Information Extraction from Unstructured data using Augmented-AI and Computer Vision

Process of information extraction (IE) is often used to extract meaningful information from unstructured and unlabeled data. Conventional methods of data extraction including application of OCR and passing extraction engine, are inefficient on large data and have their limitation. In this paper, a peculiar technique of information extraction is proposed using A2I and computer vision technologies, which also includes NLP

A new analytics model for large scale multidimensional data visualization

© Springer International Publishing Switzerland 2015. With The Rise Of Big Data, The Challenge For Modern Multidimen-Sional Data Analysis And Visualization Is How It Grows Very Quickly In Size And Complexity. In This Paper, We First Present A Classification Method Called The 5ws Dimensions Which Classifies Multidimensional Data Into The 5ws Definitions. The 5ws Dimensions Can Be Applied To Multiple Datasets Such As Text Datasets, Audio Datasets And Video Datasets. Second, We Establish A Pair-Density Model To Analyze The Data Patterns To Compare The Multidimensional Data On The 5ws Patterns. Third, We Created Two Additional Parallel Axes By Using Pair-Density For Visualization. The Attributes Has Been Shrunk To Reduce Data Over-Crowding In Pair-Density Parallel Coordinates. This Has Achieved More Than 80% Clutter Reduction Without The Loss Of Information. The Experiment Shows That Our Model Can Be Efficiently Used For Big Data Analysis And Visualization

Big Data: development, advancement and implementation organizations in information age

With the advancement of the information age and knowledge, new techniques have been designed to allow the development, creation and evolution of strategies, tools and applications that facilitate internal and external actions of organizations. The purpose of this article is to show the results of a literature review of one of these techniques: Big Data. The methodology consisted of a review of the Scopus database throughout the last two years (2014-2016). Based on the findings, the importance, advantages and disadvantages of this application are discussed. It was clear that the use of Big Data is an important technique that contributes to handling large volumes of information and is used in the field of technology management in organizations; it confirmed the existence of organizations who, thanks to the implementation and use of Big Data, have managed to increase their competitiveness over other organization. Big Data has allowed them to reduce costs in operations, to ease processes, to design new business models and to take organizational decisions that have become more difficult to take because the volume of information increases constantly

Cloud Services Brokerage for Mobile Ubiquitous Computing

Recently, companies are adopting Mobile Cloud Computing (MCC) to efficiently deliver enterprise services to users (or consumers) on their personalized devices. MCC is the facilitation of mobile devices (e.g., smartphones, tablets, notebooks, and smart watches) to access virtualized services such as software applications, servers, storage, and network services over the Internet. With the advancement and diversity of the mobile landscape, there has been a growing trend in consumer attitude where a single user owns multiple mobile devices. This paradigm of supporting a single user or consumer to access multiple services from n-devices is referred to as the Ubiquitous Cloud Computing (UCC) or the Personal Cloud Computing. In the UCC era, consumers expect to have application and data consistency across their multiple devices and in real time. However, this expectation can be hindered by the intermittent loss of connectivity in wireless networks, user mobility, and peak load demands. Hence, this dissertation presents an architectural framework called, Cloud Services Brokerage for Mobile Ubiquitous Cloud Computing (CSB-UCC), which ensures soft real-time and reliable services consumption on multiple devices of users. The CSB-UCC acts as an application middleware broker that connects the n-devices of users to the multi-cloud services. The designed system determines the multi-cloud services based on the user's subscriptions and the n-devices are determined through device registration on the broker. The preliminary evaluations of the designed system shows that the following are achieved: 1) high scalability through the adoption of a distributed architecture of the brokerage service, 2) providing soft real-time application synchronization for consistent user experience through an enhanced mobile-to-cloud proximity-based access technique, 3) reliable error recovery from system failure through transactional services re-assignment to active nodes, and 4) transparent audit trail through access-level and context-centric provenance