Soft Integration of Geo-Tagged Data Sets in J-CO-QL+

The possibility offered by the current technology to collect and store data sets regarding public places located on Earth globe is posing new challenges, as far integration of these concerned. Analysts usually need perform such an from scratch, without performing complex long preprocessing or data-cleaning tasks, well training activities that require tedious labeling data; furthermore, analysts now have deal with popular JSON format stored within document stores. This paper demonstrates a methodology based soft (i.e., performed through computing fuzzy sets) can be effectively applied J-CO Framework, which stand-alone tool devised process stores, possibly querying sets. Specifically, provides following contributions: (1) It presents soft-computing technique for integrating describing places, any preliminary pre-processing, cleaning training, scratch; (2) it capabilities sets, provided Framework; (3) effectiveness technique; (4) shows how able support (as Framework) effective efficient in data-integration tasks scratch.