Catchwords refer to popular words or phrases within certain area in certain period of time. In this paper, we propose a novel approach for automatic Chinese catchwords extraction. At the beginning, we discuss the linguistic definition of catchwords and analyze the features of catchwords by manual evaluation. According to those features of catchwords, we define three aspects to describe Popular Degree of catchwords. To extract terms with maximum meaning, we adopt an effective ATE algorithm for multi-character words and long phrases. Then we use conic fitting in Time Series Analysis to build Popular Degree Curves of extracted terms. To calculate Popular Degree Values of catchwords, a formula is proposed which includes values of Popular Trend, Peak Value and Popular Keeping. Finally, a ranking list of catchword candidates is built according to Popular Degree Values. Experiments show that automatic Chinese catchword extraction is effective and objective in comparison with manual evaluation.
Automatic Chinese Catchword Extraction Based on Time Series Analysis
Han Ren | Donghong Ji | Jing Wan | Lei Han
CoNLL 2008: Proceedings of the Twelfth Conference on Computational Natural Language Learning