scholarly journals Website evaluation using opinion mining

2018 ◽  
Vol 7 (2.7) ◽  
pp. 51
Author(s):  
T V.R. Sai ◽  
SK Haaris ◽  
S Sridevi
Keyword(s):  
Data Mining ◽  
Opinion Mining ◽  
User Feedback ◽  
The Internet ◽  
Website Evaluation ◽  
The World ◽  
Frame Work ◽  
Mining Methods ◽  
Feedback Data

In this project we used opinion mining methods to evaluate various websites present on the internet. We also analyzed the approaches, tools, and dataset used by Scholars with their accuracy and we used this technology for evaluation of a website. Opinion mining is used in various scenarios around the world. But it is hardly used in websites evaluation which we are implementing with this project, as now a day’s, websites we regularly use are spamming with advertisements and unusable content. This paper proposed a frame work of evaluating a website using the user feedback on the website collected on our website. That collected feedback data is processed using a data mining software that is rapid miner. 

Web Usage Mining and Its Applications

2011 ◽  
pp. 1221-1225
Author(s):  
Yongjian Fu
Keyword(s):  
Data Mining ◽  
World Wide ◽  
Online Shopping ◽  
Rapid Development ◽  
User Feedback ◽  
Web Usage Mining ◽  
Web Based ◽  
Web Usage ◽  
The World ◽  
The Web

With the rapid development of the World Wide Web or the Web, many organizations now put their information on the Web and provide Web-based services such as online shopping, user feedback, technical support, and so on. Understanding Web usage through data mining techniques is recognized as an important area.

Model of Improving Searching Precision For Interactive Users with Searching Requirements

2013 ◽  
Vol 756-759 ◽  
pp. 833-836
Author(s):  
Tian Chong ◽  
Yan Ling Shao ◽  
Jian Jun Wang
Keyword(s):  
Data Mining ◽  
Search Engine ◽  
User Feedback ◽  
Demand Model ◽  
Model Based ◽  
Search Precision ◽  
The One ◽  
Feedback Data

This paper presents a model based on analysis on interactive users search needs. This model changes from the analysis on user's behavior to the one on search content, which reduces to violate users privacy, and enables users to actively participate in determining the needs of search from the client end in the search engine, in addition to establishment of search demand model based on a large number of user feedback data mining in the search engine subsystem, as a result of higher search precision with less client spending and higher user s participation.

scholarly journals Complexities in Implementing the Frame Work of E-Governance Plan of Indian Government in using with Developmental for Tamilnadu Citizens- By using Data Mining Methods

2019 ◽  
Vol 8 (4) ◽  
pp. 1035-1040
Keyword(s):  
Data Mining ◽  
Social Welfare ◽  
Tamil Nadu ◽  
Electronic Media ◽  
Indian Government ◽  
Information Mining ◽  
Frame Work ◽  
Mining Methods ◽  
The Government ◽  
Using Data

With the landing of advanced India affiliation, our nation is operational through solid computerized correspondence. In today circumstance, India government gives e-administrations to all people groups at their entryway ventures through e-administration. Invigorated by the need to change e-taxpayer supported organizations to e-incorporation applications, we recommend the use of information digging systems for preparing the legislative information to concentrate and partner data sections with genuine resident needs and in this manner empower the epitome of the later in future administrative choices. Information Mining systems are utilized to broke down the information gained from NeGP National e-Governance Plan is an activity of Government of India for making every administrative administration are accessible to natives of India through electronic media of different E-Governance ventures has been actualized in all states. In Tamil Nadu states providing various schemes followed by social welfare Schemes has been implemented in all districts. The recommended method of data mining can be accommodating for the government to supplementary investigate other public recipient systems.

scholarly journals Educational Data Mining (EDM)on the use of the Internet in the World of Indonesian Education

TEM Journal ◽  
2020 ◽  
pp. 1134-1140
Author(s):  
Robbi Rahim
Keyword(s):  
Data Mining ◽  
Internet Use ◽  
Educational Data Mining ◽  
Internet Usage ◽  
The Internet ◽  
Internet Users ◽  
The World ◽  
Data Source ◽  
Use Of The Internet ◽  
High Cluster

