ICSEKD 2016 - 2016 International Conference on Software Engineering and Knowledge Discovery

Software Engineering and Knowledge Discovery are two developing areas in the Information technology. These two fields are interrelated and have important roles in business, education, health, government, and society. Even though, these fields are considered quite mature, research in these areas are yet evolving with the objective of providing better performance of offered services.
Software Engineering is concerned with developing and maintaining software systems that behave reliably and efficiently, and satisfy all the requirements that customers have defined for them. It is important because of the impact of large, expensive software systems and the role of software in safety-critical applications. It integrates significant mathematics, computer science and practices whose origins are in engineering.
Knowledge Discovery is an interdisciplinary area that focuses on methodologies for identifying novel, valid, useful and meaningful patterns from data. Knowledge Discovery also includes the evaluation of patterns and identification of which add to knowledge.
Two tracks of submissions are solicited:
Software Engineering:
? Software Lifecycle
? Software Management
? Software Engineering Process
? Software Engineering Tools
? Software Analysis and Design Methods
? Software Quality Assurances
? Open Source Software
? Software Measurement
? Requirements Engineering
? Agile Methodology
? Extreme Programming
? Empirical Software Engineering
? Software Engineering Education
? Software Project Management
? Software Industry
? Software Product Line
? Software and System Security
? Configuration Management and Deployment
? Knowledge-Based Software Engineering
? Large-Scale Distributed Software Engineering
? Software Documentation
? Software Engineering of Web Services
? Software Inspection Approaches
? Software Modelling Approaches
? Software Performance Engineering
? Software Re-use and Product Development
? Software Reverse Engineering
? Testing, Analysis and Verification
Knowledge Discovery:
? Pattern Discovery
? Business Intelligence Applications
? Clustering and Classification Methods
? Collaborative Filtering
? Concept Mining
? Context Discovery
? Data Analytics
? Data Mining
? Data Reduction and Quality Assessment
? Foundations of Knowledge Discovery in Databases
? Information Extraction
? Interactive and Online Data Mining
? Machine Learning
? Mining Multimedia Data
? Mining Text and Semi-structured Data
? Pre-processing and Post-processing for Data Mining
? Process Mining
? Structured Data Analysis and Statistical Methods
? User Profiling and Recommender Systems
? Visual Data Mining and Data Visualization
? Web Mining