Science and Research Journal
|ISSN 2619-9955 | eISSN 2619-9963 | Frequency:4/year | Peer Reviewed: Yes | UIKTEN Publisher|
Deep Learning and Optimization of Organizational Memory
© 2018 Anis Sefidanoski, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)
Citation Information: SAR Journal. Volume 1, Issue 3, Pages 115-118, ISSN 2619-9955, DOI: 10.18421/SAR13-06, September 2018.
Received: 07 August 2018
Accepted: 14 September 2018
Published: 26 September 2018
Knowledge is the greatest and the most valuable asset a company can have. With every customer interaction we learn more and get closer in providing the best possible customer service and experience. Employees are using valuable time and information dealing with dispersed data and information silos. Deep Learning (DL) based organizational memory (OM) platform aims to make information tangible, measurable and omnipresent in order to create 360 degree awareness of your corporate knowledge using cutting edge technologies, i.e. Artificial Intelligence (AI), Big Data, Machine Learning (ML), Internet of Things (IoT), Natural Language Processing (NLP) and predictive analytics, combined with the power of the new communication paradigms and interaction styles. Ubiquitous capture, processing and dissemination of knowledge will deliver unified and continuous knowledge management experience and evolve the way organization learns and works.
Keywords – Organizational Memory, Deep Learning, Artificial Intelligence, Big Data, Machine Learning.