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In this paper I will be reviewing and evaluating the work of Zhiyuan Chen and Bing Liu of the University of Chicago, entitled _Mining Topics in Documents: Standing on the Shoulders of Big Data_, presented at the 2014 Conference of Knowledge Discovery and Data Mining. After a brief summary of the paper and its findings, I present the author's background and related previous work - to find that they have pioneered transfer-learning models for topic mining. Subsequenlty I conduct a brief overview of related work and possible improvements, followed by my personal reflections and suggested future work pathways. I finish with a brief conclusion.