Tekijä: Jinyan Li (ed.); Xue Li (ed.); Shuliang Wang (ed.); Jianxin Li (ed.); Quan Z. Sheng (ed.) Kustantaja: Springer (2016) Saatavuus: Noin 17-20 arkipäivää
Tekijä: Jianxin Li (ed.); Sen Wang (ed.); Shaowen Qin (ed.); Xue Li (ed.); Shuliang Wang (ed.) Kustantaja: Springer (2019) Saatavuus: Noin 17-20 arkipäivää
With the ever-growing power to generate, transmit and collect huge amounts of data, information overload is now an imminent problem to mankind. The overwhelming demand for information processing is not just about a better - derstanding of data, but also a better usage of data in a timely fashion. Data mining, or knowledge discovery from databases, is proposed to gain insight into aspects of dataand to help peoplemakeinformed,sensible, andbetter decisions. At present, growing attention has been paid to the study, development and - plication of data mining. As a result there is an urgent need for sophisticated techniques and tools that can handle new ?elds of data mining, e.g., spatialdata mining, biomedical data mining, and mining on high-speed and time-variant data streams. The knowledge of data mining should also be expanded to new applications. The1stInternationalConferenceonAdvancedDataMiningandApplications (ADMA 2005) aimed to bring together the experts on data mining throughout the world. It provided a leading international forum for the dissemination of original research results in advanced data mining techniques, applications, al- rithms, software and systems, and di?erent applied disciplines. The conference attracted 539 online submissions and 63 mailing submissions from 25 di?erent countriesandareas.Allfullpaperswerepeer reviewedbyatleastthreemembers of the Program Committee composed of international experts in data mining ?elds. A total number of 100 papers were accepted for the conference. Amongst them 25 papers were selected as regular papers and 75 papers were selected as short papers, yielding a combined acceptance rate of 17%.
