Sciweavers

KDD
2009
ACM
173views Data Mining» more  KDD 2009»
14 years 4 months ago
The offset tree for learning with partial labels
We present an algorithm, called the offset tree, for learning in situations where a loss associated with different decisions is not known, but was randomly probed. The algorithm i...
Alina Beygelzimer, John Langford
KDD
2009
ACM
216views Data Mining» more  KDD 2009»
14 years 4 months ago
Finding a team of experts in social networks
Given a task T , a pool of individuals X with different skills, and a social network G that captures the compatibility among these individuals, we study the problem of finding X ,...
Theodoros Lappas, Kun Liu, Evimaria Terzi
KDD
2009
ACM
260views Data Mining» more  KDD 2009»
14 years 4 months ago
Enabling analysts in managed services for CRM analytics
Data analytics tools and frameworks abound, yet rapid deployment of analytics solutions that deliver actionable insights from business data remains a challenge. The primary reason...
Indrajit Bhattacharya, Shantanu Godbole, Ajay Gupt...
KDD
2009
ACM
156views Data Mining» more  KDD 2009»
14 years 4 months ago
Collusion-resistant anonymous data collection method
The availability and the accuracy of the data dictate the success of a data mining application. Increasingly, there is a need to resort to on-line data collection to address the p...
Mafruz Zaman Ashrafi, See-Kiong Ng
KDD
2009
ACM
167views Data Mining» more  KDD 2009»
14 years 4 months ago
Seven pitfalls to avoid when running controlled experiments on the web
Controlled experiments, also called randomized experiments and A/B tests, have had a profound influence on multiple fields, including medicine, agriculture, manufacturing, and adv...
Thomas Crook, Brian Frasca, Ron Kohavi, Roger Long...
KDD
2009
ACM
198views Data Mining» more  KDD 2009»
14 years 4 months ago
Heterogeneous source consensus learning via decision propagation and negotiation
Nowadays, enormous amounts of data are continuously generated not only in massive scale, but also from different, sometimes conflicting, views. Therefore, it is important to conso...
Jing Gao, Wei Fan, Yizhou Sun, Jiawei Han
KDD
2009
ACM
182views Data Mining» more  KDD 2009»
14 years 4 months ago
Scalable graph clustering using stochastic flows: applications to community discovery
Algorithms based on simulating stochastic flows are a simple and natural solution for the problem of clustering graphs, but their widespread use has been hampered by their lack of...
Venu Satuluri, Srinivasan Parthasarathy
KDD
2009
ACM
156views Data Mining» more  KDD 2009»
14 years 4 months ago
Query result clustering for object-level search
Query result clustering has recently attracted a lot of attention to provide users with a succinct overview of relevant results. However, little work has been done on organizing t...
Jongwuk Lee, Seung-won Hwang, Zaiqing Nie, Ji-Rong...
KDD
2009
ACM
239views Data Mining» more  KDD 2009»
14 years 4 months ago
Applying syntactic similarity algorithms for enterprise information management
: ? Applying Syntactic Similarity Algorithms for Enterprise Information Management Ludmila Cherkasova, Kave Eshghi, Charles B. Morrey III, Joseph Tucek, Alistair Veitch HP Laborato...
Ludmila Cherkasova, Kave Eshghi, Charles B. Morrey...
KDD
2009
ACM
185views Data Mining» more  KDD 2009»
14 years 4 months ago
Entity discovery and assignment for opinion mining applications
Opinion mining became an important topic of study in recent years due to its wide range of applications. There are also many companies offering opinion mining services. One proble...
Xiaowen Ding, Bing Liu, Lei Zhang