Social Networking activities raise multiple challenges for the evolution of Service Oriented Systems Engineering. The purpose of this research work is to demonstrate how a specific core technology and cloud platform with micro-services can be designed and used for performing data-intensive computations and implementing services in a real case of social analytics. In detail, we face the challenges of real-time data-intensive processing with the systematic application of in-memory view-based information modeling & computation, which is based on different types of non-materialized views without pre-aggregation of data. Finally, our study presents and compares design alternatives for these mappings, and demonstrates their effective application for implementing a large set of social analytics service types, with particular reference to the case of streaming sources of twitter data. A prototype of this system was experimented in the contest of a specific kind of social event, a permanent exhibition of Artworks, where the system collected and analyzed in real-time the tweets issued in an entire region, including exhibition sites, and continuously updated analytical dashboards placed in one of the exhibition rooms. © 2016 Elsevier B.V.
S-InTime: A social cloud analytical service oriented system / Piccialli, Francesco; Benedusi, Paolo; Amato, Flora. - In: FUTURE GENERATION COMPUTER SYSTEMS. - ISSN 0167-739X. - 80:(2018), pp. 229-241. [10.1016/j.future.2016.12.007]
S-InTime: A social cloud analytical service oriented system
Francesco Piccialli;Flora Amato
2018
Abstract
Social Networking activities raise multiple challenges for the evolution of Service Oriented Systems Engineering. The purpose of this research work is to demonstrate how a specific core technology and cloud platform with micro-services can be designed and used for performing data-intensive computations and implementing services in a real case of social analytics. In detail, we face the challenges of real-time data-intensive processing with the systematic application of in-memory view-based information modeling & computation, which is based on different types of non-materialized views without pre-aggregation of data. Finally, our study presents and compares design alternatives for these mappings, and demonstrates their effective application for implementing a large set of social analytics service types, with particular reference to the case of streaming sources of twitter data. A prototype of this system was experimented in the contest of a specific kind of social event, a permanent exhibition of Artworks, where the system collected and analyzed in real-time the tweets issued in an entire region, including exhibition sites, and continuously updated analytical dashboards placed in one of the exhibition rooms. © 2016 Elsevier B.V.File | Dimensione | Formato | |
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