A grand challenge of the 21st Century is to make big data useful and usable to end users. An important aspect to tackle this challenge is to bring together two worlds: Human–Computer Interaction (HCI) and Knowledge Discovery from Data (KDD). A synergetic combination of theories, methods and approaches from both domains can make users active players in mining the data and discover the knowledge they need.

This special issue in the Journal Information Processing and Management (IPM) is aimed at reporting on recent research advances on theories and methods including Human-Computer Interaction & Knowledge Discovery from Data (HCI-KDD), with focus on the interactive analysis of weakly structured and unstructured data.

The special issue focuses on aspects related to interactive analytics of unstructured or weakly structured data, including understanding of human behavior, designing novel intelligent systems to support interactive analytics, and applications involving novel interactions of human with a data mining system, including:

a) Interactive Content Analytics from “unstructured” (weakly structured) data

b) Advanced Methods of collaborative Knowledge Discovery (e.g. swarm intelligence, collective intelligence, crowd sourcing) and collaborative Knowledge Discovery/Data Mining/Decision Making;

c) Intelligent, interactive, semi-automatic, multivariate Information Visualization and Visual Analytics;

d) Novel Search User Interaction Techniques (supporting human intelligence with computational intelligence);

e) Modeling Human Search Behavior and Understanding Human Information Needs;