SENTIMENT ANALYSIS USING STRING TOKEN CLASSIFICATION ALGORITHM

Sentiment analysis is a type of data mining which involves computation of opinions, sentiments and to determine if an information or a piece of text conveys positive, negative or neutral opinion. Public opinion regarding various aspects can be found using sentiment analysis. Clustering and classification are the key techniques in sentiment analysis. Consensus clustering is better than existing clustering algorithms as it provides a stable and efficient final result. However, it has its own drawbacks. Instead of performing consensus clustering and selecting classifiers from the consolidated result, we try to develop a new classification algorithm in our wor

SENTIMENT ANALYSIS USING STRING TOKEN CLASSIFICATION ALGORITHM

Sentiment analysis is a type of data mining which involves computation of opinions, sentiments and to determine if an information or a piece of text conveys positive, negative or neutral opinion. Public opinion regarding various aspects can be found using sentiment analysis. Clustering and classification are the key techniques in sentiment analysis. Consensus clustering is better than existing clustering algorithms as it provides a stable and efficient final result. However, it has its own drawbacks. Instead of performing consensus clustering and selecting classifiers from the consolidated result, we try to develop a new classification algorithm in our wor

Hybrid Sentiment Classification of Reviews Using Synonym Lexicon and Word embedding

Sentiment analysis is used in extract some useful information from the given set of documents by using Natural Language Processing (NLP) techniques. These techniques have wide scope in various fields which are dealing with huge amount of data link e-commerce, business and market analysis, social media and review impact of products and movies. Sentiment analysis can be applied over these data for finding the polarity of the data like positive, neutral or negative automatically or many complex sentiments like happiness, sad, anger, joy, etc. for a particular product and services based on user reviews. Sentiment analysis not only able to find the polarity of the reviews. Sentiment analysis utilizes machine learning algorithms with vectorization techniques based on textual documents to train the classifier models. These models are later used to perform sentiment analysis on the given dataset of particular domain on which the classifier model is trained. Vectorization is done for text document by using word embedding based and hybrid vectorization. The proposed methodology focus on fast and accurate sentiment prediction with higher confidence value over the dataset in both Tamil and English

A Modified Polybius Square Based Approach for Enhancing Data Security

Digital communication is the prominent technique used by various organizations for information exchange. It replaces the traditional methods with the help of internet and its related technologies. There is a chance to retrieve the contents of the transmitted message from the unsecure communication medium. The biggest challenge is to deploy a suitable mechanism for secure communication. Cryptography plays a dominant role in the information security domain. This paper proposes a modified Polybius square based approach for efficient key generation. New key is obtained from the original key by performing three different operations on modified Polybius square namely Square ring rotation, Square reversal and Transpose. From the security analysis it can be inferred that the proposed approach generates an efficient key

A Modified Polybius Square Based Approach for Enhancing Data Security

Digital communication is the prominent technique used by various organizations for information exchange. It replaces the traditional methods with the help of internet and its related technologies. There is a chance to retrieve the contents of the transmitted message from the unsecure communication medium. The biggest challenge is to deploy a suitable mechanism for secure communication. Cryptography plays a dominant role in the information security domain. This paper proposes a modified Polybius square based approach for efficient key generation. New key is obtained from the original key by performing three different operations on modified Polybius square namely Square ring rotation, Square reversal and Transpose. From the security analysis it can be inferred that the proposed approach generates an efficient key

Knowledge Modelling and Learning through Cognitive Networks

One of the most promising developments in modelling knowledge is cognitive network science, which aims to investigate cognitive phenomena driven by the networked, associative organization of knowledge. For example, investigating the structure of semantic memory via semantic networks has illuminated how memory recall patterns influence phenomena such as creativity, memory search, learning, and more generally, knowledge acquisition, exploration, and exploitation. In parallel, neural network models for artificial intelligence (AI) are also becoming more widespread as inferential models for understanding which features drive language-related phenomena such as meaning reconstruction, stance detection, and emotional profiling. Whereas cognitive networks map explicitly which entities engage in associative relationships, neural networks perform an implicit mapping of correlations in cognitive data as weights, obtained after training over labelled data and whose interpretation is not immediately evident to the experimenter. This book aims to bring together quantitative, innovative research that focuses on modelling knowledge through cognitive and neural networks to gain insight into mechanisms driving cognitive processes related to knowledge structuring, exploration, and learning. The book comprises a variety of publication types, including reviews and theoretical papers, empirical research, computational modelling, and big data analysis. All papers here share a commonality: they demonstrate how the application of network science and AI can extend and broaden cognitive science in ways that traditional approaches cannot

