A Novel Business Cycle Surveillance System Using the Query Logs of Search Engines
Date Issued
2011
Date
2011
Author(s)
Tsai, Yi-Tien
Abstract
Business indices and indicators are used to monitor the regime shifts of business cycles. Generally, the indices and indicators are comprised of various economic variables that are compiled by different government departments. The compilation of the variables involves a great deal of data processing operation, which delays the monitoring of business cycles. In this paper, we propose a novel business cycle surveillance system that utilizes the query logs of search engines for business cycle modeling. The system employs an effective feature selection and pruning technique to identify query terms that are representative of business cycles. The selected terms and the frequency count of queries associated with the terms are then integrated to classify the status of business cycles. We use data discretization techniques to reduce the sparseness of query frequencies.
Experimental results based on a five-year dataset show that the proposed system can classify the status of business cycles accurately, and the selected query terms reveal interesting human behavior patterns in different business cycles. Unlike economic variables, query logs are readily available through online Web services, so our system can provide business cycle information in a timely manner.
Subjects
Business Intelligence
Feature Selection
Classification
Type
thesis
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