Knowledge Discovery from Academic Search Engine

Authors:
Ye Wang;Miao Jiang;Xiaoling Wang;Aoying Zhou
Affiliations:
Network Information Center, Second Military Medical University, Shanghai 200433 and Department of Computer Science and Engineering, Fudan University, Shanghai 200433;Department of Computer Science and Engineering, Fudan University, Shanghai 200433;Shanghai Key Laboratory of Trustworthy Computing, Software Engineering Institute, East China Normal University, Shanghai 200062;Shanghai Key Laboratory of Trustworthy Computing, Software Engineering Institute, East China Normal University, Shanghai 200062
Venue:
KSEM '09 Proceedings of the 3rd International Conference on Knowledge Science, Engineering and Management
Year:
2009

Citing 9
Cited 0

Improved algorithms for topic distillation in a hyperlinked environment

Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
The anatomy of a large-scale hypertextual Web search engine

WWW7 Proceedings of the seventh international conference on World Wide Web 7
Authoritative sources in a hyperlinked environment

Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
Authoritative sources in a hyperlinked environment

Journal of the ACM (JACM)
The stochastic approach for link-structure analysis (SALSA) and the TKC effect

Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
Finding authorities and hubs from link structures on the World Wide Web

Proceedings of the 10th international conference on World Wide Web
Academic web search engine: generating a survey automatically

Proceedings of the 16th international conference on World Wide Web
Topic-bridged PLSA for cross-domain text classification

Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Search Computing

ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering

Quantified Score

Hi-index	0.00

Visualization

Abstract

The purpose of a search engine is to retrieve information relevant to a user's query from a big textual collection. However, most vertical search engines, such as Google Scholar and Citeseer, only return the flat ranked list without an efficient result exhibition and knowledge arrangement for given users. This paper considers the problem of knowledge discovery in the literature of search computing. We design some search and ranking strategies to mining potential knowledge from returned search results. A vertical search engine prototype, called Dolphin, is implemented where users are not only getting the results from search engine, but also the knowledge relevant to given query. Experiments show the effectiveness of our approach.