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ICASSP
2008
IEEE
15 years 4 months ago
A comparative study of probabilistic ranking models for spoken document summarization
The purpose of extractive document summarization is to automatically select a number of indicative sentences, passages, or paragraphs from the original document according to a tar...
Shih-Hsiang Lin, Yi-Ting Chen, Hsin-Min Wang, Bin ...
ICDE
2006
IEEE
128views Database» more  ICDE 2006»
15 years 4 months ago
Searching and Ranking Documents based on Semantic Relationships
Just as the link structure of the web is a critical component in today's web search, complex relationships (i.e., the different ways the dots are connected) will be an import...
Boanerges Aleman-Meza
IPM
2008
113views more  IPM 2008»
14 years 10 months ago
Lexical cohesion and term proximity in document ranking
We demonstrate effective new methods of document ranking based on lexical cohesive relationships between query terms. The proposed methods rely solely on the lexical relationships...
Olga Vechtomova, Murat Karamuftuoglu
CIKM
2010
Springer
14 years 8 months ago
Learning to rank relevant and novel documents through user feedback
We consider the problem of learning to rank relevant and novel documents so as to directly maximize a performance metric called Expected Global Utility (EGU), which has several de...
Abhimanyu Lad, Yiming Yang
86
Voted
INEX
2007
Springer
15 years 4 months ago
Structured Document Retrieval, Multimedia Retrieval, and Entity Ranking Using PF/Tijah
CWI and University of Twente used PF/Tijah, a flexible XML retrieval system, to evaluate structured document retrieval, multimedia retrieval, and entity ranking tasks in the conte...
Theodora Tsikrika, Pavel Serdyukov, Henning Rode, ...