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Papers by Akanksha Dhamija

Research paper thumbnail of A Novel Approach towards Movie Recommender System using Deep Learning Techniques

International Journal of Computing and Digital Systems, Sep 30, 2022

Recommender systems have become a key technology to help the users in interacting with the increa... more Recommender systems have become a key technology to help the users in interacting with the increasingly larger data and information available online. The rapid advancements in Deep Learning techniques have been very useful in recommendation systems as it enhances the overall performance and accuracy of the recommendation systems. This paper attempts to work on a hybrid recommendation model by considering a weighted average of top N recommendations from both content based and collaborative based filtering methods and hence eliminating their individual shortcomings. A LightFM module has been also used to evaluate the loss functions on this hybrid model and to capture the latent features about attributes of users and items. Thereafter, a class of two-layer undirected graphical models, called Restricted Boltzmann Machine (RBM) and Auto-encoder is successfully applied to the Movielens data set to provide the accurate recommendations. This study shows that the proposed approach outperform the traditional recommender systems in terms of accuracy.

Research paper thumbnail of A Framework for Virtual Reality in Healthcare

CRC Press eBooks, Apr 26, 2023

Research paper thumbnail of A Novel Approach towards Movie Recommender System using Deep Learning Techniques

International Journal of Computing and Digital Systems

Recommender systems have become a key technology to help the users in interacting with the increa... more Recommender systems have become a key technology to help the users in interacting with the increasingly larger data and information available online. The rapid advancements in Deep Learning techniques have been very useful in recommendation systems as it enhances the overall performance and accuracy of the recommendation systems. This paper attempts to work on a hybrid recommendation model by considering a weighted average of top N recommendations from both content based and collaborative based filtering methods and hence eliminating their individual shortcomings. A LightFM module has been also used to evaluate the loss functions on this hybrid model and to capture the latent features about attributes of users and items. Thereafter, a class of two-layer undirected graphical models, called Restricted Boltzmann Machine (RBM) and Auto-encoder is successfully applied to the Movielens data set to provide the accurate recommendations. This study shows that the proposed approach outperform the traditional recommender systems in terms of accuracy.

Research paper thumbnail of Unmasking the Malware Using Android Debug Bridge

Lecture notes in networks and systems, Aug 30, 2022

Research paper thumbnail of Natural Selection Simulator using Machine Learning

2022 Fifth International Conference on Computational Intelligence and Communication Technologies (CCICT)

Research paper thumbnail of Time Series Prediction for Stock Market Analysis

Advances in Systems Analysis, Software Engineering, and High Performance Computing

The stock market is an ideal way to invest money and earn potential returns. But, even with advan... more The stock market is an ideal way to invest money and earn potential returns. But, even with advanced technology and computational power, this chapter still cannot predict the patterns of rise and fall in the stock market, and still, it is considered a risky business. To ease the process of investment and to provide better consciousness, this chapter proposes the prediction of stock market deviation using the ARIMA (auto-regressive integrated moving average) algorithm and long short-term memory (LSTM) algorithm. This chapter is using an algorithm which is trying to predict the future pattern for any stock based on the real-time analysis and data provided from Yahoo Finance data. The software provides pictorial and graphical representations. The objective is to provide short-term and long-term prediction competence to prepare for future potential investments.

Research paper thumbnail of Discerning Spam in Social Networking Sites

Advances in Vision Computing: An International Journal, 2016

Research paper thumbnail of EHminor

Trojan, is any malicious computer program which is used to hack into a computer by misleading use... more Trojan, is any malicious computer program which is used to hack into a computer by misleading users of its true intent.Trojans can be employed by cyber-thieves and hackers trying to gain access to users' systems. Users are typically tricked by some form of social engineering into loading and executing Trojans on their systems. If installed or run with elevated privileges a Trojan will generally have unlimited access. What it does with this power depends on the motives of the attacker.

Research paper thumbnail of A Novel Approach towards Movie Recommender System using Deep Learning Techniques

International Journal of Computing and Digital Systems, Sep 30, 2022

Recommender systems have become a key technology to help the users in interacting with the increa... more Recommender systems have become a key technology to help the users in interacting with the increasingly larger data and information available online. The rapid advancements in Deep Learning techniques have been very useful in recommendation systems as it enhances the overall performance and accuracy of the recommendation systems. This paper attempts to work on a hybrid recommendation model by considering a weighted average of top N recommendations from both content based and collaborative based filtering methods and hence eliminating their individual shortcomings. A LightFM module has been also used to evaluate the loss functions on this hybrid model and to capture the latent features about attributes of users and items. Thereafter, a class of two-layer undirected graphical models, called Restricted Boltzmann Machine (RBM) and Auto-encoder is successfully applied to the Movielens data set to provide the accurate recommendations. This study shows that the proposed approach outperform the traditional recommender systems in terms of accuracy.

Research paper thumbnail of A Framework for Virtual Reality in Healthcare

CRC Press eBooks, Apr 26, 2023

Research paper thumbnail of A Novel Approach towards Movie Recommender System using Deep Learning Techniques

International Journal of Computing and Digital Systems

Recommender systems have become a key technology to help the users in interacting with the increa... more Recommender systems have become a key technology to help the users in interacting with the increasingly larger data and information available online. The rapid advancements in Deep Learning techniques have been very useful in recommendation systems as it enhances the overall performance and accuracy of the recommendation systems. This paper attempts to work on a hybrid recommendation model by considering a weighted average of top N recommendations from both content based and collaborative based filtering methods and hence eliminating their individual shortcomings. A LightFM module has been also used to evaluate the loss functions on this hybrid model and to capture the latent features about attributes of users and items. Thereafter, a class of two-layer undirected graphical models, called Restricted Boltzmann Machine (RBM) and Auto-encoder is successfully applied to the Movielens data set to provide the accurate recommendations. This study shows that the proposed approach outperform the traditional recommender systems in terms of accuracy.

Research paper thumbnail of Unmasking the Malware Using Android Debug Bridge

Lecture notes in networks and systems, Aug 30, 2022

Research paper thumbnail of Natural Selection Simulator using Machine Learning

2022 Fifth International Conference on Computational Intelligence and Communication Technologies (CCICT)

Research paper thumbnail of Time Series Prediction for Stock Market Analysis

Advances in Systems Analysis, Software Engineering, and High Performance Computing

The stock market is an ideal way to invest money and earn potential returns. But, even with advan... more The stock market is an ideal way to invest money and earn potential returns. But, even with advanced technology and computational power, this chapter still cannot predict the patterns of rise and fall in the stock market, and still, it is considered a risky business. To ease the process of investment and to provide better consciousness, this chapter proposes the prediction of stock market deviation using the ARIMA (auto-regressive integrated moving average) algorithm and long short-term memory (LSTM) algorithm. This chapter is using an algorithm which is trying to predict the future pattern for any stock based on the real-time analysis and data provided from Yahoo Finance data. The software provides pictorial and graphical representations. The objective is to provide short-term and long-term prediction competence to prepare for future potential investments.

Research paper thumbnail of Discerning Spam in Social Networking Sites

Advances in Vision Computing: An International Journal, 2016

Research paper thumbnail of EHminor

Trojan, is any malicious computer program which is used to hack into a computer by misleading use... more Trojan, is any malicious computer program which is used to hack into a computer by misleading users of its true intent.Trojans can be employed by cyber-thieves and hackers trying to gain access to users' systems. Users are typically tricked by some form of social engineering into loading and executing Trojans on their systems. If installed or run with elevated privileges a Trojan will generally have unlimited access. What it does with this power depends on the motives of the attacker.