DocumentCode
2865866
Title
Supervised ordering - an empirical survey
Author
Kamishima, Toshihiro ; Kazawa, Hideto ; Akaho, Shotaro
Author_Institution
Nat. Inst. of Adv. Ind. Sci. & Technol., Japan
fYear
2005
fDate
27-30 Nov. 2005
Abstract
Ordered lists of objects are widely used as representational forms. Such ordered objects include Web search results or bestseller lists. In spite of their importance, methods of processing orders have received little attention. However, research concerning orders has become common; in particular, researchers have developed various methods for the task of supervised ordering to acquire functions for object sorting from example orders. Here, we give a unified view of these methods and our new one, and empirically survey their merits and demerits.
Keywords
learning (artificial intelligence); sorting; object sorting; ordered lists; ordered object; supervised ordering; Communication industry; Data mining; Laboratories; Marketing and sales; Random variables; Search engines; Sorting; Telegraphy; Telephony; Web search;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Mining, Fifth IEEE International Conference on
ISSN
1550-4786
Print_ISBN
0-7695-2278-5
Type
conf
DOI
10.1109/ICDM.2005.138
Filename
1565754
Link To Document