The purpose of this research is to analyze internet users in the world who are educated in Indonesia by utilizing computer science techniques. The use of the internet in question is the percentage in accessing the internet for ages 5-12 years old, 13-15 years old and 16-18 years old. The data source used is from https://www.bps.go.id/. The method used is kmedoids, while mapping in the form of clusters in this study uses 2 labels namely C1: high cluster for internet use and C2: low cluster for internet use. The results mention that the islands of Sumatra and Java dominate in the use of the internet in all ages. The results state that k-medoids can be applied to the case of mapping internet usage with an accuracy of mentioning above 90% and an error rate below 5%.

scholarly journals PENERAPAN DATA MINING DENGAN ALGORITMA C4.5 UNTUK KALKULASI DATA DALAM AL-QUR’AN TERJEMAHAN

2019 ◽  
Vol 6 (2) ◽  
pp. 152
Author(s):  
Asmira Mira Rusli
Keyword(s):  
Data Mining ◽  
Decision Trees ◽  
The World ◽  
C4.5 Algorithm ◽  
Mining Methods

<p><em>Al-Qur'an was delivered by Prophet Muhammad SAW to mankind to become a guide in life in the world, which has 30 Juz, 114 suras and 6,236 verses. In the Qur'an there are many words that are repeated in a surah on a particular topic. To find out the number of repetitions of the word, an application of data calculations is built in the Al-Qur'an translation that can facilitate the calculation of words. So that users can quickly find out the number of words that repeat and how accurate the data is. This application is made with C4.5 algorithm, one of the data mining methods. Using the C4.5 algorithm is expected to be able to solve the problem of search and calculation in the translation of the Qur'an. The advantages of the C4.5 algorithm are producing decision trees that can be easily interpreted, as well as acceptable and efficient levels of accuracy. In this case the accuracy of the C4.5 algorithm reaches 80%.</em></p><p><em><strong>Keywords</strong></em><em>: </em><em>al-quran, data mining, algoritma </em>C4.5</p><p><em>Al-Qur’an </em><em>disampaikan oleh Nabi Muhammad SAW kepada umat manusia untuk dijadikan pedoman dalam kehidupan di dunia, yang </em><em>mempunyai 30 Juz, 114 surah dan 6</em><em>.</em><em>236 ayat. Dalam Al-Qur’an </em><em>terdapat banyak kata yang berulang dalam suatu surah mengenai topik tertentu. Untuk mengetahui jumlah perulangan kata tersebut, maka dibangun sebuah aplikasi kalkulasi data dalam Al-Qur’an terjemahan yang dapat mempermudah pengkalkulasian kata. Sehingga pengguna bisa dengan cepat mengetahui jumlah kata yang berulang serta seberapa akuratnya data tersebut. Aplikasi ini dibuat dengan algoritma C4.5 salah satu metode data mining. Dengan menggunakan algoritma C4.5 diharapkan mampu menyelesaikan masalah pencarian dan pengkalkulasian dalam terjemahan Al-Qur’an. </em><em>Kelebihan </em><em>dari </em><em>algoritma C4.5 </em><em>yaitu </em><em>menghasilkan pohon keputusan yang </em><em>dapat dengan </em><em>mudah diinterprestasikan, </em><em>serta </em><em>tingkat akurasi yang dapat diterima dan efisien. </em><em>Dalamm kasus ini tingkat akurasi Algoritma C4.5 mencapai 80%</em><em>.</em></p><p><em><strong>Kata kunci</strong></em><em>: </em><em>al-quran, data mining, algoritma </em>C4.5</p>

scholarly journals Efficient Anonymization Algorithm for Multiple Sensitive Attributes

2019 ◽  
Vol 9 (1) ◽  
pp. 4961-4963
Keyword(s):  
Data Mining ◽  
Performance Evaluation ◽  
Information Loss ◽  
The Internet ◽  
Medical Applications ◽  
Huge Number ◽  
Sensitive Data ◽  
Privacy Preserving Data Mining ◽  
Privacy Model ◽  
Mining Methods

