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ICDAR
2009
IEEE
8 years 6 months ago
Finding the Most Probable Ranking of Objects with Probabilistic Pairwise Preferences
This paper discusses the ranking of a set of objects when a possibly inconsistent set of pairwise preferences is given. We consider the task of ranking objects when pairwise prefe...
Mikhail Parakhin, Patrick M. Haluptzok
EMNLP
2009
8 years 6 months ago
Empirical Exploitation of Click Data for Task Specific Ranking
There have been increasing needs for task specific rankings in web search such as rankings for specific query segments like long queries, time-sensitive queries, navigational quer...
Anlei Dong, Yi Chang, Shihao Ji, Ciya Liao, Xin Li...
ACL
2009
8 years 6 months ago
Co-Feedback Ranking for Query-Focused Summarization
In this paper, we propose a novel ranking framework
Furu Wei, Wenjie Li, Yanxiang He
ACL
2009
8 years 6 months ago
Exploiting Bilingual Information to Improve Web Search
Web search quality can vary widely across languages, even for the same information need. We propose to exploit this variation in quality by learning a ranking function on bilingua...
Wei Gao, John Blitzer, Ming Zhou, Kam-Fai Wong
WEBI
2010
Springer
8 years 6 months ago
Ranking Approaches for Microblog Search
Ranking microblogs, such as tweets, as search results for a query is challenging, among other things because of the sheer amount of microblogs that are being generated in real time...
Rinkesh Nagmoti, Ankur Teredesai, Martine De Cock
WEBI
2010
Springer
8 years 6 months ago
How to Improve Your Google Ranking: Myths and Reality
Abstract--Search engines have greatly influenced the way people access information on the Internet as such engines provide the preferred entry point to billions of pages on the Web...
Ao-Jan Su, Y. Charlie Hu, Aleksandar Kuzmanovic, C...
NAACL
2010
8 years 6 months ago
Learning Dense Models of Query Similarity from User Click Logs
The goal of this work is to integrate query similarity metrics as features into a dense model that can be trained on large amounts of query log data, in order to rank query rewrit...
Fabio De Bona, Stefan Riezler, Keith Hall, Massimi...
ECIR
2010
Springer
8 years 6 months ago
Maximum Margin Ranking Algorithms for Information Retrieval
Abstract. Machine learning ranking methods are increasingly applied to ranking tasks in information retrieval (IR). However ranking tasks in IR often differ from standard ranking t...
Shivani Agarwal, Michael Collins
CIKM
2010
Springer
8 years 6 months ago
Probabilistic ranking for relational databases based on correlations
This paper proposes a ranking method to exploit statistical correlations among pairs of attribute values in relational databases. For a given query, the correlations of the query ...
Jaehui Park, Sang-goo Lee
AIRS
2010
Springer
8 years 6 months ago
Relevance Ranking Using Kernels
This paper is concerned with relevance ranking in search, particularly that using term dependency information. It proposes a novel and unified approach to relevance ranking using ...
Jun Xu, Hang Li, Chaoliang Zhong
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