Enhancing Soft Web Intelligence with User-Defined Fuzzy Aggregators

In our previous work, we proposed Soft Web Intelligence as the interpretation of the general notion of Web Intelligence in the current technological panorama, in such a way JSON data sets are acquired from the Internet, stored within JSON document stores and then processed and queried by means of soft computing and soft querying methods. Specific extensions to the J-CO Framework and to its query language (named J-CO-QL+) made possible to practically implement the concept. However, any “data intelligence” activity does not exclude aggregating data, but J-CO-QL+ did not provide statements for defining “user-defined fuzzy aggregators”. In this paper, we present the novel constructs introduced into J-CO-QL+ to allow users to define and use their own fuzzy aggregators, so as to evaluate membership degrees to fuzzy sets moving from array fields within processed JSON documents. This way, complex soft queries are enabled, so as to enhance Soft Web Intelligence.