Paper Info
Title
A Scoring Function for Retrieving Photo Sets with Broad Topic Coverage
Abstract
As a storage-unit of user created Web objects, the set has become an emerging challenge in the retrieval. Set search requires relevant sets to meet the information need of users, whereas traditional information retrieval focuses on finding relevant Web objects. This paper proposes a new approach to measure relevance of sets with respect to a user query by their topic coverage. The main idea of the proposed approach is to prefer the set which covers as many different query-related topics as possible. The problem domain of this paper is photo sets of the Flickr.com, which are collections of photos. The experimental result shows that our algorithm outperforms the previous collection selection algorithm.
Year
DOI
Venue
2009
10.1109/NCM.2009.102
NCM
Keywords
Field
DocType
broad topic coverage,photo set retrieval,relevant set,web object,user query,information retrieval,photo set,set search,collection selection,previous collection selection algorithm,image retrieval,information need,relevant web object,scoring function,ranking algorithm,new approach,traditional information retrieval,retrieving photo sets,noise,probability density function,tag clouds,data mining,score function
Collection selection,Data mining,Information needs,Information retrieval,Problem domain,Computer science,Image retrieval,Tag cloud,Probability density function
Conference
ISBN
Citations 
PageRank 
978-0-7695-3769-6
2
0.36
References 
Authors
12
2
Name
Order
Citations
PageRank
Sangjin Lee130.72
Jonghun Park249137.86