Dignum, Stephen; Kim, Yunhyong; Kruschwitz, Udo; Song, Dawei; Fasli, Maria and De Roeck, Anne
- Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
|Google Scholar:||Look up in Google Scholar|
Information retrieval has become very popular over the last
decade with the advent of the Web. Nevertheless, searching on the Web is very different to searching on smaller, often more structured collections such as intranets and digital libraries. Such collections are the focus of the AutoAdapt project. The project seeks to aid user search by providing well structured domain knowledge to assist query modification and navigation.
There are two challenges: acquiring the domain knowledge and adapting it automatically to the specific interest of the user community. The paper introduces an implemented prototype that serves as a starting point on the
way to truly adaptive search.
|Item Type:||Conference Item|
|Copyright Holders:||2009 AT4DL|
|Project Funding Details:||
|Academic Unit/School:||Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
|Interdisciplinary Research Centre:||Centre for Research in Computing (CRC)|
|Depositing User:||Catherine McNulty|
|Date Deposited:||02 Feb 2011 22:24|
|Last Modified:||30 Nov 2016 15:31|
|Share this page:|
Download history for this item
These details should be considered as only a guide to the number of downloads performed manually. Algorithmic methods have been applied in an attempt to remove automated downloads from the displayed statistics but no guarantee can be made as to the accuracy of the figures.