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» Parallel learning to rank for information retrieval
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SIGMOD
2009
ACM
190views Database» more  SIGMOD 2009»
15 years 10 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»
15 years 10 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
14 years 11 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»
15 years 3 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
15 years 3 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