Paper: Efficient Statement Identification for Automatic Market Forecasting

ACL ID C10-1127
Title Efficient Statement Identification for Automatic Market Forecasting
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2010
Authors

Strategic business decision making in- volves the analysis of market forecasts. Today, the identification and aggregation of relevant market statements is done by human experts, often by analyzing doc- uments from the World Wide Web. We present an efficient information extrac- tion chain to automate this complex nat- ural language processing task and show results for the identification part. Based on time and money extraction, we iden- tify sentences that represent statements on revenue using support vector classifica- tion. We provide a corpus with German online news articles, in which more than 2,000 such sentences are annotated by do- main experts from the industry. On the test data, our statement identification al- gorithm achieves an overall precision and recall of 0.86 and 0.87 respe...