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» Top-k Ranked Document Search in General Text Databases
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SIGIR
2012
ACM
12 years 1 months ago
Top-k learning to rank: labeling, ranking and evaluation
In this paper, we propose a novel top-k learning to rank framework, which involves labeling strategy, ranking model and evaluation measure. The motivation comes from the difficul...
Shuzi Niu, Jiafeng Guo, Yanyan Lan, Xueqi Cheng
WSDM
2009
ACM
104views Data Mining» more  WSDM 2009»
14 years 5 months ago
Top-k aggregation using intersections of ranked inputs
There has been considerable past work on efficiently computing top k objects by aggregating information from multiple ranked lists of these objects. An important instance of this...
Ravi Kumar, Kunal Punera, Torsten Suel, Sergei Vas...
SIGIR
2003
ACM
14 years 4 months ago
Generating hierarchical summaries for web searches
Hierarchies provide a means of organizing, summarizing and accessing information. We describe a method for automatically generating hierarchies from small collections of text, and...
Dawn J. Lawrie, W. Bruce Croft
ICDE
2009
IEEE
118views Database» more  ICDE 2009»
14 years 5 months ago
An Incremental Threshold Method for Continuous Text Search Queries
Abstract—A text filtering system monitors a stream of incoming documents, to identify those that match the interest profiles of its users. The user interests are registered at ...
Kyriakos Mouratidis, HweeHwa Pang
IMCSIT
2010
13 years 8 months ago
Quality Benchmarking Relational Databases and Lucene in the TREC4 Adhoc Task Environment
The present work covers a comparison of the text retrieval qualities of open source relational databases and Lucene, which is a full text search engine library, over English docume...
Ahmet Arslan, Ozgur Yilmazel