Manzai Robots: Entertainment Robots Based on Auto-Created Manzai Scripts from Web News Articles

2014 ◽  
Vol 26 (5) ◽  
pp. 662-664 ◽  
Author(s):  
Tomohiro Umetani ◽  
◽  
Ryo Mashimo ◽  
Akiyo Nadamoto ◽  
Tatsuya Kitamura ◽  
...  
Keyword(s):  
Data Mining ◽  
The Internet ◽  
System Configuration ◽  
Robot System ◽  
Using Data ◽  
Web News

<div class=""abs_img""><img src=""[disp_template_path]/JRM/abst-image/00260005/18.jpg"" width=""300"" />Manzai robots</div> This paper introduces manzai robots – entertainment robots that automatically create manzai scripts from Internet articles based on keywords given by the audiences and perform manzai based on created manzai scripts. The robot consists two robots connected to the Internet that automatically create manzai scripts from Web news articles in response to a user’s keywords using data mining and manzai techniques. After manzai scripts are created, the two robots perform manzai using these scripts. This paper reviews the robot system configuration, manzai script creation, and robot-based management. </span>

Threat Detection in Cyber Security Using Data Mining and Machine Learning Techniques

2020 ◽  
pp. 234-253
Author(s):  
Daniel Kobla Gasu
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
Intrusion Detection ◽  
Cyber Security ◽  
Attack Detection ◽  
Machine Learning Techniques ◽  
The Internet ◽  
Threat Detection ◽  
Use Of The Internet ◽  
Using Data

The internet has become an indispensable resource for exchanging information among users, devices, and organizations. However, the use of the internet also exposes these entities to myriad cyber-attacks that may result in devastating outcomes if appropriate measures are not implemented to mitigate the risks. Currently, intrusion detection and threat detection schemes still face a number of challenges including low detection rates, high rates of false alarms, adversarial resilience, and big data issues. This chapter describes a focused literature survey of machine learning (ML) and data mining (DM) methods for cyber analytics in support of intrusion detection and cyber-attack detection. Key literature on ML and DM methods for intrusion detection is described. ML and DM methods and approaches such as support vector machine, random forest, and artificial neural networks, among others, with their variations, are surveyed, compared, and contrasted. Selected papers were indexed, read, and summarized in a tabular format.

Malware Detection in Android Using Data Mining

2017 ◽  
Vol 6 (2) ◽  
pp. 1-17 ◽  
Author(s):  
Suparna Dasgupta ◽  
Soumyabrata Saha ◽  
Suman Kumar Das
Keyword(s):  
Data Mining ◽  
Supervised Learning ◽  
Execution Time ◽  
Classification Tree ◽  
The Internet ◽  
Data Set ◽  
Software Packages ◽  
Using Data ◽  
Day By Day ◽  
User Location

This article describes how as day-to-day Android users are increasing, the Internet has become the type of environment preferred by attackers to inject malicious packages. This is content with the intention of gathering critical information, spying on user details, credentials, call logs, contact details, and tracking user location. Regrettably it is very hard to detect malware even with antivirus software/packages. In addition, this type of attack is increasing day by day. In this article the authors have chosen a Supervised Learning Classification Tree-based algorithm to detect malware on the data set. Comparison amongst all the classifiers on the basis of accuracy and execution time are used to build the classifier model which has the highest executed detections.

scholarly journals Employing Data Mining Techniques in Testing the Effectiveness of Modernization Theory

2016 ◽  
Vol 2 (1) ◽  
pp. 98
Author(s):  
Tolga Aydın
Keyword(s):  
Data Mining ◽  
Economic Development ◽  
Mobile Phone ◽  
Important Variable ◽  
The Internet ◽  
Modernization Theory ◽  
Data Mining Techniques ◽  
Mobile Phone Usage ◽  
Using Data ◽  
New Variables

This interdisciplinary study is concerned with testing the effectiveness of Modernization Theory in explaining regime change by means of data mining techniques. Modernization Theory, which links democratization with economic development (improvements in income, urbanization, industrialization, education and communication levels), has been criticized widely. Many criticisms posited that there is not a significant relation between economic development and democratization. This study is an attempt to test whether the theory has improved its effectiveness with the advent of the Internet and mobile phone technologies. To this end, first, the variables are introduced. Then, the study makes an analysis by using data mining techniques. It first tests the correlation between democratization and improvements in income, education, urbanization and communication levels within the period between 1976 and 1995. Then it adds the new variables, the Internet and mobile phone usage, and tests the correlation between democratization and this new range of variables for 1996-2015 period. In the conclusion, the study evaluates whether the effectiveness of Modernization Theory is improved when the Internet and mobile phone usage are added as the new variables. It is found that there is not a strong relation between income per capita and democratization as some critics of the Modernization Theory suggest, but other factors emphasized by this theory like improvements in education and communication have a more decisive effect. Moreover, among our new variables, Internet usage proved to be a really important variable conducive to democratization according to test results.

scholarly journals Prediction of Emergency Admissions in Health Centres using Data Mining

2020 ◽  
Vol 9 (8) ◽  
pp. 664-667
Keyword(s):  
Data Mining ◽  
The Internet ◽  
Free Text ◽  
Accuracy Score ◽  
Patient Records ◽  
Negative Consequences ◽  
Emergency Admissions ◽  
X Ray ◽  
Health Centres ◽  
Using Data

