Title :
Link Structure Ranking Algorithm for Trading Networks
Author_Institution :
Grad. Sch. of Inf. Sci. & Technol., Hokkaido Univ., Sapporo
Abstract :
Ranking algorithms based on link structure of the network are well-known methods in Web search engines to improve the quality of the searches. The most famous ones are PageRank and HITS. PageRank uses probability of a random surfer to visit a page as the score of that page, and HITS instead of produces one score, proposes using two scores, authority and hub scores. In this paper, we introduce a new link structure ranking algorithm for trading network based on the differences between trading network and WWW network in the links addition process, a process that known to be the foundation of PageRank and HITS formulation. In the last section, we describe the using of proposed algorithm as a tool for network clustering in addition to its original function as a ranking method.
Keywords :
Internet; electronic trading; pattern clustering; probability; search engines; HITS formulation; WWW network clustering; Web search engine; link structure ranking algorithm; online trading network; pagerank; probability; Clustering algorithms; Competitive intelligence; Intelligent networks; Intelligent structures; Internet; Software algorithms; Software quality; Sparse matrices; Testing; World Wide Web; HITS; PageRank; network clustering; ranking algorithms; trading networks;
Conference_Titel :
Complex, Intelligent and Software Intensive Systems, 2009. CISIS '09. International Conference on
Conference_Location :
Fukuoka
Print_ISBN :
978-1-4244-3569-2
Electronic_ISBN :
978-0-7695-3575-3
DOI :
10.1109/CISIS.2009.27