The data of medical applications over the internet contains sensitive data. There exist several methods that provide privacy for these data. Most of the privacy-preserving data mining methods make the assumption of the separation of quasi-identifiers (QID) from multiple sensitive attributes. But in reality, the attributes in a dataset possess both the features of QIDs and sensitive data. In this paper privacy model namely (vi…vj)-diversity is proposed. The proposed anonymization algorithm works for databases containing numerous sensitive QIDs. The real dataset is used for performance evaluation. Our system reduced the information loss for even huge number of attributes and the values of sensitive QID’s are protected.

scholarly journals Global Big Data confirm Remdesivir to be a Recommended Antiviral Drug to Fight COVID-19

2020 ◽  
Vol 55 (4) ◽  
Author(s):  
Maslichah Mafruchati
Keyword(s):  
Data Mining ◽  
Clinical Trials ◽  
Big Data ◽  
Information Search ◽  
Antiviral Drug ◽  
Google Trends ◽  
The Internet ◽  
Relevance Score ◽  
The World ◽  
The Usa

COVID-19 is the latest deadly virus to haunt the world. The virus is so contagious it needs a precise drug for treating patients who contract it. The purpose of this study is to observe trends and relevant points of information about Remdesivir in global big data. This article describes a new method of collecting data, namely data mining from Google trends. The subjects under consideration is how Remdesivir is used in the USA, Russia, and India, as they are the current countries with the most COVID-19-positive cases. This method enabled us to discover how many topics on the internet related to Remdesivir, as well as how strong the relevance of this topic was in those three countries. The results shows that the USA had the biggest relevance score in the information search (8.86 points), but the information trends were quite static. Russia had fluctuating trends but the lowest relevance score. India had a dynamic trend recently and a higher relevance score than Russia. It can be concluded that medical authorities are the cause behind information trends for Remdesivir in these three countries that have approved clinical trials for the use of Remdesivir as a COVID-19 treatment.

scholarly journals Application of K-Means Algorithm to Mapping Poverty Outline by Province in India

2020 ◽  
Vol 8 (6) ◽  
pp. 1045-1049
Keyword(s):  
Data Mining ◽  
Poverty Line ◽  
Line Number ◽  
Process Data ◽  
Class Label ◽  
Data Utilization ◽  
Data Similarity ◽  
New Information ◽  
The World ◽  
Mining Methods

India has a second largest population and seventh largest country in the world, the UN data in 2018 recorded that there were 1,368,681,134 more people scattered throughout the Indian provinces. In addition, India also has a variety of social problems, one of which is poverty. The poverty line number in Indonesia needs to be improved. Data utilization techniques become new information called data mining. One of the most popular data mining methods is clustering using the k-means algorithm. K-means can process data without being notified in advance of the class label. This study will produce three provincial groups according to very low, low and sufficient income figures. Data processing of poverty line numbers in India using the k-means algorithm to get the results of the Davies Bouldin index of 0.271. These results are considered well enough because the closer the results obtained with zeros, the better the data similarity between members of the cluster.

Data Mining for the Internet of Things

2018 ◽  
pp. 181-191 ◽  
Author(s):  
Akhil Rajendra Khare ◽  
Pallavi Shrivasta
Keyword(s):  
Data Mining ◽  
Internet Of Things ◽  
System Optimization ◽  
The Internet ◽  
Mining System ◽  
Data Mining Algorithms ◽  
The World ◽  
Data Mining System ◽  
Mining Algorithms ◽  
The Internet Of Things

The Internet of Things concept arises from the need to manage, automate, and explore all devices, instruments and sensors in the world. In order to make wise decisions both for people and for the things in IoT, data mining technologies are integrated with IoT technologies for decision making support and system optimization. Data mining involves discovering novel, interesting, and potentially useful patterns from data and applying algorithms to the extraction of hidden information. Data mining is classified into three different views: knowledge view, technique view, and application view. The challenges in the data mining algorithms for IoT are discussed and a suggested big data mining system is proposed.

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