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Vectorial Web Search

General similarity search of quantifiable resources is possible on the Web, if these are represented in standardized way. As standardized data structure for representation of quantifiable resources a "Vectorial Resource Descriptor" or "VRD" is proposed, which contains a feature vector for representation of the quantitative data and a "Vector Space Identifier" or "VSI" (a HTTP URI) which uniquely identifies the meaning of every dimension (number) of the feature vector. Feature vectors of VRDs with the same VSI are directly comparable using a given metric. At this similarities of the resources' data are mapped to spatial similarities of the feature vectors. So similarity search is possible by calculating distances: resources are the more similar, the smaller the distance between the feature vectors of the representing VRDs is. This vectorial (numeric) similarity search could be efficiently combined with conventional word based search. We describe this here:
Realization of vectorial web search (2009)

Concrete standard for VRD representation (2010, discussion topic, please send comments and proposals to me)

Application in medicine (2010 published here)

Additional information:
A Searchable Patient Record Database for Decision Support (2009, also here accessible)
Design of a global medical database which is searchable by human diagnostic patterns* (2008, also here accessible)
Short video (2008, with old nomenclature using the word "pattern"* instead of VRD)
*Change of nomenclature and data representation since 10. October 2009, please contact me in case of interest in details.
Many numeric data are stored in separated databases in the hidden web. The proposed VRD structure gives also motivation to pack such numeric data in a globally accessible and interchangeable form. So it could also help to make hidden (numeric) data from the deep web accessible for all people.

Keywords:
VRD, Vectorial Resource Descriptor, VSI, Vector Space Identifier, QRI, HTTP URI, feature vector, Vectorial Web Search

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