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» A new family of online algorithms for category ranking
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SIGMOD
2007
ACM
181views Database» more  SIGMOD 2007»
14 years 5 months ago
Progressive and selective merge: computing top-k with ad-hoc ranking functions
The family of threshold algorithm (i.e., TA) has been widely studied for efficiently computing top-k queries. TA uses a sort-merge framework that assumes data lists are pre-sorted...
Dong Xin, Jiawei Han, Kevin Chen-Chuan Chang
ICML
2003
IEEE
14 years 5 months ago
Online Ranking/Collaborative Filtering Using the Perceptron Algorithm
In this paper we present a simple to implement truly online large margin version of the Perceptron ranking (PRank) algorithm, called the OAP-BPM (Online Aggregate Prank-Bayes Poin...
Edward F. Harrington
IBPRIA
2009
Springer
13 years 9 months ago
Large Scale Online Learning of Image Similarity through Ranking
ent abstract presents OASIS, an Online Algorithm for Scalable Image Similarity learning that learns a bilinear similarity measure over sparse representations. OASIS is an online du...
Gal Chechik, Varun Sharma, Uri Shalit, Samy Bengio
WWW
2005
ACM
14 years 5 months ago
Object-level ranking: bringing order to Web objects
In contrast with the current Web search methods that essentially do document-level ranking and retrieval, we are exploring a new paradigm to enable Web search at the object level....
Zaiqing Nie, Yuanzhi Zhang, Ji-Rong Wen, Wei-Ying ...
ICDE
2005
IEEE
133views Database» more  ICDE 2005»
14 years 6 months ago
Efficient Inverted Lists and Query Algorithms for Structured Value Ranking in Update-Intensive Relational Databases
We propose a new ranking paradigm for relational databases called Structured Value Ranking (SVR). SVR uses structured data values to score (rank) the results of keyword search que...
Lin Guo, Jayavel Shanmugasundaram, Kevin S. Beyer,...