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ECIR
2011
Springer
14 years 1 months ago
Learning Models for Ranking Aggregates
Aggregate ranking tasks are those where documents are not the final ranking outcome, but instead an intermediary component. For instance, in expert search, a ranking of candidate ...
Craig Macdonald, Iadh Ounis
ECIR
2009
Springer
15 years 7 months ago
Mean-Variance Analysis: A New Document Ranking Theory in Information Retrieval
Abstract. This paper concerns document ranking in information retrieval. In information retrieval systems, the widely accepted probability ranking principle (PRP) suggests that, fo...
Jun Wang
COLING
2010
14 years 5 months ago
Towards a Unified Approach to Simultaneous Single-Document and Multi-Document Summarizations
Single-document summarization and multidocument summarization are very closely related tasks and they have been widely investigated independently. This paper examines the mutual i...
Xiaojun Wan
EMNLP
2008
14 years 11 months ago
An Exploration of Document Impact on Graph-Based Multi-Document Summarization
The graph-based ranking algorithm has been recently exploited for multi-document summarization by making only use of the sentence-to-sentence relationships in the documents, under...
Xiaojun Wan
ICML
2009
IEEE
15 years 10 months ago
BoltzRank: learning to maximize expected ranking gain
Ranking a set of retrieved documents according to their relevance to a query is a popular problem in information retrieval. Methods that learn ranking functions are difficult to o...
Maksims Volkovs, Richard S. Zemel