Finding the lineage of a research topic is crucial for understanding the prior state of the art and advancing scientific displacement. The deluge of scholarly articles makes it difficult to locate the most relevant previous work. It causes researchers to spend a considerable amount of time building up their literature list. Citations play a crucial role in discovering relevant literature. However, not all citations are created equal. The majority of the citations that a paper receives provide contextual and background information to the citing papers. In those cases, the cited paper is not central to the theme of citing papers. However, some papers build upon a given paper and further the research frontier. In those cases, the concerned cited paper plays a pivotal role in the citing paper. Hence, the nature of the citation that the former receives from the latter is significant . In this work, we discuss our investigations towards discovering significant citations of a given paper. We further show how we can leverage significant citations to build a research lineage via a significant citation graph . We demonstrate the efficacy of our idea with two real-life case studies. Our experiments yield promising results with respect to the current state of the art in classifying significant citations , outperforming the earlier ones by a relative margin of 20 points in terms of precision. We hypothesize that such an automated system can facilitate relevant literature discovery and help identify knowledge flow for a particular category of papers.