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IPM
2008
100views more  IPM 2008»
14 years 11 months ago
Query-level loss functions for information retrieval
Many machine learning technologies such as support vector machines, boosting, and neural networks have been applied to the ranking problem in information retrieval. However, since...
Tao Qin, Xu-Dong Zhang, Ming-Feng Tsai, De-Sheng W...
HT
2010
ACM
14 years 9 months ago
On the robustness of google scholar against spam
In this poster we present the current results of several experiments in which we analyzed whether spamming Google Scholar is possible. Our results show, it is possible: We ,,impro...
Jöran Beel, Bela Gipp
CCS
2011
ACM
13 years 11 months ago
SURF: detecting and measuring search poisoning
Search engine optimization (SEO) techniques are often abused to promote websites among search results. This is a practice known as blackhat SEO. In this paper we tackle a newly em...
Long Lu, Roberto Perdisci, Wenke Lee
ERCIMDL
2009
Springer
117views Education» more  ERCIMDL 2009»
15 years 6 months ago
A Visualization Tool of Probabilistic Models for Information Access Components
An effective graphic interface is a key tool to improve the fruition of the results retrieved by an Information Retrieval (IR) system. In this work, we describe a two-dimensional...
Lorenzo De Stefani, Giorgio Maria Di Nunzio, Giorg...
RIAO
2007
15 years 1 months ago
Using Prior Information Derived from Citations in Literature Search
Researchers spent a large amount of their time searching through an ever increasing number of scientific articles. Although users of scientific search engines prefer the ranking o...
Edgar Meij, Maarten de Rijke