KDIR is part of IC3K, the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management. Registration to KDIR allows free access to all other IC3K conferences.
IC3K 2020 will be held in conjunction with WEBIST 2020, PECCS 2020, IJCCI 2020 and IN4PL 2020.
Registration to IC3K allows free access to the WEBIST, PECCS, IJCCI and IN4PL conferences (as a non-speaker).
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. 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.
Joaquim Filipe, Polytechnic Institute of Setubal / INSTICC, Portugal
Ana Fred, Instituto de Telecomunicações and Instituto Superior Técnico (University of Lisbon), Portugal
Alexander Smirnov, SPC RAS, Russian FederationManfred Reichert, Ulm University, GermanyFrank van Harmelen, The Hybrid Intelligence Center & Vrije Universiteit Amsterdam, NetherlandsStefan Decker, RWTH Aachen University, Germany
Publications:
It is planned to publish a short list of revised and
extended versions of presented papers with
Springer in a CCIS Series book
Proceedings will be submitted for evaluation for indexing by: