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The amount of data from users in Hindi language is tremendously increasing on social media, blogs, online forums due to which Sentiment analysis of Indian languages has turned out to be a predominant research area. Lexicon based analysis is one of the techniques that can be used for analyzing sentiments. While using the lexicon-based sentiment analysis, ambiguous words could be an issue. This paper proposes a graph based Lesk approach to handle the word sense disambiguation issue and tries to enhance and improve the lexicon approach. Experiments performed to evaluate the performance of the proposed algorithm shows that the performance of lexicon-based sentiment analysis is increased significantly by using the graph based Lesk approach.

Sentiment Analysis (SA) has been a core interest in the field of text mining research, dealing with computational processing of sentiments, views, and subjective nature of the text. Due to the availability of extensive web-based data in Indian languages such as Hindi, Marathi, Kannada, Tamil, and so on. It has become extremely significant to analyze this data and recover valuable and relevant information. Hindi being the first language of the majority of the population in India, SA in Hindi has turned out to be a critical task particularly for companies and government organizations. This research portrays a systematic review specifically in the field of Hindi SA. The major contribution of this article includes the categorization of numerous articles based on techniques that have attracted researchers in performing SA tasks in Hindi language. This survey classifies these state-of-the-art computational intelligence techniques into four major categories namely lexicon-based techniques, machine learning techniques, deep learning techniques, and hybrid techniques. It discusses the importance of these techniques based on different aspects such as their impact on the issues of SA, levels of analysis, and performance evaluation measures. The research puts forward a comprehensive overview of the majority of the work done in Hindi SA. This study will help researchers in finding out resources such as annotated datasets, linguistic resources, and lexical resources. This survey delivers some significant findings and presents overall future research directions in the field of Hindi SA.

With the proliferation of mobile devices and wireless technologies, mobile social network systems used more. A mobile social network has important role in social network. The Process of finding influential nodes is NP-hard. Greedy rule with demonstrable approximation guarantees will provide smart approximation. A divide-and-conquer method with parallel computing mechanism has been used. Communitybased Greedy rule for mining top-K influential nodes is used first. It has two parts: dividing the large-scale mobile social network into many communities by taking under consideration data diffusion. Communities select influential nodes by a dynamic programming. Performance is to be increased by considering the influence propagation supported communities and take into account the influence propagation crossing communities. Experiments on real large-scale mobile social networks show that the proposed algorithm is quicker than previous algorithms. General TermsMobile social network, influence maximization, PCA greedy algorithm,

Data deduplication is one of the most important Data compression techniques used for to removing the duplicate copies of repeating data and it is widely used in the cloud storage for the purpose of reduce the storage space and save bandwidth. To keep the confidentiality of sensitive data while supporting the deduplication, to encrypt the data before outsourcing convergent encryption technique has been proposed .To better protect data security, this project makes the first attempt to formally address the problem of authorized data deduplication .Different from the traditional deduplication system, differential benefits of the user are further considered the duplicate check besides the data itself. Hybrid cloud architecture contains several new deduplication constructions supporting authorized duplicate check. The proposed security models contain the demonstration of security analysis scheme. As a proof of concept, contains the implementation framework of proposed authorized duplicate check scheme and conduct testbed experiments using these prototype. In proposed system contain authorized duplicate check scheme incurs minimal overhead compared to normal operations.