Expert Systems in data mining generally use knowledge extraction methods to form a classifier or predictor. These have the advantage of forming high quality results due to the inclusion of expert knowledge. The problem, however, is that they do not allow for autonomous knowledge discovery. Therefore, such systems will only find results that the expert is capable of giving examples about and wil...

This paper presents an approach to expert-guided subgroup discovery. The main step of the subgroup discovery process, the induction of subgroup descriptions, is performed by a heuristic beam search algorithm, using a novel parametrized definition of rule quality which is analyzed in detail. The other important steps of the proposed subgroup discovery process are the detection of statistically s...

This article provides an overview of expert finding systems which assist in the discovery of distributed expertise. We summarize requirements for expert finders, the current state of the art, and our corporately deployed expert finding system and its performance. We describe research directions in distributed expertise discovery and visualization. Introduction In a global economy, expertise is ...

The Discovery Bus, a multi-agent software system designed for automating aspects of Molecular Design, particularly expert decision making, is described. It extends approaches aimed at automating the processing of drug discovery information but where control remains with the human expert, to automating the " tacit knowledge " of the expert and best practice, which we model as a workflow, and exp...

The University College London Information Retrieval Group participated in both the Expert Search and Document Search tasks in the TREC2008 Enterprise Track. We used a generic two-stage approach, which consists of a document retrieval stage followed by an expert association discovery stage, for expert finding. Since document search is an integral part of our expert finding approach, we have stud...

Process discovery algorithms typically aim at discovering process models from event logs. Most discovery algorithms discover the model based on an event log, without allowing the domain expert to influence the discovery approach in any way. However, the user may have certain domain expertise which should be exploited to create a better process model. In this paper, we address this issue of inco...

BACKGROUND Multimorbidity, the co-occurrence of two or more chronic medical conditions within a single individual, is increasingly becoming part of daily care of general medical practice. Literature-based discovery may help to investigate the patterns of multimorbidity and to integrate medical knowledge for improving healthcare delivery for individuals with co-occurring chronic conditions. OB...