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» Learning to Rank for Personalized News Article Retrieval
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CIKM
2008
Springer
13 years 9 months ago
Answering general time sensitive queries
Time is an important dimension of relevance for a large number of searches, such as over blogs and news archives. So far, research on searching over such collections has largely f...
Wisam Dakka, Luis Gravano, Panagiotis G. Ipeirotis
WSDM
2012
ACM
352views Data Mining» more  WSDM 2012»
12 years 2 months ago
Multi-relational matrix factorization using bayesian personalized ranking for social network data
A key element of the social networks on the internet such as Facebook and Flickr is that they encourage users to create connections between themselves, other users and objects. On...
Artus Krohn-Grimberghe, Lucas Drumond, Christoph F...
CIKM
2009
Springer
14 years 1 months ago
Enabling multi-level relevance feedback on pubmed by integrating rank learning into DBMS
Background: Finding relevant articles from PubMed is challenging because it is hard to express the user’s specific intention in the given query interface, and a keyword query ty...
Hwanjo Yu, Taehoon Kim, Jinoh Oh, Ilhwan Ko, Sungc...
CIKM
2010
Springer
13 years 6 months ago
Context modeling for ranking and tagging bursty features in text streams
Bursty features in text streams are very useful in many text mining applications. Most existing studies detect bursty features based purely on term frequency changes without takin...
Wayne Xin Zhao, Jing Jiang, Jing He, Dongdong Shan...
KDD
2006
ACM
141views Data Mining» more  KDD 2006»
14 years 7 months ago
Statistical entity-topic models
The primary purpose of news articles is to convey information about who, what, when and where. But learning and summarizing these relationships for collections of thousands to mil...
David Newman, Chaitanya Chemudugunta, Padhraic Smy...