ACM DL

Knowledge Discovery from Data (TKDD)

Menu

Search Issue
enter search term and/or author name

Archive


ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 7 Issue 4, November 2013

iHypR: Prominence ranking in networks of collaborations with hyperedges1
Sibel Adali, Malik Magdon-Ismail, Xiaohui Lu
Article No.: 16
DOI: 10.1145/2541268.2541269

We present a new algorithm called iHypR for computing prominence of actors in social networks of collaborations. Our algorithm builds on the assumption that prominent actors collaborate on prominent objects, and prominent objects are naturally...

Social trust prediction using heterogeneous networks
Jin Huang, Feiping Nie, Heng Huang, Yi-Cheng Tu, Yu Lei
Article No.: 17
DOI: 10.1145/2541268.2541270

Along with increasing popularity of social websites, online users rely more on the trustworthiness information to make decisions, extract and filter information, and tag and build connections with other users. However, such social network data...

Solving inverse frequent itemset mining with infrequency constraints via large-scale linear programs
Antonella Guzzo, Luigi Moccia, Domenico Saccà, Edoardo Serra
Article No.: 18
DOI: 10.1145/2541268.2541271

Inverse frequent set mining (IFM) is the problem of computing a transaction database D satisfying given support constraints for some itemsets, which are typically the frequent ones. This article proposes a new formulation of IFM, called...

Formal and computational properties of the confidence boost of association rules
José L. Balcázar
Article No.: 19
DOI: 10.1145/2541268.2541272

Some existing notions of redundancy among association rules allow for a logical-style characterization and lead to irredundant bases of absolutely minimum size. We push the intuition of redundancy further to find an intuitive notion of novelty of...

Classification in P2P networks with cascade support vector machines
Hock Hee Ang, Vivekanand Gopalkrishnan, Steven C. H. Hoi, Wee Keong Ng
Article No.: 20
DOI: 10.1145/2541268.2541273

Classification in Peer-to-Peer (P2P) networks is important to many real applications, such as distributed intrusion detection, distributed recommendation systems, and distributed antispam detection. However, it is very challenging to perform...