Unstructured data

Ontologies of combining structured and unstructured data Proposal, Research Project Plan X to be presented on [presentation date] [Student Name] Option: XXXXXXXXXXXXXX Advisor: XXXXX This proposal is submitted to the Computer and Information Science faculty in partial fulfillment for the degree Master of Science in Computer and Information Science. TABLE OF CONTENTS 1. Introduction 1 1.1 Background RESEARCH 1 1.2 IDENTIFY THE PROBLEM AREA 1 2. REsearch APPROACH 2 2.1 HYPOTHESIS 2 2.2

In some sense, the unstructured information is the intriguing information, however it 's hard to syn the Big information is a generally new term yet the definition demonstrates that it has been around for quite a while. Huge information is can be summed up by the three V 's, Volume, Velocity and Variety. Volume is when associations gather information from an assortment of sources, including business exchanges, online networking and data from sensor or machine-to-machine information. Prior to recent

with regards to unstructured data. Firstly understanding what unstructured data is of primary importance before trying to handle it. In simple terms unstructured data can be understood as data that can’t be stored in the form of rows and columns. It can be anything including email files, text documents, presentations, image and video files. Studies carried out by IDC and EMC forecasts that data will grow to 40 zettabyes (1 ZB = 1 billion TB). As of now more than 80% of all stored data in organizations

Solution Description Emergence of big data generated by an increased number of data sources led the evolution of many data-handling tools. Storing and analyzing vast amounts of structured and unstructured data is a big challenge. Traditional relational databases such as Oracle, DB2, HANA, MySQL, and SQL Server still handle structured data for enterprise applications like ERP and CRM and financial systems. Most of these databases have added some level of in-memory features exception to SAP HANA, which

Combining Structured and Unstructured Data Research Proposal - Plan A (11/11/ 2016) Option: Information System Proposed Completion Date: 11/11/2016 This proposal is submitted to the Computer and Information Science faculty in partial fulfillment for the degree Master of Science in Computer and Information Science TABLE OF CONTENTS 1. Introduction 1 1.1 Background RESEARCH 1 1.2 PROBLEM AREA 2 2. REsearch APPROACH 3 2.1 HYPOTHESIS 3 2.2 ANALYSIS APPROACH 3 3. EXPECTED RESEARCH ACCOMPLISHMENT

receive thousands of resumes from job seekers online. It is difficult to extract relevant information from a resume because of its unstructured and nonstandard structure. Also, it comes in different file types such as PDF, DOC, etc. This makes the information extraction even more challenging. With the dramatic growth of social media, a considerable amount of data becomes available to be exploited by many companies, organizations, and researchers based on their interests. The candidate’s behavior

Government Call Center Service Improvement Through Unstructured Data Analytics Overview Unstructured data analytics is an essential part of any Big Data offering. Making sense of unstructured data is time consuming and complicated, yet the insights generated from these data are valuable and meaningful if proper techniques are utilized. This report is to analyze the factors that could affect the resident satisfaction levels based on the government call center service. Two separated models

.1 Generic Strategy for Classifying a Text Document The main steps involved are i) document pre-processing, ii) feature extraction / selection iii) model selection iv) Training and testing the classifier. Information pre-preparing lessens the measure of the information content records essentially. It includes exercises like sentence limit determination [2], characteristic dialect particular stop-word disposal [1] [2] [3] and stemming [2] [4]. Stop-words are practical words which happen as often

Introduction Nowadays, terabytes to petabytes of data that is been stored and transmitted by numerous sources and organizations have realized that these data contain tangible value that has the potential to change the fortunes of a business. Top firms leverage their business through the valuable insights gained through these data to assist them in their decision making process. The huge chucks of data consists structured, semi structured and unstructured data. Organizations have switched their focus more

1 Data Lake A data lake is a massive, easily usable, centralized repository of large volumes of unstructured and structured data. The data lake approach is a ‘store-everything’ approach to big data. Data is not classified when the data is stored in the repository, so the value of the data is not unlocked. A data lake is unstructured when compared to a data warehouse. (‘Data Lake’, 2015) 1.2 Hadoop Hadoop is an open-source framework which is used for processing and analyzing big data. It consists