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» Combining Candidate and Document Models for Expert Search
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SIGIR
2006
ACM
15 years 3 months ago
Learning a ranking from pairwise preferences
We introduce a novel approach to combining rankings from multiple retrieval systems. We use a logistic regression model or an SVM to learn a ranking from pairwise document prefere...
Ben Carterette, Desislava Petkova
ACL
2011
14 years 1 months ago
Jointly Learning to Extract and Compress
We learn a joint model of sentence extraction and compression for multi-document summarization. Our model scores candidate summaries according to a combined linear model whose fea...
Taylor Berg-Kirkpatrick, Dan Gillick, Dan Klein
GFKL
2005
Springer
142views Data Mining» more  GFKL 2005»
15 years 3 months ago
Near Similarity Search and Plagiarism Analysis
Abstract. Existing methods to text plagiarism analysis mainly base on “chunking”, a process of grouping a text into meaningful units each of which gets encoded by an integer nu...
Benno Stein, Sven Meyer zu Eissen
WISE
2007
Springer
15 years 4 months ago
Optimization of Bounded Continuous Search Queries Based on Ranking Distributions
A common search problem in the World Wide Web concerns finding information if it is not known when the sources of information appear and how long sources will be available on the ...
Dirk Kukulenz, Nils Hoeller, Sven Groppe, Volker L...
AMR
2008
Springer
214views Multimedia» more  AMR 2008»
14 years 11 months ago
Using Thematic Ontologies for User- and Group-Based Adaptive Personalization in Web Searching
This paper presents Prospector, an adaptive meta-search layer, which performs personalized re-ordering of search results. Prospector combines elements from two approaches to adapti...
Alexandros Paramythis, Florian König, Christi...