Title :
Visualized Elucidations of Ranking by Exploiting Object Relations
Author :
Zhang, Xinpeng ; Asano, Yasuhito ; Yoshikawa, Masatoshi
Author_Institution :
Grad. Sch. of Inf., Kyoto Univ. Yoshida-Honmachi, Kyoto
fDate :
March 29 2009-April 2 2009
Abstract :
For understanding human activity, a useful approach is to rank people according to the strength of their relations to a specified person. Similarly, rankings of objects based on such a relation are used in several fields. Several methods have been proposed for computing the strength of a relation between two objects. These methods do not present a reason why an object has a stronger relation to a specified object than another object has. Therefore, it is difficult for a user to understand a ranking obtained using these methods. On the other hand, the authors recently proposed a method for computing the strength of a relation through mining objects to elucidate the relation. We propose a ranking tool based on this method to afford a better understanding of a ranking. Our ranking tool has the following three characteristics for understanding a ranking: (1) it visualizes a relation by displaying objects that are important for elucidating the relation; (2) it classifies ranked objects into several groups, e.g., the two groups of "petroleum exporting countries\´\´ and "petroleum consuming countries\´\´ for ranking countries based on their respective relations to petroleum; and (3) it visualizes a reason explaining why an object has a stronger relation to a specified object than another object has. We explain novel ideas used in our ranking tool for understanding a ranking based on relations, and claim how effective the features of our tool are by presenting examples.
Keywords :
data mining; program visualisation; elucidation visualization; object display; object relations; petroleum exporting countries´; ranking methods; Data engineering; Data visualization; Design methodology; Diseases; Humans; Informatics; Petroleum; Social network services; Web pages; Wikipedia;
Conference_Titel :
Data Engineering, 2009. ICDE '09. IEEE 25th International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3422-0
Electronic_ISBN :
1084-4627
DOI :
10.1109/ICDE.2009.163