Ukp -Unified Knowledge Platform
Smile can customise a Big Data simplification solution for you! A new collaborative project of scale for Smile Innovation: designing a new Unified Knowledge Platform (UKP)! This 100% Open Source platform aims to value all data (internal, external, behavioural...) used in your everyday activities. And it is a great pleasure for the R&D teams at Smile to work together with academic partners such as Armadillo, Proxem, Wallix, Esilv and LIPN. Thank you to the competitive cluster Systematic Paris- Region – GTLL and the BPL and the Ile de France Region for supporting the project. A key ambition to influence the future of Big Data With the explosion of massive databases and all the relational marketing challenges to bring brands closer to their clients, this project will mobilise teams for 36 months, for an investment of 3.5 million euros. As with any Smile project, implementation focuses on the reality of your daily activity, thanks to design discussions carried out from a business point of view. The objective? The platform must meet the needs of different usage concepts, with a specific focus on e-commerce, a favourite area of the project due to its very large added value! So what’s new in the UKP programme? From a technical point of view, the co-innovation approach with the partners of the consortium includes different aspects:
- Processing of data flow throughout its life cycle
- The creation of new algorithms analysing user behaviour (machine learning).
- Implementation of a “plant” with multichannel research motors
- Development of a modular and extensible architecture on the best Open Source bricks on the market.
This is just a preview, the latest innovations will be unveiled when the platform launches! A word from Marc DUTOO, head of R&D projects at Smile “This Unified Knowledge Platform project serves pragmatic objectives such as simplification of Big Data technology implementation for e-commerce optimisation. It will also enable us to obtain generic databases which make it possible to easily produce data optimisation platforms thanks to architecture available depending on the use. “