Kumar Shubhankar

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In this paper we propose an efficient method to rank the research papers from various fields of research published in various conferences over the years. This ranking method is based on citation network. The importance of a research paper is captured well by the peer vote, which in this case is the research paper being cited in other research papers. Using(More)
In this paper we introduce a novel and efficient approach to detect and rank topics in a large corpus of research papers. With rapidly growing size of academic literature, the problem of topic detection and topic ranking has become a challenging task. We present a unique approach that uses closed frequent keywordset to form topics. We devise a modified time(More)
The world of academia is growing at a tremendous rate with thousands of research papers being published every year. For a researcher looking for new dimensions of research, it is becoming an increasingly difficult task to identify the relevant yet novel domains of research from amongst the host of varied domains. There is a definite need of a system that(More)
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