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» Adapting ranking functions to user preference
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CIKM
2009
Springer
14 years 10 days ago
MRM: an adaptive framework for XML searching
In order to deal with the diversified nature of XML documents as well as individual user preferences, we propose a novel Multiodel (MRM), which is able to abstract a spectrum of i...
Ho Lam Lau, Wilfred Ng
ICDE
2003
IEEE
114views Database» more  ICDE 2003»
14 years 7 months ago
Ranked Join Indices
A plethora of data sources contain data entities that could be ordered according to a variety of attributes associated with the entities. Such orderings result effectively in a ra...
Panayiotis Tsaparas, Themistoklis Palpanas, Yannis...
DASFAA
2007
IEEE
173views Database» more  DASFAA 2007»
14 years 3 days ago
Towards Adaptive Information Merging Using Selected XML Fragments
As XML information proliferates on the Web, searching XML information via a search engine is crucial to the experience of both casual and experienced Web users. The returned XML fr...
Ho Lam Lau, Wilfred Ng
KDD
2005
ACM
143views Data Mining» more  KDD 2005»
14 years 6 months ago
SVM selective sampling for ranking with application to data retrieval
Learning ranking (or preference) functions has been a major issue in the machine learning community and has produced many applications in information retrieval. SVMs (Support Vect...
Hwanjo Yu
ICDE
2010
IEEE
202views Database» more  ICDE 2010»
14 years 5 months ago
Ranked Queries over Sources with Boolean Query Interfaces without Ranking Support
Many online or local data sources provide powerful querying mechanisms but limited ranking capabilities. For instance, PubMed allows users to submit highly expressive Boolean keywo...
Panagiotis G. Ipeirotis, Vagelis Hristidis, Yuheng...