کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6948408 | 1451039 | 2018 | 14 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A Tabu search heuristic for smoke term curation in safety defect discovery
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
سیستم های اطلاعاتی
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چکیده انگلیسی
The ability to detect and rapidly respond to the presence of safety defects is vital to firms and to regulatory agencies. In this paper, we employ a text mining methodology to generate industry-specific “smoke terms” for identifying these defects in the countertop appliances and over-the-counter medicine industries. Building upon prior work, we propose several methodological improvements to enhance the precision of our industry-specific terms. First, we replace the subjective manual curation of these terms with an automated Tabu search algorithm, which provides a statistically significant improvement over a sample of human-curated lists. Contrary to the assumptions of prior work, we find that shorter, targeted smoke term lists produce superior precision. Second, we incorporate non-textual review features to enhance the performance of these smoke term lists. In total, we find greater than a twofold improvement over typical human-curated lists. As safety surveillance is vital across industries, our method has great potential to assist firms and regulatory agencies in identifying and responding quickly to safety defects.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Decision Support Systems - Volume 105, January 2018, Pages 52-65
Journal: Decision Support Systems - Volume 105, January 2018, Pages 52-65
نویسندگان
David M. Goldberg, Alan S. Abrahams,