Need of Intelligent Search in Dynamic Social Network

Sonkar, Shailendra Kumar; Bhatnagar, Vishal; Challa, Rama Krishna

doi:10.4018/irmj.2015040104

Approaches and Applications of Virtual Reality and Gesture Recognition

Sudha¹,

K²,

S.³

et al.

Virtual and Augmented Reality

0

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Interaction with a computer has been the center of innovation ever since the advent of input devices. From simple punch cards to keyboards, there are number of novel ways of interaction with computers which influence the user experience. Communicating using gestures is perhaps one of the most natural ways of interaction. Gesture recognition as a tool for interpreting signs constitutes a pivotal area in gesture recognition research where accuracy of the algorithm and the ease of usability determine the effectiveness of the algorithm or system. Introducing gesture based interaction in Virtual reality applications has not only helped solve problems which were commonly reported in traditional Virtual Reality systems, but also gives user a more natural and enriching experience. This paper concentrates on comparison of different systems and identifying their similarities, differences, advantages and demerits which can play a key role in designing a system using such technologies.

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Hybrid Ensemble Learning With Feature Selection for Sentiment Classification in Social Media

Sharma

¹

,

Jain

²

2022

Research Anthology on Applying Social Networking Strategies to Classrooms and Libraries

7

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This article presents a study on ensemble learning and an empirical evaluation of various ensemble classifiers and ensemble features for sentiment classification of social media data. The data was collected from Twitter in real-time using Twitter API and text pre-processing and ranking-based feature selection is applied to textual data. A framework for a hybrid ensemble learning model is presented where a combination of ensemble features (Information Gain and CHI-Squared) and ensemble classifier that includes Ada Boost with SMO-SVM and Logistic Regression has been implemented. The classification of Twitter data is performed where sentiment analysis is used as a feature. The proposed model has shown improvements as compared to the state-of-the-art methods with an accuracy of 88.2% with a low error rate.

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Approaches and Applications of Virtual Reality and Gesture Recognition

Sudha¹,

K²,

S³

et al. 2017

International Journal of Ambient Computing and Intelligence

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Interaction with a computer has been the center of innovation ever since the advent of input devices. From simple punch cards to keyboards, there are number of novel ways of interaction with computers which influence the user experience. Communicating using gestures is perhaps one of the most natural ways of interaction. Gesture recognition as a tool for interpreting signs constitutes a pivotal area in gesture recognition research where accuracy of the algorithm and the ease of usability determine the effectiveness of the algorithm or system. Introducing gesture based interaction in Virtual reality applications has not only helped solve problems which were commonly reported in traditional Virtual Reality systems, but also gives user a more natural and enriching experience. This paper concentrates on comparison of different systems and identifying their similarities, differences, advantages and demerits which can play a key role in designing a system using such technologies.

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Need of Intelligent Search in Dynamic Social Network

Cited by 4 publications

References 35 publications

Approaches and Applications of Virtual Reality and Gesture Recognition

Approaches and Applications of Virtual Reality and Gesture Recognition

Hybrid Ensemble Learning With Feature Selection for Sentiment Classification in Social Media

Approaches and Applications of Virtual Reality and Gesture Recognition

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