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The rise of “Big Data ” analytics over unstruc-tured text has led to renewed interest in infor-mation extraction (IE). We surveyed the land-scape of IE technologies and identified a major disconnect between industry and academia: while rule-based IE dominates the commercial world, it is widely regarded as dead-end tech-nology by the academia. We believe the dis-connect stems from the way in which the two communities measure the benefits and costs of IE, as well as academia’s perception that rule-based IE is devoid of research challenges. We make a case for the importance of rule-based IE to industry practitioners. We then lay out a research agenda in advancing the state-of-the-art in rule-based IE systems which we believe has the potential to bridge the gap between academic research and industry practice. 1
Chiticariu et al. (Tue,) studied this question.