New Frontiers in Applied Data Mining: PAKDD 2008 International Workshops, Osaka, Japan, May 20-23, 2008, Revised Selected PapersSanjay Chawla, Takashi Washio, Shin-ichi Minato, Shusaku Tsumoto, Takashi Onoda, Seiji Yamada, Akihiro Inokuchi 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. |
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acquisition active learning active SKM analysis appearing bit sequences attributes BDist bitmasks bucket calculated color compute counting data item Data Mining data stream database dataset defined denote detect Directed Acyclic Graph Dynamic Bayesian Networks evaluate example experimental results fibrotic stages Figure framework frequent itemsets fuzzy sets HDAG Heidelberg hit table I-Closed iMDOT intentional kernel interactive Japan kernel function Keyword Map Knowledge Discovery label LNAI LNCS Machine Learning main memory maximum repeating pattern method multi-set node ordered subtrees ordered trees paper parameter pattern matching problem Proc proposed Re-mining relevance type sample sentiment sentences shows sibling distance similarity SKM learning sorting algorithm string list string sorting Support Vector Machine synopsis trie topic map topic map prototypes transaction tree edit distance unordered trees unusual condition data weighted support