Poor data quality is known to compromise the credibility and efficiency of commercial and public endeavours. Also, the importance of managing data quality has increased manifold as the diversity of sources, formats and volume of data grows. This volume targets the data quality in the light of collaborative information systems where data creation and ownership is increasingly difficult to establish.

The two-volume set LNAI 7301 and 7302 constitutes the refereed proceedings of the 16th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2012, held in Kuala Lumpur, Malaysia, in May 2012. The total of 20 revised full papers and 66 revised short papers were carefully reviewed and selected from 241 submissions. The papers present new ideas, original research results, and practical development experiences from all KDD-related areas. The papers are organized in topical sections on supervised learning: active, ensemble, rare-class and online; unsupervised learning: clustering, probabilistic modeling in the first volume and on pattern mining: networks, graphs, time-series and outlier detection, and data manipulation: pre-processing and dimension reduction in the second volume.

The two-volume set LNAI 7301 and 7302 constitutes the refereed proceedings of the 16th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2012, held in Kuala Lumpur, Malaysia, in May 2012. The total of 20 revised full papers and 66 revised short papers were carefully reviewed and selected from 241 submissions. The papers present new ideas, original research results, and practical development experiences from all KDD-related areas. The papers are organized in topical sections on supervised learning: active, ensemble, rare-class and online; unsupervised learning: clustering, probabilistic modeling in the first volume and on pattern mining: networks, graphs, time-series and outlier detection, and data manipulation: pre-processing and dimension reduction in the second volume.

Asdataminingtechniquesandtoolsmature, theirapplicationdomainsextendto previousuncharteredterritories.The commontheme ofthe workshopsorganized along with the main 2008 Paci?c Asia Conference on Knowledge Discovery and Data Mining (PAKDD) in Osaka, Japan was to extend the application of data mining techniques to new frontiers. Thus the title of the proceedings: "New Frontiers in Application of Data Mining." For the 2008 program, three workshops were organized. 1. Algorithms for Large-Scale Information Processing (ALSIP). The focus of the workshop was novel algorithms and data structures to deal with p- cessing of very large data sets. 2. Data Mining for Decision Making and Risk Management (DMDRM), which emphasized applications of risk information derived from data mining te- niques on diverse applications ranging from medicine to marketing to chemistry. 3. Interactive Data Mining (IDM), which emphasized the relationship between techniques in data mining and human-computer interaction. In total 38 papers were submitted to the workshops. After consultation with theworkshopChairswhowereaskedto ranktheir submissions,18wereaccepted for publicationin this volume.We hope that the published papers propelfurther interest in the growing ?eld of knowledge discovery in databases (KDD). The paper selection of the industrial track and the workshops was made by the Program Committee of each organization. Upon the paper selection, the book was edited and managed by the volume editors.