Automated keyphrase extraction: assisting students in the search for online materials

Authors:
John Kilbride;Eleni Mangina
Affiliations:
Department of Computer Science, University College Dublin, Belfield, Dublin 4, Ireland;Department of Computer Science, University College Dublin, Belfield, Dublin 4, Ireland
Venue:
AWIC'05 Proceedings of the Third international conference on Advances in Web Intelligence
Year:
2005

Citing 9
Cited 0

Agents that reduce work and information overload

Communications of the ACM
GroupLens: an open architecture for collaborative filtering of netnews

CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
The anatomy of a large-scale hypertextual Web search engine

WWW7 Proceedings of the seventh international conference on World Wide Web 7
KEA: practical automatic keyphrase extraction

Proceedings of the fourth ACM conference on Digital libraries
A personalized television listings service

Communications of the ACM
Web-collaborative filtering: recommending music by crawling the Web

Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
Machine Learning

Machine Learning
On the MSE robustness of batching estimators

Proceedings of the 33nd conference on Winter simulation
Domain-specific keyphrase extraction

IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2

Quantified Score

Hi-index	0.00

Visualization

Abstract

A high percentage of today's students use the World Wide Web (WWW) on a regular basis as a source for information, learning materials and references. In order to find reliable and trustworthy material students must sift through the millions of pages available on the web. Search engines can greatly reduce the number of documents a student must navigate through. In order to use search engines and find reliable resources efficiently, students must learn a number of search techniques. As students gain experience, they will gradually build up a model of certain sites and the quality and types of content they contain. Classmates often collaborate with one another in the search for materials recommending books, web-sites and other resources to one another. This paper describes a system designed to assist students of a web-based learning environment, while searching for online materials. This is achieved by either acting autonomously or assisting users to create queries, perform searches and filter the search results.