30 search results - page 3 / 6 » Query-level loss functions for information retrieval |
ECIR
2009
Springer
14 years 2 months ago
2009
Springer
Abstract. Learning ranking functions is crucial for solving many problems, ranging from document retrieval to building recommendation systems based on an individual user’s prefer...
SIGIR
2009
ACM
2009
ACM
Incorporating prior knowledge into a transductive ranking algorithm for multi-document summarization
13 years 11 months ago
This paper presents a transductive approach to learn ranking functions for extractive multi-document summarization. At the first stage, the proposed approach identifies topic th...
CIKM
2009
Springer
13 years 12 months ago
2009
Springer
Traditional boosting algorithms for the ranking problems usually employ the pairwise approach and convert the document rating preference into a binary-value label, like RankBoost....
RECSYS
2010
ACM
13 years 3 months ago
2010
ACM
A ranking approach, ListRank-MF, is proposed for collaborative filtering that combines a list-wise learning-to-rank algorithm with matrix factorization (MF). A ranked list of item...
CIKM
2004
Springer
13 years 10 months ago
2004
Springer
Automatically categorizing documents into pre-defined topic hierarchies or taxonomies is a crucial step in knowledge and content management. Standard machine learning techniques ...