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SIGIR
2008
ACM
13 years 7 months ago
Learning to rank with partially-labeled data
Ranking algorithms, whose goal is to appropriately order a set of objects/documents, are an important component of information retrieval systems. Previous work on ranking algorith...
Kevin Duh, Katrin Kirchhoff
ICDE
2010
IEEE
209views Database» more  ICDE 2010»
14 years 2 months ago
TopCells: Keyword-based search of top-k aggregated documents in text cube
— Previous studies on supporting keyword queries in RDBMSs provide users with a ranked list of relevant linked structures (e.g. joined tuples) or individual tuples. In this paper...
Bolin Ding, Bo Zhao, Cindy Xide Lin, Jiawei Han, C...
ROCAI
2004
Springer
14 years 1 months ago
Learning Interestingness Measures in Terminology Extraction. A ROC-based approach
Abstract. In the field of Text Mining, a key phase in data preparation is concerned with the extraction of terms, i.e. collocation of words attached to specific concepts (e.g. Ph...
Mathieu Roche, Jérôme Azé, Yve...
WSDM
2012
ACM
267views Data Mining» more  WSDM 2012»
12 years 3 months ago
Learning to rank with multi-aspect relevance for vertical search
Many vertical search tasks such as local search focus on specific domains. The meaning of relevance in these verticals is domain-specific and usually consists of multiple well-d...
Changsung Kang, Xuanhui Wang, Yi Chang, Belle L. T...
ACL
2009
13 years 5 months ago
English-Chinese Bi-Directional OOV Translation based on Web Mining and Supervised Learning
In Cross-Language Information Retrieval (CLIR), Out-of-Vocabulary (OOV) detection and translation pair relevance evaluation still remain as key problems. In this paper, an English...
Yuejie Zhang, Yang Wang, Xiangyang Xue