2021 5th International Conference on Computing Methodologies and Communication (ICCMC)最新文献_第3页

Swindle: Predicting the Probability of Loan Defaults using CatBoost Algorithm 诈骗:使用CatBoost算法预测贷款违约的概率

2021 5th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2021-04-08 DOI: 10.1109/ICCMC51019.2021.9418277

Sujoy Barua, Divya Gavandi, P. Sangle, Leena Shinde, J. Ramteke

引用次数: 3

Data Preprocessing based Connecting Suicidal and Help-Seeking Behaviours 基于连接自杀和求助行为的数据预处理

2021 5th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2021-04-08 DOI: 10.1109/ICCMC51019.2021.9418452

A. Mittal, A. Goyal, Mohit Mittal

{"title":"Data Preprocessing based Connecting Suicidal and Help-Seeking Behaviours","authors":"A. Mittal, A. Goyal, Mohit Mittal","doi":"10.1109/ICCMC51019.2021.9418452","DOIUrl":"https://doi.org/10.1109/ICCMC51019.2021.9418452","url":null,"abstract":"Everyone knows that although there are so many researchers and suicide prevention teams that are active out there to help individuals with mental health problems, many cases of suicide are not able to be detected. Social media acts as a platform for users to express their views online on the internet. How can we help such suicide prevention teams using social media to identify people where there is a possibility that they may develop suicidal ideation thoughts? The main goal of this project is to identify those people from social media who may have suicidal thoughts or may develop suicidal thoughts after some time. We are using the Reddit dataset to find the people who may have had thoughts about suicide before and those people who have other problems like depression or anxiety and express their views by posting in subreddits. We all know that any machine learning algorithm of any classification algorithm cannot work well on a completely raw dataset. So, our next step is doing the preprocessing of the data to extract the data that is relevant for us out of the user's posts for our classification algorithms. Then after that, we will perform the support vector machine (SVM) algorithm to classify the users based on their subreddits that they have posted.","PeriodicalId":131747,"journal":{"name":"2021 5th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"232 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124557105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Performance Metric System for Malicious URL Data using Revised Random Forest Algorithm 基于改进随机森林算法的恶意URL数据性能度量系统

2021 5th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2021-04-08 DOI: 10.1109/ICCMC51019.2021.9418480

K. Ramesh, M. Bennet, J. Veerappan, P. Renjith

{"title":"Performance Metric System for Malicious URL Data using Revised Random Forest Algorithm","authors":"K. Ramesh, M. Bennet, J. Veerappan, P. Renjith","doi":"10.1109/ICCMC51019.2021.9418480","DOIUrl":"https://doi.org/10.1109/ICCMC51019.2021.9418480","url":null,"abstract":"Phishing alludes to drawing techniques utilized by character cheats to angle for individual data in a lake of clueless Internet clients. Phishers use ridiculed email, phishing programming to take Phishing costs, Internet clients, billions of dollars for every year. It alludes to attracting techniques utilized by character cheats to angle for individual data in a lake of clueless Internet clients. Phishers use satirize email, phishing programming to take budgetary record subtleties, and individual data, for example, usernames and passwords. This paper manages techniques for distinguishing phishing Web destinations by investigating different highlights of benevolent and phishing URLs by Machine learning calculations. We talk about the techniques utilized for the recognition of phishing Web locales dependent on have properties, axical highlights, and page significance properties. the Proposed model has been assessed utilizing five distinctive AI calculations provided the best performance and results. The tests were led with a few (angled and symmetrical) random forest (RF) method used to classy the data for site acknowledgment","PeriodicalId":131747,"journal":{"name":"2021 5th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124627078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Comparative Study of Different Image Captioning Models 不同图像字幕模型的比较研究

2021 5th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2021-04-08 DOI: 10.1109/ICCMC51019.2021.9418451

Sahil Takkar, Anshul Jain, Piyush Adlakha

引用次数: 5

Context-based News Articles Retrieval using CLSM 使用CLSM进行基于上下文的新闻文章检索

2021 5th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2021-04-08 DOI: 10.1109/ICCMC51019.2021.9418018

Komala Anamalamudi, Y. Padmanabha Reddy

引用次数: 0

Comparative study of Twitter Sentiment On COVID - 19 Tweets COVID - 19推特情绪的比较研究

2021 5th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2021-04-08 DOI: 10.1109/ICCMC51019.2021.9418320

