Back to Results
First PageMeta Content
Relevance / Cluster analysis / Constrained clustering / Discounted cumulative gain / Query expansion / Vector space model / Precision and recall / Lemur Project / Information science / Information retrieval / Relevance feedback


Relevance Feedback based on Constrained Clustering: FDU at TREC 09 Bingqing Wang and Xuanjing Huang School of Computer Science and Technology Fudan University [removed]
Add to Reading List

Document Date: 2010-01-12 08:59:34

Open Document

File Size: 152,41 KB

Share Result on Facebook

Company

Information Extraction Systems / CCi / EMAP / /

Country

China / Singapore / /

Currency

COP / /

/

Event

FDA Phase / /

IndustryTerm

constrained clustering algorithm / web document retrieval / /

MarketIndex

Expected Mean / /

Organization

Shanghai Committee of Science and Technology / Bingqing Wang and Xuanjing Huang School of Computer Science / National Natural Science Foundation of China / Fudan University / National Aeronautics and Space Administration / Ministry of Education / /

Person

Ben Carterette / Sugato Basu / Trond Grenager / Claire Cardie / Javed A. Aslam / Claudio Carpineto / Christopher M. Bishop / Stefan Schroedl / Jenny Rose Finkel / Brigitte Bigi / Ian Davidson / Christopher Manning / James Allan / Kiri Wagsta / Giovanni Romano / Renato De Mori / Evangelos Kanoulas / Virgil Pavlu / Seth Rogers / /

Position

model for the query expansion task / /

Product

Stanford Named Entity / COPKMeans / Qrel-Phase 1 / ClueWeb 09 TREC Category B / RF09 / ClueWeb09 / Phase1 / /

PublishedMedium

Machine Learning / /

Technology

n=1 k=1 The algorithm / K-Means algorithm / constrained clustering algorithm / 1 COP-KMeans Algorithm / Machine Learning / COPKMeans algorithm / /

URL

http /

SocialTag