Your search for: 'author:("Sarkar, Manash")' has returned 2 results. (0.006s) Save search

Authors: Sarkar, Manash | Banerjee, Soumya

Article Type: Research Article

Abstract: Social network is an exciting online community for sharing the moments, opinion and comments. This tendency of having a unanimous person as a friend or as an acquaintance could be a serious threat to the security aspects of social network and the privacy and confidentiality of information may also become vulnerable. Several techniques are available to measure security and sustain the privacy in the current literature. In this paper, social network is considered as a vector space with multi dimensions and any community within this network is considered as a vector subspace of the social network. A Fuzzy Commitment Vector …is introduced to provide high level privacy using dimension reduction of subspace in the social network. As the results indicate, the Fuzzy Commitment Vector provides a significantly higher level of privacy protection compared to some of the existing techniques cited in the literature. Show more

Keywords: Vector space, vector sub space, hyperspace, fuzzy commitment vector

DOI: 10.3233/IDT-160256

Citation: Intelligent Decision Technologies, vol. 10, no. 3, pp. 285-297, 2016

Authors: Vo, Thanh | Sharma, Rohit | Kumar, Raghvendra | Son, Le Hoang | Pham, Binh Thai | Tien Bui, Dieu | Priyadarshini, Ishaani | Sarkar, Manash | Le, Tuong

Article Type: Research Article

Abstract: Nowadays, the crime rate increases dramatically in every country. Therefore, it is an urgent need for governments and social associations to produce persistent solutions and disincentive penalties to prevent crime issues. Specifically, social media plays an important role in crime rate detection; thus, reducing crime rates significantly. It would be a good medium for the desired task. In this paper, we analyze Twitter data collected from Twitter accounts for seven different locations (Ghaziabad, Chennai, Bangaluru, Chandigarh, Jammu, Gujarat, and Hyderabad) from January 2014 to November 2018 in a case study of India, which is opted to illustrate the efficiency of …the proposed work. Sentiment analysis has been used to analyze users’ behavior and psychology through the tweets of people to track crime actions. Twitter part-of-speech tagger, which is a Markov Model of first-order entropy, has been used for part-of-speech in online conversational text. Brown clustering is used for a long set of unlabeled tweets. Comparisons are verified with real crime rates from an authorized source of information according to different locations. We also measure the latest crime trends for the highest (Ghaziabad, Uttar Pradesh) and lowest crime cities (Jammu) in India. It has been found that the latest crime trends have been recorded for the time duration of 7 days (23, January 2019 to 30, January 2019). The analyses demonstrate that the obtained results match with the real crime rate data. We believe that these types of studies will help to detect the real-time crime rate for different locations and detect the crime pattern easily. Show more

Keywords: Crime detection, Twitter data, social media, sentiment analysis, Brown clustering

DOI: 10.3233/JIFS-190870

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 4, pp. 4287-4299, 2020