Optimizing Research Progress Trajectories with Semantic Power Graphs

Any researcher who is taking up a new research work must explore the works done in the past. For this we propose an idea to track the possible work progresses of a particular research article through semantic based approaches. In addition we analyze the co-citations and cross-citations among research works to avoid leaving out any significant works of the past. Finally we attempt to represent the citation networks and related meta-info using power graphs. This technique reduces the overhead of huge dimensions of citation networks thereby providing optimized trajectory representations which leads to finding significant research progress trajectories.

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