Sciweavers

CIKM
2000
Springer
13 years 9 months ago
Boosting for Document Routing
RankBoost is a recently proposed algorithm for learning ranking functions. It is simple to implement and has strong justifications from computational learning theory. We describe...
Raj D. Iyer, David D. Lewis, Robert E. Schapire, Y...
VLDB
2004
ACM
129views Database» more  VLDB 2004»
13 years 10 months ago
Probabilistic Ranking of Database Query Results
We investigate the problem of ranking answers to a database query when many tuples are returned. We adapt and apply principles of probabilistic models from Information Retrieval f...
Surajit Chaudhuri, Gautam Das, Vagelis Hristidis, ...
COLT
2005
Springer
13 years 11 months ago
Learnability of Bipartite Ranking Functions
The problem of ranking, in which the goal is to learn a real-valued ranking function that induces a ranking or ordering over an instance space, has recently gained attention in mac...
Shivani Agarwal, Dan Roth
P2P
2005
IEEE
13 years 11 months ago
Finding Rare Data Objects in P2P File-Sharing Systems
Peer-to-peer file-sharing systems have hundreds of thousands of users sharing petabytes of data, however, their search functionality is limited. In general, query results contain...
Wai Gen Yee, Dongmei Jia, Ophir Frieder
SIGIR
2006
ACM
13 years 11 months ago
Learning to advertise
Content-targeted advertising, the task of automatically associating ads to a Web page, constitutes a key Web monetization strategy nowadays. Further, it introduces new challenging...
Anísio Lacerda, Marco Cristo, Marcos Andr&e...
CIKM
2007
Springer
13 years 11 months ago
Effective top-k computation in retrieving structured documents with term-proximity support
Modern web search engines are expected to return top-k results efficiently given a query. Although many dynamic index pruning strategies have been proposed for efficient top-k com...
Mingjie Zhu, Shuming Shi, Mingjing Li, Ji-Rong Wen
ICDE
2008
IEEE
189views Database» more  ICDE 2008»
13 years 12 months ago
Adapting ranking functions to user preference
— Learning to rank has become a popular method for web search ranking. Traditionally, expert-judged examples are the major training resource for machine learned web ranking, whic...
Keke Chen, Ya Zhang, Zhaohui Zheng, Hongyuan Zha, ...
TACAS
2010
Springer
146views Algorithms» more  TACAS 2010»
14 years 14 days ago
Ranking Function Synthesis for Bit-Vector Relations
Ranking function synthesis is a key aspect to the success of modern termination provers for imperative programs. While it is wellknown how to generate linear ranking functions for ...
Byron Cook, Daniel Kroening, Philipp Rümmer, ...
WSDM
2010
ACM
194views Data Mining» more  WSDM 2010»
14 years 2 months ago
Ranking with Query-Dependent Loss for Web Search
Queries describe the users' search intent and therefore they play an essential role in the context of ranking for information retrieval and Web search. However, most of exist...
Jiang Bian, Tie-Yan Liu, Tao Qin, Hongyuan Zha
ICDE
2010
IEEE
252views Database» more  ICDE 2010»
14 years 5 months ago
Semantic Ranking and Result Visualization for Life Sciences Publications
An ever-increasing amount of data and semantic knowledge in the domain of life sciences is bringing about new data management challenges. In this paper we focus on adding the seman...
Julia Stoyanovich, Kenneth A. Ross, William Mee