A model for the integration of interactive visualizations into the process of information searching and linking on the Web

The Web provides access to a mass of heterogeneous information such as: websites, news, articles, statistics, numbers, facts and so on. Accessing this information through search engines and browsing is nowadays a standard procedure for everyone. Interactive visualizations are not yet an integral part of this search process due to a long-time lack of standards for native graphics on the Web and a lack of models for their connectivity. However, interactive visualizations provide a lot of benefits like (1) a variety of different representations for big, heterogeneous and complex information and (2) their interactivity that supports the cognition process of the user. In this article, a model for the integration of interactive visualizations into the process of information searching and linking on the Web is developed. This enables interactive visualizations to be an integral part of the web search process. The model has been used as basis for the implementation of the Vizgr toolkit and has been applied and tested in different application scenarios. This article is a shortened and revised summary of the relevant chapter in the dissertation of Hienert (2013)

Recognizing Topic Change in Search Sessions of Digital Libraries based on Thesaurus and Classification System

Log analysis in Web search showed that user sessions often contain several different topics. This means sessions need to be segmented into parts which handle the same topic in order to give appropriate user support based on the topic, and not on a mixture of topics. Different methods have been proposed to segment a user session to different topics based on timeouts, lexical analysis, query similarity or external knowledge sources. In this paper, we study the problem in a digital library for the social sciences. We present a method based on a thesaurus and a classification system which are typical knowledge organization systems in digital libraries. Five experts evaluated our approach and rated it as good for the segmentation of search sessions into parts that treat the same topic