PurposeThis article describes the knowledge‐mapping framework the authors designed based on their theoretical and practical research on knowledge mapping. It also shows the practical use of the Framework for companies interested in knowledge‐mapping tools.Design/methodology/approachIn the first place the authors position their research in the context of knowledge management and knowledge‐mapping research and practice. An example of their practical research on knowledge mapping is given as a preliminary step to describe their knowledge‐mapping framework. The use of this framework is illustrated. Finally, the authors validate their framework against a number of commercially available tools with knowledge‐mapping functionality.FindingsThe authors found that their framework is useful, insightful and robust when applied to new knowledge‐mapping tools/functionality.Research limitations/implicationsThe important issue how to embed knowledge‐mapping tools in organizations is not considered to be in the scope of this article.Practical implicationsBased on concrete examples the authors illustrate the practical implications of their knowledge‐mapping framework for companies. The Framework can be used for defining knowledge‐mapping tool requirements, the assessment and comparison of commercial tools, and the assessment of available knowledge in an organization.Originality/valueKnowledge mapping and its use have been a research issue for some time. Companies have also adopted knowledge‐mapping tools to support and stimulate knowledge sharing in their organizations and to help employees find the expertise they are looking for. But no research has been done on how to help companies decide what kind of knowledge‐mapping tool they need or how any tools they already have can be combined in a knowledge‐mapping tool. This article describes a unique and new Framework the authors devised to help companies do just that.

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Abstract. We present a preliminary study the aim of which is to provide a high level model for the evaluation of the trustworthiness of recommender systems as e-commerce services. We identify and comment on relevant trustworthiness indicators for the following different perspectives: user interface, content information and quality of recommendations.

Searching through information can be done in two ways: by querying and browsing. In the literature these approaches are treated separately. However every search usually consists of a combination of browsing and querying. Therefore this paper is about combining querying and browsing in one search interface.Our hypothesis is that both strategies can be combined and users will be better supported in their search for information. A model is presented how to combine these approaches and this model is evaluated by applying it in the knowledge-mapping domain.We will show that combining both strategies in one model is possible. Based on our evaluation of the application of this model we conclude that the users understand this combination and find it to be helpful.However several technical issues need to be addressed in our future research to confirm the usefulness of this combination.

Knowledge-mapping tools enable users to quickly identify relevant information and expertise. This paper discusses a number of natural-language phenomena that limit the performance of a straightforward approach. An empirical study on a real-life community provides a quantitative indication of the impact of this noise on the markup of concepts and retrieval of documents. We then discuss enhancing the usefulness of knowledgemapping tools through automatically derived concepts. General TermsDesign