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SPAA
2009
ACM
14 years 10 months ago
Beyond nested parallelism: tight bounds on work-stealing overheads for parallel futures
Work stealing is a popular method of scheduling fine-grained parallel tasks. The performance of work stealing has been extensively studied, both theoretically and empirically, but...
Daniel Spoonhower, Guy E. Blelloch, Phillip B. Gib...
KDD
2009
ACM
237views Data Mining» more  KDD 2009»
14 years 10 months ago
Exploring social tagging graph for web object classification
This paper studies web object classification problem with the novel exploration of social tags. Automatically classifying web objects into manageable semantic categories has long ...
Zhijun Yin, Rui Li, Qiaozhu Mei, Jiawei Han
KDD
2009
ACM
206views Data Mining» more  KDD 2009»
14 years 10 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
KDD
2009
ACM
227views Data Mining» more  KDD 2009»
14 years 10 months ago
User grouping behavior in online forums
Online forums represent one type of social media that is particularly rich for studying human behavior in information seeking and diffusing. The way users join communities is a re...
Xiaolin Shi, Jun Zhu, Rui Cai, Lei Zhang
KDD
2009
ACM
198views Data Mining» more  KDD 2009»
14 years 10 months ago
Pervasive parallelism in data mining: dataflow solution to co-clustering large and sparse Netflix data
All Netflix Prize algorithms proposed so far are prohibitively costly for large-scale production systems. In this paper, we describe an efficient dataflow implementation of a coll...
Srivatsava Daruru, Nena M. Marin, Matt Walker, Joy...