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Augmenting search with a Semantic Visual Graph --- Improving search in a large database by using a SVG visualization of a reduced Xml Topic Map

Paper, was published by Edwin de Jonge and Olav ten Bosch at 2006-01-03

This paper briefly describes a new approach to the concept of semantic search.

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Statistics Netherlands produces statistics on a wide spectrum of topics about Dutch society. All statistical results are published for free on the internet via the StatLine database, currently containing over 100 million statistical facts. Searching and finding information in such a large database is not trivial. This searching problem is aggravated because statistical institutes traditionally treat the statistical areas of interest differently. For example economical and social statistics are rarely made by the same statisticians. Many statistical areas however overlap and relate to one other. Each statistical overlapping area though has its own jargon, homonyms and synonyms, which makes searching difficult. However the end-user can’t be expected to know all these domain specific knowledge and should be provided with a powerful search engine that helps him find relevant statistics easily.

The search problem can be alleviated using semantic web technology (XTM) and SVG visualization. This paper briefly describes a new approach to this concept of semantic search focused on SVG visualization and implementation. This search mechanism combines an advanced search engine for statistics with a Semantic Visual Graph (SVG). Scalable Vector Graphics is the natural choice for its implementation because of the possibility to use animation, textPath and callback functionality. The paper gives an example where visualization is an integral part of the semantic searching process. The visualization enables a user not only to specify his search via keywords but also to search associatively, which makes users user find information more intuitively.

Authors

Edwin de Jonge

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The idea of Topic Maps is essential to enable dynamic information logistic. This requires a system that understands the context of the user to provide relevant informations and options automatically. Therefore semantic analysis is needed organizing content in a dynamic net structure.

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