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131
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COLING
1996
15 years 5 months ago
Computational Complexity of Probabilistic Disambiguation by means of Tree-Grammars
This paper studies the computational complexity of disambiguation under probabilistic tree-grammars as in (Bod, 1992; Schabes and Waters, 1993). It presents a proof that the follo...
Khalil Sima'an
139
Voted
ICDM
2008
IEEE
184views Data Mining» more  ICDM 2008»
15 years 10 months ago
Bayesian Co-clustering
In recent years, co-clustering has emerged as a powerful data mining tool that can analyze dyadic data connecting two entities. However, almost all existing co-clustering techniqu...
Hanhuai Shan, Arindam Banerjee
143
Voted
ICDM
2007
IEEE
124views Data Mining» more  ICDM 2007»
15 years 10 months ago
Community Learning by Graph Approximation
Learning communities from a graph is an important problem in many domains. Different types of communities can be generalized as link-pattern based communities. In this paper, we p...
Bo Long, Xiaoyun Xu, Zhongfei (Mark) Zhang, Philip...
142
Voted
KDD
2009
ACM
245views Data Mining» more  KDD 2009»
16 years 4 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
160
Voted
PKDD
2010
Springer
313views Data Mining» more  PKDD 2010»
15 years 2 months ago
Topic Modeling for Personalized Recommendation of Volatile Items
One of the major strengths of probabilistic topic modeling is the ability to reveal hidden relations via the analysis of co-occurrence patterns on dyadic observations, such as docu...
Maks Ovsjanikov, Ye Chen