A Hybrid Technique for Enhancing Data Security

The worldwide information and technology has an astounding dependency o n data s e c u r i t y . The r i s k fabricated by the interloper has been a maelstrom for forthcoming specialists. Security pl ay s an essential role in governing the data transfer. The primary objective of this paper is to propose a black box approach which generates a modified plain text from the original message. For this purpose, we have used techniques like Perturbation, Swapping and Shifting which will modify the original plain text. Before giving the plain text directly into encryption process, the m o d i f i e d plain text obtained f r o m above techniques will be given as an input. The complexity of breaking the plain text is increased by applying the above techniques. For experimental purpose, w e use AES algorithm for encryption and d e c r y p t i o n and Java is used for implementing t h e proposed a p p r o a c h . © 2018 Academic Press. All Rights Reserved

An Enhanced Least Significant Bit Steganography to Improve the Effectiveness of Graphical Password Authentication

Authentication means acknowledging a user’s identity. It is the way of associating a request with a set of identity. The identification provided is an authorized user’s information on a personal computer system or within an authentication server. A graphical password is a validation system in which user has to select from images, in a particular order, presented in a graphical user + interface (GUI). Graphical passwords can be easily remembered, as users remember images better than words. Also, the system should be more unaffected by brute-force attacks, because there is practically an infinite search space. Complex text passwords are hard to remember and simple textual passwords are easy to guess. Graphical passwords provide more robustness and memorability. It is a secure mechanism to provide authenticated sign up to a system

Reversible Data Hiding scheme using modified Histogram Shifting in Encrypted Images for Bio-medical images

Existing Least Significant Bit (LSB) steganography system is less robust and the stego-images can be corrupted easily by attackers. To overcome these problems Reversible data hiding (RDH) techniques are used. RDH is an efficient way of embedding confidential message into a cover image. Histogram expansion and histogram shifting are effective techniques in reversible data hiding. The embedded message and cover images can be extracted without any distortion. The proposed system focuses on implementation of RDH techniques for hiding data in encrypted bio-medical images without any loss. In the proposed techniques the bio-medical data are embedded into cover images by reversible data hiding technique. Histogram expansion and histogram shifting have been used to extract cover image and bio- medical data. Each pixel is encrypted by public key of Paillier cryptosystem algorithm. The homomorphic multiplication is used to expand the histogram of the image in encrypted domain. The histogram shifting is done based on the homomorphic addition and adjacent pixel difference in the encrypted domain. The message is embedded into the host image pixel difference. On receiving encrypted image with additional data, the receiver using his private key performs decryption. As a result, due to histogram expansion and histogram shifting embedded message and the host image can be recovered perfectly. The embedding rate is increased in host image than in existing scheme due to adjacency pixel difference

A Hybrid Technique for Enhancing Data Security

The worldwide information and technology has an astounding dependency o n data s e c u r i t y . The r i s k fabricated by the interloper has been a maelstrom for forthcoming specialists. Security pl ay s an essential role in governing the data transfer. The primary objective of this paper is to propose a black box approach which generates a modified plain text from the original message. For this purpose, we have used techniques like Perturbation, Swapping and Shifting which will modify the original plain text. Before giving the plain text directly into encryption process, the m o d i f i e d plain text obtained f r o m above techniques will be given as an input. The complexity of breaking the plain text is increased by applying the above techniques. For experimental purpose, w e use AES algorithm for encryption and d e c r y p t i o n and Java is used for implementing t h e proposed a p p r o a c h . © 2018 Academic Press. All Rights Reserved