Identifying Meaningful Citations & Important Component of Analyzing Big Data - IT Assignment Help

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Tracking citations is an important component of analyzing scholarly big data. Citations provide a quantitative way to measure the quality of published works, to detect emerging research topics, and to follow evolving ones. In this work we argue that not all citations are equal.While some indeed indicate that the cited work is used or, more importantly, extended in the new publication, some are less important, e.g., they discuss the cited work in the context of related work that does not directly impact the new effort. To illustrate this point, Table 1 lists several citationsin increasing order of importance. We further argue that because current citation tracking algorithms do not distinguish between important vs. incidental citations, all of the above applications (e.g., measuring the quality of a publication, or tracking research topics) are negatively affected.To our knowledge, this work is among the first to tacklethe problem of identifying important citations. The contributions of our work are the following:1. We introduce the novel task of identifying important citations, defined as a classification task with either two classes (important vs. non-important citation) or four classes (following the examples in Table 1)

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