Anupama J Nair, V. G, Aadithya Vinayak

{"title":"Comparative study of Twitter Sentiment On COVID - 19 Tweets","authors":"Anupama J Nair, V. G, Aadithya Vinayak","doi":"10.1109/ICCMC51019.2021.9418320","DOIUrl":"https://doi.org/10.1109/ICCMC51019.2021.9418320","url":null,"abstract":"Recently, the number of tweets on COVID-19 are increasing at an unprecedented rate by including positive, negative and neutral tweets. This diversified nature of tweets has attracted the researchers to perform sentiment analysis and analyze the varied emotions of a large public towards COVID-19. The traditional sentiment analysis techniques will only find out the polarity and classify it as either positive, negative or neutral tweets. As an advanced step, the proposed research work attempts to find the sentiment of tweets using Logistic Regression sentiment analysis, VADER sentiment analysis and BERT sentiment analysis. The proposed analysis methods are more sensitive to sentiment expressions in social media contexts, while it can be generalized on the basis of the domain. Even though 3 different algorithms are implemented, all the preprocessing and further steps excluding the sentiment analysis algorithm will remain identical. The identical processing steps will help to compare the proposed three different sentiment analysis algorithms. Furthermore, there are many useful applications with this proposed analysis, as this work obtains a public opinion for the government officials or even for the health officials and help them to work on the basis of the obtained results.","PeriodicalId":131747,"journal":{"name":"2021 5th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123479523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 25

FPGA Architecture To Enhance Hardware Acceleration for Machine Learning Applications FPGA架构增强机器学习应用的硬件加速

2021 5th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2021-04-08 DOI: 10.1109/ICCMC51019.2021.9418015

Anirudh Itagi, S. Krishvadana, K. Bharath, M. Rajesh Kumar

引用次数: 2

Crop Recommender System Using Machine Learning Approach 使用机器学习方法的作物推荐系统

2021 5th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2021-04-08 DOI: 10.1109/ICCMC51019.2021.9418351

S. Pande, Prem Kumar Ramesh, Anmol Anmol, B. Aishwarya, Karuna Rohilla, Kumar Shaurya

{"title":"Crop Recommender System Using Machine Learning Approach","authors":"S. Pande, Prem Kumar Ramesh, Anmol Anmol, B. Aishwarya, Karuna Rohilla, Kumar Shaurya","doi":"10.1109/ICCMC51019.2021.9418351","DOIUrl":"https://doi.org/10.1109/ICCMC51019.2021.9418351","url":null,"abstract":"Agriculture and its allied sectors are undoubtedly the largest providers of livelihoods in rural India. The agriculture sector is also a significant contributor factor to the country’s Gross Domestic Product (GDP). Blessing to the country is the overwhelming size of the agricultural sector. However, regrettable is the yield per hectare of crops in comparison to international standards. This is one of the possible causes for a higher suicide rate among marginal farmers in India. This paper proposes a viable and user-friendly yield prediction system for the farmers. The proposed system provides connectivity to farmers via a mobile application. GPS helps to identify the user location. The user provides the area & soil type as input. Machine learning algorithms allow choosing the most profitable crop list or predicting the crop yield for a user-selected crop. To predict the crop yield, selected Machine Learning algorithms such as Support Vector Machine (SVM), Artificial Neural Network (ANN), Random Forest (RF), Multivariate Linear Regression (MLR), and K-Nearest Neighbour (KNN) are used. Among them, the Random Forest showed the best results with 95% accuracy. Additionally, the system also suggests the best time to use the fertilizers to boost up the yield.","PeriodicalId":131747,"journal":{"name":"2021 5th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121658218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 36

Communication Mode of Computer Cluster Network in Cloud Environment based on Neural Computing 基于神经计算的云环境下计算机集群网络通信模式

2021 5th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2021-04-08 DOI: 10.1109/ICCMC51019.2021.9418350

Weijie Zhang, Kaitai Xiao

引用次数: 0

CNN based Covid-aid: Covid 19 Detection using Chest X-ray CNN的covidaid:使用胸部x射线检测Covid- 19

2021 5th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2021-04-08 DOI: 10.1109/ICCMC51019.2021.9418407

Shrinjal Singh, Piyush Sapra, Aman Garg, D. Vishwakarma

引用次数: 11