Automated knowledge discovery in advanced knowledge management

Purpose – To resent approaches and some research results of various research areas contributing to knowledge discovery from different sources, different data forms, on different scale, and for different purpose. Design/methodology/approach – Contribute to knowledge management by applying knowledge discovery approaches to enable computer search for the relevant knowledge whereas the humans give just broad directions. Findings – Knowledge discovery techniques proved to be very appropriate for many problems related to knowledge management. Surprisingly, it is often the case that already relatively simple approaches provide valuable results. Research limitations/implications – Still there are many open problems and scalability issues that arise when dealing with real‐world data and especially in the areas involving text and network analysis. Practical implications – Each problem should be handled with care, taking into account different aspects and selecting/extending the most appropriate available methods or developing some new approaches. Originality/value – This paper provides an interesting collection of selected knowledge discovery methods applied in different context but all contributing in some way to knowledge management. Several of the reported approaches were developed in collaboration with the authors of the paper with especial emphases on their usability for practical problems involving knowledge management.