Search

Your search keyword '"Mangat, Veenu"' showing total 96 results
Start Over Author "Mangat, Veenu"
96 results on '"Mangat, Veenu"'

2. Spatio-Temporal Dataset with Other Multisensory Collected Data of Human Mobility

Author

Angmo, Rigzin, Mangat, Veenu, Aggarwal, Naveen, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Choudrie, Jyoti, editor, Mahalle, Parikshit N., editor, Perumal, Thinagaran, editor, and Joshi, Amit, editor

Published
2023
Full Text
View/download PDF

9. Analytical Modeling of Real-World Social Network Parameters

Author

Monika, Mangat, Veenu, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Ranganathan, G., editor, Chen, Joy, editor, and Rocha, Álvaro, editor

Published
2021
Full Text
View/download PDF

10. Hybrid Deep Neural Architecture for Detection of DDoS Attacks in Cloud Computing

Author

Bhardwaj, Aanshi, Mangat, Veenu, Vig, Renu, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Paprzycki, Marcin, editor, Thampi, Sabu M., editor, Mitra, Sushmita, editor, Trajkovic, Ljiljana, editor, and El-Alfy, El-Sayed M., editor

Published
2021
Full Text
View/download PDF

11. A Study of Efficient Methods for Selecting Quasi-identifier for Privacy-Preserving Data Mining

Author

Angmo, Rigzin, Mangat, Veenu, Aggarwal, Naveen, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Singh, Vijendra, editor, Asari, Vijayan K., editor, Kumar, Sanjay, editor, and Patel, R. B., editor

Published
2021
Full Text
View/download PDF

14. Pragmatic Analysis of Machine Learning Techniques in Network Based IDS

Author

Nehra, Divya, Kumar, Krishan, Mangat, Veenu, Barbosa, Simone Diniz Junqueira, Editorial Board Member, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Kotenko, Igor, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Yuan, Junsong, Founding Editor, Luhach, Ashish Kumar, editor, Jat, Dharm Singh, editor, Hawari, Kamarul Bin Ghazali, editor, Gao, Xiao-Zhi, editor, and Lingras, Pawan, editor

Published
2019
Full Text
View/download PDF

18. Improved Accuracy of PSO and DE using Normalization: an Application to Stock Price Prediction

Author

Kaur, Savinderjit and Mangat, Veenu

Subjects
Computer Science - Neural and Evolutionary Computing, Computer Science - Learning
Abstract

Data Mining is being actively applied to stock market since 1980s. It has been used to predict stock prices, stock indexes, for portfolio management, trend detection and for developing recommender systems. The various algorithms which have been used for the same include ANN, SVM, ARIMA, GARCH etc. Different hybrid models have been developed by combining these algorithms with other algorithms like roughest, fuzzy logic, GA, PSO, DE, ACO etc. to improve the efficiency. This paper proposes DE-SVM model (Differential EvolutionSupport vector Machine) for stock price prediction. DE has been used to select best free parameters combination for SVM to improve results. The paper also compares the results of prediction with the outputs of SVM alone and PSO-SVM model (Particle Swarm Optimization). The effect of normalization of data on the accuracy of prediction has also been studied.

Published
2013

23. Modelling information flow in social networks: Metrics and evaluation.

Author

Saini, Monika and Mangat, Veenu

Subjects
*SOCIAL networks, *SOCIAL network analysis, *DATA visualization
Abstract

Social network analysis is a key concept in analyzing the pattern of communication between various individuals in a social network. Various traditional metrics like centrality measures are used in literature to examine the interactions between various nodes. In this paper main aim of our analysis is to quantify the influential property of a nodeas well as path followed for information flow from one node to another node. To achieve this purpose statistical analysis and visualization is performed with the help of experimental setup and social network visualization tools. [ABSTRACT FROM AUTHOR]

Published
2023
Full Text
View/download PDF

27. Survey on Particle Swarm Optimization Based Clustering Analysis

Author

Mangat, Veenu, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Rutkowski, Leszek, editor, Korytkowski, Marcin, editor, Scherer, Rafał, editor, Tadeusiewicz, Ryszard, editor, Zadeh, Lotfi A., editor, and Zurada, Jacek M., editor

Published
2012
Full Text
View/download PDF

49. Dictionary based Sentiment Analysis of Hinglish text.

Author

kaur, Harpreet, Mangat, Veenu, and Nidhi

Subjects
SENTIMENT analysis, SOCIAL media, TEXT mining, ONLINE data processing, BLOGS
Abstract

Sentiment analysis is a popular field of research in text mining. It involves extracting opinions from text such as reviews, news data, blog data etc. and then classifying them into positive, negative or neutral sentiments. Sentiment analysis of English has been explored but not much work has been done for Indian language. Some research has been carried in Hindi, Bengali, Marathi and Punjabi languages. Nowadays, a lot of communication in social media happens using Hinglish text which is a combination of two languages Hindi and English. Hinglish is a colloquial language which is very popular in India as people feel more comfortable speaking in their own language. This paper provides a survey of recent work done in the Hindi language along with a new proposed approach for sentiment analysis of Hinglish (Hindi + English) text. [ABSTRACT FROM AUTHOR]

Published
2017

Catalog

Books, media, physical & digital resources
See catalog results