Abstract Details
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Activity Number:
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634
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Type:
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Topic Contributed
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Date/Time:
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Thursday, August 7, 2014 : 10:30 AM to 12:20 PM
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Sponsor:
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Government Statistics Section
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Abstract #311518
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View Presentation
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Title:
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Topics in Time: Exploring Trends in Accident Reports Using Document Clustering
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Author(s):
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Wendy Martinez*+
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Companies:
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Bureau of Labor Statistics
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Keywords:
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clustering ;
text analysis ;
unsupervised learning ;
trend analysis
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Abstract:
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Semi-structured or unstructured text fields in government records are often unutilized. In this talk, I explore ways we can analyze text in survey data. In particular, I discuss the ideas behind document clustering (a type of unsupervised learning), where we want to group documents together, such that documents in a group have similar topics. I describe how this analysis can be used as an aid for computer-assisted coding, editing, and verification of survey records. A motivating example using accident reports from the Occupational Safety and Health Administration (OSHA) is presented. I show how we can cluster accident reports at different time intervals, assign topics to the clusters, and use this information to assess accident trends over time.
clustering, text analysis, unsupervised learning, trends
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Authors who are presenting talks have a * after their name.
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