Sciweavers

Share
warning: Creating default object from empty value in /var/www/modules/taxonomy/taxonomy.module on line 1416.
PKDD
2015
Springer
9views Data Mining» more  PKDD 2015»
4 years 10 months ago
Discovering Opinion Spammer Groups by Network Footprints
Online reviews are an important source for consumers to evaluate products/services on the Internet (e.g. Amazon, Yelp, etc.). However, more and more fraudulent reviewers write fake...
Junting Ye, Leman Akoglu
PKDD
2015
Springer
19views Data Mining» more  PKDD 2015»
4 years 10 months ago
Safe Exploration for Active Learning with Gaussian Processes
In this paper, the problem of safe exploration in the active learning context is considered. Safe exploration is especially important for data sampling from technical and industria...
Jens Schreiter, Duy Nguyen-Tuong, Mona Eberts, Bas...
PKDD
2015
Springer
13views Data Mining» more  PKDD 2015»
4 years 10 months ago
Convex Factorization Machines
Abstract. Factorization machines are a generic framework which allows to mimic many factorization models simply by feature engineering. In this way, they combine the high predictiv...
Mathieu Blondel, Akinori Fujino, Naonori Ueda
PKDD
2015
Springer
10views Data Mining» more  PKDD 2015»
4 years 10 months ago
The Difference and the Norm - Characterising Similarities and Differences Between Databases
Suppose we are given a set of databases, such as sales records over different branches. How can we characterise the differences and the norm between these datasets? That is, what a...
Kailash Budhathoki, Jilles Vreeken
PAKDD
2015
ACM
13views Data Mining» more  PAKDD 2015»
4 years 10 months ago
What Is New in Our City? A Framework for Event Extraction Using Social Media Posts
Post streams from public social media platforms such as Instagram and Twitter have become precious but noisy data sources to discover what is happening around us. In this paper, we...
Chaolun Xia, Jun Hu, Yan Zhu, Mor Naaman
PAKDD
2015
ACM
21views Data Mining» more  PAKDD 2015»
4 years 10 months ago
Internal Clustering Evaluation of Data Streams
Abstract. Clustering validation is a crucial part of choosing a clustering algorithm which performs best for an input data. Internal clustering validation is efficient and realisti...
Marwan Hassani, Thomas Seidl 0001
PAKDD
2015
ACM
10views Data Mining» more  PAKDD 2015»
4 years 10 months ago
Coupling Multiple Views of Relations for Recommendation
Learning user/item relation is a key issue in recommender system, and existing methods mostly measure the user/item relation from one particular aspect, e.g., historical ratings, e...
Bin Fu, Guandong Xu, Longbing Cao, Zhihai Wang, Zh...
PAKDD
2015
ACM
10views Data Mining» more  PAKDD 2015»
4 years 10 months ago
Rank Matrix Factorisation
We introduce the problem of rank matrix factorisation (RMF). That is, we consider the decomposition of a rank matrix, in which each row is a (partial or complete) ranking of all co...
Thanh Le Van, Matthijs van Leeuwen, Siegfried Nijs...
PAKDD
2015
ACM
21views Data Mining» more  PAKDD 2015»
4 years 10 months ago
Scalable Outlying-Inlying Aspects Discovery via Feature Ranking
In outlying aspects mining, given a query object, we aim to answer the question as to what features make the query most outlying. The most recent works tackle this problem using tw...
Nguyen Xuan Vinh, Jeffrey Chan, James Bailey, Chri...
PAKDD
2015
ACM
14views Data Mining» more  PAKDD 2015»
4 years 10 months ago
Uncovering the Latent Structures of Crowd Labeling
Crowdsourcing provides a new way to distribute enormous tasks to a crowd of annotators. The divergent knowledge background and personal preferences of crowd annotators lead to nois...
Tian Tian, Jun Zhu
books