Conference Topics Topics at this conference include, but are not limited to: Business Analytics - Methods: Dimensionality Reduction, Feature Extraction, and Feature Selection Supervised, Semi-Supervised, and Unsupervised Methods Statistical Learning Theory Online Learning, Data Stream Mining, and Dynamic Data Mining Graph Mining and Semi-Structured Data patial and Temporal Data Mining Deep Learning and Neural Network Research Large Scale Data Mining Uncertainty Modeling in Data Mining Business Analytics - Applications: Credit Scoring and Financial Modeling Forecasting Fraud Detection Web Intelligence and Information Retrieval Marketing, Business Intelligence, and e-Commerce Decision Analysis and Decision Support Systems Social Network Analysis Privacy-preserving Data Mining and Privacy-related Issue Text Mining, Sentiment Analysis, and Opinion Mining Important Dates July 31, 2017: Deadline for submission of extended abstracts August 15, 2017: Accept/reject decision November 15, 2017: Deadline for early registration January 17-19, 2018: BAFI 2018 *Only one contributed abstract is accepted from the same presenting author. Submission Guidelines Authors are requested to submit a 600 word abstract in English using the platform available at the EasyChair system. Please do not attach any additional files at this time.
Data mining is the process of extracting hidden patterns from data. With data ever increasing in volume, mining it into usable information is becoming increasingly important. Data mining approaches are commonly used in a wide range of profiling services, including marketing, fraud detection, and scientific discovery. The FLAIRS Data Mining special track is devoted to data mining with the aim of presenting new and important contributions in this area.
This special track is devoted to showcasing the latest advances in the field of data mining research. Topics of interest include applications, such as intelligence analysis, genomics, bioinformatics and biometrics, medical and health industry, text, video, and multimedia mining, e-commerce, web, financial data analysis, intrusion detection, remote sensing, earth sciences, and astronomy; modeling algorithms such as hidden Markov models, decision trees, neural networks, or statistical methods and probabilistic methods; case studies in areas of application, or over different algorithms and approaches; feature extraction and selection; post-processing techniques such as visualization, summarization, or trending; preprocessing and data reduction; data engineering or warehousing; or other data mining research which is related to artificial intelligence. This year the special track received many quality submissions and, of these, accepted eight papers for presentation while three additional contributions were referred to the poster session. The majority of submissions dealt with improving well established algorithms, while a fraction of them took on new applications. Topics of papers presented at the conference reflect current trends in data mining, as follows.