12th International Conference on Knowledge Discovery and Information Retrieval

KDIR 2020


Data Mining & Analysis Databases & Information Systems



CALL FOR PAPERS
12th International Conference on Knowledge Discovery and Information Retrieval KDIR
website: http://www.kdir.ic3k.org
November 2 - 4, 2020 Budapest, Hungary
In Cooperation with: ACM SIGAI, APPIA, APRP and AI*IA.
Proceedings will be submitted for indexation by: DBLP, Thomson Reuters, EI, SCOPUS, Semantic Scholar, Google Scholar and Microsoft Academic.
IMPORTANT DATES:
Regular Paper Submission: May 19, 2020
Authors Notification (regular papers): July 17, 2020
Final Regular Paper Submission and Registration: July 31, 2020
Position Paper Submission: July 24, 2020
Authors Notification (position papers): September 2, 2020
Final Regular Paper Submission and Registration: September 16, 2020
Scope:
Knowledge Discovery is an interdisciplinary area focusing upon methodologies for identifying valid, novel, potentially useful and meaningful patterns from data, often based on underlying large data sets. A major aspect of Knowledge Discovery is data mining, i.e. applying data analysis and discovery algorithms that produce a particular enumeration of patterns (or models) over the data. Knowledge Discovery also includes the evaluation of patterns and identification of which add to knowledge. This has proven to be a promising approach for enhancing the intelligence of software systems and services. The ongoing rapid growth of online data due to the Internet and the widespread use of large databases have created an important need for knowledge discovery methodologies. The challenge of extracting knowledge from data draws upon research in a large number of disciplines including statistics, databases, pattern recognition, machine learning, data visualization, optimization, and high-performance computing, to deliver advanced business intelligence and web discovery solutions. Information retrieval (IR) is concerned with gathering relevant information from unstructured and semantically fuzzy data in texts and other media, searching for information within documents and for metadata about documents, as well as searching relational databases and the Web. Automation of information retrieval enables the reduction of what has been called "information overload". Information retrieval can be combined with knowledge discovery to create software tools that empower users of decision support systems to better understand and use the knowledge underlying large data sets. The primary focus of KDIR is to provide a major forum for the scientific and technical advancement of knowledge discovery and information retrieval.
Conference Topics:
Area 1: KDIR - International Conference on Knowledge Discovery and Information Retrieval
- Machine Learning
- Deep Learning
- Neural Networks
- Information Extraction
- Context Discovery
- Business Intelligence Applications
- Statistical Methods
- Data Analytics
- Data Reduction and Quality Assessment
- Interactive and Online Data Mining
- Mining Multimedia Data
- Mining Text and Semi-Structured Data
- Pre-Processing and Post-Processing for Data Mining
- Concept Mining
- Process Mining
- Web Mining
- Data Mining in Electronic Commerce
- Visual Data Mining and Data Visualization
- Knowledge Discovery in Databases
- Pattern Recogntion
- Feature Selection
- Clustering and Classification Methods
- User Profiling and Recommender Systems
- BioInformatics & Pattern Discovery
- Collaborative Filtering
- Software Frameworks
KDIR KEYNOTE LECTURE
Alexander Smirnov, SPIIRAS, Russian Federation
Manfred Reichert, Ulm University, Germany
KDIR CONFERENCE CHAIR:
Joaquim Filipe, Polytechnic Institute of Setúbal / INSTICC, Portugal
KDIR PROGRAM CHAIR:
Ana Fred, Instituto de Telecomunicações and University of Lisbon, Portugal
PROGRAM COMMITTEE
http://www.kdir.ic3k.org/ProgramCommittee.aspx
KDIR Secretariat
Address: Avenida de S. Francisco Xavier, Lote 7 Cv. C
Tel: +351 265 520 185
Fax: +351 265 520 186
Web: http://www.kdir.ic3k.org
e-mail: kdir.secretariat@insticc.org