A system to recognize the citation intent of a given passage in a scholarly article and retrieve relevant citation targets from a given database.
For centuries, a key to the remarkable technological progress in our society has been the unassailable integrity exhibited by scientists in conducting scholarly communications. New discoveries and theories are openly distributed and discussed in published articles, and impactful contributions are often recognized by the research community at large in the form of citations. However, with the competition for research funding or promotions getting ever fiercer, unscrupulous behaviors intended at “gaming the system” rather than advancing the frontiers of our knowledge have become regrettably prevalent. Known as “coercive citations”, journal editors are seen to force authors to cite marginally relevant articles in particular journals to boost their journal impact factors, so are paper reviewers to solely increase their citation counts or h-index. These conducts are an affront to the highest integrity demanded of any scientists and technologists and, left unchecked, can undermine the public trusts and hamper the future developments in science and technology. This contest is the first in a series that explores the extent to which the web search and data mining technologies can be employed to distinguish superfluous citations from genuine recognitions. In this contest, however, we are focusing on a necessary first step in which the citation intents of the authors are recognized: the contestant is asked to develop a system that can recognize the citation intent of a given passage in a scholarly article and retrieve relevant citation targets from a given database.