In Email Analytics, our main focus on criminal and civil investigation from large email dataset. It is very difficult to deal with challenging task for investigator due to large size of email dataset. This paper offer an interactive email analytics various to current and manually intensive technique is used for search evidence from large email dataset. In investigation process, many emails are irrelevant to the investigation so it will force investigator to search carefully through email in order to find relevant emails manually. This process is very costly in terms of money and times. To help to investigation process. We combine Elasticsearch, Logstash and Kibana for data storing, data preprocessing, data visualization and data analytics and displaying results. In this process reduce the number of email which are irrelevant for investigation. It shows the relationship between them and also analyzing the email corpus based on topic relation using text mining.
Tema simples de apresentação Latex para UNB - Universidade de Brasília, derivado de outro template cujas informações estão abaixo.
Name :: sthlm Beamer Theme HEAVILY based on the hsrmbeamer theme (Benjamin Weiss)
Author :: Mark Hendry Olson (firstname.lastname@example.org)
Created :: 2013-07-31
Updated :: [[April]] 04, 2017 at 16:26:39
Version :: 2.0.2
The Web has evolved from a system of internet servers supporting formatted documents into a web of linked data. In the last years, the Web of Data is constantly growing. Consequently, it has developed a large collection of interlinked data sets from multiple domains. To exploit the diversity of all available data, federated queries are needed. However, many problems such as processing power, query response time, high workload or outdated information are hindering the query processing. In this paper, I am aiming to explain various optimization techniques which have the potential to lead a significant improvement on the final query runtime. I will start by briefly introducing recent approaches of federation and show why SPARQL federation endpoints are mostly in my focus. Specifically, I will compare state-of-the-art SPARQL query federation engines and analyze respective optimization approaches. The main federation engines I will analyze in terms of query optimization are FedX, DARQ and SPLENDID. As the result I provide concrete examples and conclude which of the engines has the best performance based on the query execution time as key criterion.
Basic Math Practice worksheet
By Matthew Ferguson
Randomly Generates a PDF with
56 addition problems for a desired
Difficulty level (currently single digits).
Useful as a worksheet for early elementary school students.