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» Parallel learning to rank for information retrieval
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SIGMOD
2009
ACM
190views Database» more  SIGMOD 2009»
14 years 7 months ago
DataLens: making a good first impression
When a database query has a large number of results, the user can only be shown one page of results at a time. One popular approach is to rank results such that the "best&quo...
Bin Liu, H. V. Jagadish
SIGMOD
2009
ACM
175views Database» more  SIGMOD 2009»
14 years 7 months ago
Keyword search on structured and semi-structured data
Empowering users to access databases using simple keywords can relieve the users from the steep learning curve of mastering a structured query language and understanding complex a...
Yi Chen, Wei Wang 0011, Ziyang Liu, Xuemin Lin
CIKM
2008
Springer
13 years 9 months ago
Mining conceptual graphs for knowledge acquisition
This work addresses the use of computational linguistic analysis techniques for conceptual graphs learning from unstructured texts. A technique including both content mining and i...
Milagros Fernández, Eric Villemonte de la C...
JCDL
2005
ACM
100views Education» more  JCDL 2005»
14 years 1 months ago
Automatic extraction of titles from general documents using machine learning
In this paper, we propose a machine learning approach to title extraction from general documents. By general documents, we mean documents that can belong to any one of a number of...
Yunhua Hu, Hang Li, Yunbo Cao, Dmitriy Meyerzon, Q...
AIRS
2005
Springer
14 years 1 months ago
Query Expansion with the Minimum Relevance Judgments
Query expansion techniques generally select new query terms from a set of top ranked documents. Although a user’s manual judgment of those documents would much help to select goo...
Masayuki Okabe, Kyoji Umemura, Seiji Yamada