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WWW
2008
ACM
14 years 9 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...
NIPS
2007
13 years 10 months ago
A General Boosting Method and its Application to Learning Ranking Functions for Web Search
We present a general boosting method extending functional gradient boosting to optimize complex loss functions that are encountered in many machine learning problems. Our approach...
Zhaohui Zheng, Hongyuan Zha, Tong Zhang, Olivier C...
WWW
2011
ACM
13 years 3 months ago
Identifying primary content from web pages and its application to web search ranking
Web pages are usually highly structured documents. In some documents, content with different functionality is laid out in blocks, some merely supporting the main discourse. In ot...
Srinivas Vadrevu, Emre Velipasaoglu
KDD
2009
ACM
245views Data Mining» more  KDD 2009»
14 years 9 months ago
Mining rich session context to improve web search
User browsing information, particularly their non-search related activity, reveals important contextual information on the preferences and the intent of web users. In this paper, ...
Guangyu Zhu, Gilad Mishne
LREC
2008
155views Education» more  LREC 2008»
13 years 10 months ago
L-ISA: Learning Domain Specific Isa-Relations from the Web
Automated extraction of ontological knowledge from text corpora is a relevant task in Natural Language Processing. In this paper, we focus on the problem of finding hypernyms for ...
Alessandra Potrich, Emanuele Pianta