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» Learning Deep Web Crawling with Diverse Features
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WEBI
2009
Springer
13 years 11 months ago
Learning Deep Web Crawling with Diverse Features
—The key to Deep Web crawling is to submit promising keywords to query form and retrieve Deep Web content efficiently. To select keywords, existing methods make a decision based ...
Lu Jiang, Zhaohui Wu, Qinghua Zheng, Jun Liu
CIKM
2011
Springer
12 years 4 months ago
Focusing on novelty: a crawling strategy to build diverse language models
Word prediction performed by language models has an important role in many tasks as e.g. word sense disambiguation, speech recognition, hand-writing recognition, query spelling an...
Luciano Barbosa, Srinivas Bangalore
ADMA
2009
Springer
142views Data Mining» more  ADMA 2009»
13 years 11 months ago
Crawling Deep Web Using a New Set Covering Algorithm
Abstract. Crawling the deep web often requires the selection of an appropriate set of queries so that they can cover most of the documents in the data source with low cost. This ca...
Yan Wang, Jianguo Lu, Jessica Chen
ICCSA
2007
Springer
13 years 11 months ago
Crawling the Content Hidden Behind Web Forms
The crawler engines of today cannot reach most of the information contained in the Web. A great amount of valuable information is “hidden” behind the query forms of online data...
Manuel Álvarez, Juan Raposo, Alberto Pan, F...
MMS
2006
13 years 4 months ago
A probabilistic semantic model for image annotation and multi-modal image retrieval
This paper addresses automatic image annotation problem and its application to multi-modal image retrieval. The contribution of our work is three-fold. (1) We propose a probabilis...
Ruofei Zhang, Zhongfei (Mark) Zhang, Mingjing Li, ...