In recent days, Emergency Department in healing centre is crowded, which causes negative consequences for patients. The internet is a crucial bridge for connecting patients with medical services. The data of the patients in healing centre contain data like physician note, x-ray radiology, discharge rundowns which are unstructured. In the predictive inspection, the free text is an essential part of patient records and it is necessary. To avoid this situation, the patient data should be analyzed, and the prediction should be made. Such a pathway can be created utilizing data mining procedures, which involves inspection and observing data to obtain vital data and knowledge through which decisions can be taken. Here the understanding focuses of intrigued are entered through a webpage that's put absent inside the database. Then administrative data from three different healing centre is applied to algorithms like Logistic Regression, CART decision tree for prediction, and its accuracy score is compared.

scholarly journals Career and Skills Recommendations using Data Mining Technique: Matching Right People for Right Profession, in Pakistani Context

2018 ◽  
pp. 93-101
Author(s):  
◽  
◽  
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
Educational Background ◽  
The Internet ◽  
Job Seekers ◽  
Data Mining Technique ◽  
Association Rules Mining ◽  
Mining Technique ◽  
Using Data ◽  
Different Sources

There are a number of recommendation systems available on the internet for the help of jobseekers. These systems only generate job recommendations for people on the basis of input entered by user. The problem observed in Pakistani people is they are not clear in which field they should start or switch working. Before searching and applying for a job, one should be clear about his/her profession and important skills regarding selected profession. Based on above issues, there is a need to design such a system that can overcome the problem of profession selection and skills suggestions so that it can be easy for a jobseeker to apply for a specific job. In this research, the problem which is discussed above is resolved by proposing a model by using Association Rules Mining, a data mining technique. In this model, professions are recommended to job seekers by matching the profile of applicant or job seeker with those persons who have same profile like educational background, professional skills and the type of jobs which they are doing. The data collected for this research itself is a major contribution as we collected it from different sources. We will make this data publically available for others so that they can use for further research.

scholarly journals Salary Estimator using Data Science

2020 ◽  
Vol 6 (12) ◽  
pp. 319-322
Author(s):  
Winner Walecha and Dr. Bhoomi Gupta
Keyword(s):  
Data Mining ◽  
Random Forest ◽  
Data Science ◽  
The Internet ◽  
Prediction System ◽  
Lasso Regression ◽  
Data Mining Technique ◽  
Mining Technique ◽  
Number Of Factors ◽  
Using Data

This paper presents a salary prediction system using the job listings from an employment website, in this case Glassdoor.com. A data mining technique is used to generate a model which will scrape number of jobs from the employment website, clean it on the basis of number of factors including the rival companies, revenue and skill required thereby predicting the salary to be expected when applying for a data science job. Techniques like linear regression, lasso regression, random forest regressors are optimised using GridsearchCV to reach the best model. The model can be further extended to build a flask API thus can be deployed on the internet for public usage.

Visualization and Analysis of 3D Images Using Data Mining Approaches

2020 ◽  
pp. 289-295
Author(s):  
Parimala Boobalan
Keyword(s):  
Data Mining ◽  
Large Scale ◽  
Realistic Model ◽  
Natural Sciences ◽  
The Internet ◽  
3D Images ◽  
Using Data ◽  
Numeric Data ◽  
Innovative Techniques ◽  
Insight Into

With the recent advancements in supercomputer technologies, large-scale, high-precision, and realistic model 3D simulations have been dominant in the field of solar-terrestrial physics, virtual reality, and health. Since 3D numeric data generated through simulation contain more valuable information than available in the past, innovative techniques for efficiently extracting such useful information are being required. One such technique is visualization—the process of turning phenomena, events, or relations not directly visible to the human eye into a visible form. Visualizing numeric data generated by observation equipment, simulations, and other means is an effective way of gaining intuitive insight into an overall picture of the data of interest. Meanwhile, data mining is known as the art of extracting valuable information from a large amount of data relative to finance, marketing, the internet, and natural sciences, and enhancing that information to knowledge.

Scalable Component-Based Manzai Robots as Automated Funny Content Generators

2016 ◽  
Vol 28 (6) ◽  
pp. 862-869 ◽  
Author(s):  
Tomohiro Umetani ◽  
◽  
Satoshi Aoki ◽  
Kazuhiro Akiyama ◽  
Ryo Mashimo ◽  
...  
Keyword(s):  
The Internet ◽  
Software Components ◽  
Robot System ◽  
Distributed Software ◽  
Search Results ◽  
Stand Up Comedy ◽  
Robot Technology ◽  
Web News

[abstFig src='/00280006/10.jpg' width='300' text='Tabletop component-based Manzai robots' ] This manuscript describes a scalable tabletop Manzai robot system that has been developed using distributed software components. Manzai is a style of traditional Japanese stand-up comedy that is typically performed by two comedians – a stooge and a straight man. Manzai script refers to the dialogues exchanged between the two comedians. Manzai robots automatically generate their Manzai scripts from web news articles based on keywords provided by audiences and search results on the Internet. Then, the robots perform according to these Manzai scripts. This study focuses on the flexibility and scalability of a robot system based on distributed Robot Technology (RT) components. The results of the implementation experiments demonstrate the flexibility of the Manzai performing robots and the scalability of the functions of the robot system.

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