organisations; visual knowledge discovery; visual knowledge exploration; Assembly systems; Bicycles; Computer science; Decision making; Failure analysis; Information analysis; Information retrieval; Ontologies; Project management; Visualization; H.5.2 [Information Interfaces and Presentation]: User Interfaces—Graphical user interfaces (GUI); K.6.1 [Management of Computing and Information Systems]: Project and People Management—Life Cycle;
Conference_Titel :
Visual Analytics Science and Technology, 2009. VAST 2009. IEEE Symposium on
Conference_Location :
Atlantic City, NJ
Print_ISBN :
978-1-4244-5283-5
DOI :
10.1109/VAST.2009.5333438