Personalized Social Search Based on Agglomerative Hierarchical Graph Clustering

Autor:	Kenkichi Ishizuka
Rok vydání:	2018
Předmět:	Social search Information retrieval Social network business.industry Computer science Cluster (physics) business Social network service Video retrieval Hierarchical clustering Clustering coefficient
Zdroj:	Information Retrieval Technology ISBN: 9783030035198 AIRS
DOI:	10.1007/978-3-030-03520-4_4
Popis:	This paper describes a personalized social search algorithm for retrieving multimedia contents of a consumer generated media (CGM) site having a social network service (SNS). The proposed algorithm generates cluster information on users in the social network by using an agglomerative hierarchical graph clustering, and stores it to a contents database (DB). Retrieved contents are sorted by scores calculated according to similarities of cluster information between a searcher and authors of contents. This paper also describes the evaluation experiments to confirm effectiveness of the proposed algorithm by implementing the proposed algorithm in a video retrieval system of a CGM site.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::237482bad0c9a6d3aafa825e9a0cb446 https://doi.org/10.1007/978-3-030-03520-4_4 Zobrazit plný text záznamu