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» Providing ranked relevant results for web database queries
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WWW
2008
ACM
14 years 8 months ago
Learning to rank relational objects and its application to web search
Learning to rank is a new statistical learning technology on creating a ranking model for sorting objects. The technology has been successfully applied to web search, and is becom...
Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, De-Sheng Wang...
WWW
2004
ACM
14 years 8 months ago
A community-aware search engine
Current search technologies work in "one size fits all" fashion. Therefore, the answer to a query is independent of specific user information need. In this paper, we des...
Rodrigo B. Almeida, Virgílio A. F. Almeida
ICDE
2006
IEEE
97views Database» more  ICDE 2006»
14 years 1 months ago
Measuring Generality of Documents
Most traditional Information Retrieval (IR) systems, including web search engines, operationalize “relevant” as the word frequency in a document of a set of keywords. Because ...
Hyun Woong Shin, Eduard H. Hovy, Dennis McLeod, La...
PSSS
2003
13 years 9 months ago
DLDB: Extending Relational Databases to Support Semantic Web Queries
Abstract: We present DLDB, a knowledge base system that extends a relational database management system with additional capabilities for DAML+OIL inference. We discuss a number of ...
Zhengxiang Pan, Jeff Heflin
EDBT
2011
ACM
256views Database» more  EDBT 2011»
12 years 11 months ago
RanKloud: a scalable ranked query processing framework on hadoop
The popularity of batch-oriented cluster architectures like Hadoop is on the rise. These batch-based systems successfully achieve high degrees of scalability by carefully allocati...
K. Selçuk Candan, Parth Nagarkar, Mithila N...