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KDD
2009
ACM
611views Data Mining» more  KDD 2009»
14 years 5 months ago
Fast approximate spectral clustering
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-s...
Donghui Yan, Ling Huang, Michael I. Jordan
KDD
2009
ACM
243views Data Mining» more  KDD 2009»
14 years 5 months ago
Exploiting Wikipedia as external knowledge for document clustering
In traditional text clustering methods, documents are represented as "bags of words" without considering the semantic information of each document. For instance, if two ...
Xiaohua Hu, Xiaodan Zhang, Caimei Lu, E. K. Park, ...
KDD
2009
ACM
245views Data Mining» more  KDD 2009»
14 years 5 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
KDD
2009
ACM
232views Data Mining» more  KDD 2009»
14 years 5 months ago
Classification of software behaviors for failure detection: a discriminative pattern mining approach
Software is a ubiquitous component of our daily life. We often depend on the correct working of software systems. Due to the difficulty and complexity of software systems, bugs an...
David Lo, Hong Cheng, Jiawei Han, Siau-Cheng Khoo,...
KDD
2009
ACM
190views Data Mining» more  KDD 2009»
14 years 5 months ago
Efficient influence maximization in social networks
Influence maximization is the problem of finding a small subset of nodes (seed nodes) in a social network that could maximize the spread of influence. In this paper, we study the ...
Wei Chen, Yajun Wang, Siyu Yang
KDD
2009
ACM
178views Data Mining» more  KDD 2009»
14 years 5 months ago
Catching the drift: learning broad matches from clickthrough data
Identifying similar keywords, known as broad matches, is an important task in online advertising that has become a standard feature on all major keyword advertising platforms. Eff...
Sonal Gupta, Mikhail Bilenko, Matthew Richardson
KDD
2009
ACM
187views Data Mining» more  KDD 2009»
14 years 5 months ago
New ensemble methods for evolving data streams
Advanced analysis of data streams is quickly becoming a key area of data mining research as the number of applications demanding such processing increases. Online mining when such...
Albert Bifet, Bernhard Pfahringer, Geoffrey Holmes...
KDD
2009
ACM
190views Data Mining» more  KDD 2009»
14 years 5 months ago
Named entity mining from click-through data using weakly supervised latent dirichlet allocation
This paper addresses Named Entity Mining (NEM), in which we mine knowledge about named entities such as movies, games, and books from a huge amount of data. NEM is potentially use...
Gu Xu, Shuang-Hong Yang, Hang Li
KDD
2009
ACM
206views Data Mining» more  KDD 2009»
14 years 5 months ago
Ranking-based clustering of heterogeneous information networks with star network schema
A heterogeneous information network is an information network composed of multiple types of objects. Clustering on such a network may lead to better understanding of both hidden s...
Yizhou Sun, Yintao Yu, Jiawei Han