Research and Analysis of Improved Extraction Based on Information Processing Technology
Yongqin Wei, Yinjing Guo
Journal of Digital Information Management, Vol. 10, No. 2, 2012.
DOI: 
Link: http://dline.info/fpaper/jdim/v10i2/15.pdf
Abstract:
This paper analyzes the problem of research topics. The key words are extracted from the academic papers published in the key journals based on information processing technology, and these words have the cooccurrence relationship between clustered. Research topics in the academic field analysis applications, researchers can provide a clear outline; in the information retrieval process, you can help clarify the information needs. We will apply the proposed method to ROCLING seminar papers on the data to extract the important field of computational linguistics research topics. The results show that this method can be applied to the special circumstances of domestic academic field, while taking out the key words in English and Chinese. the word has been said that the field of cluster results can also be an important research topic. These results in a preliminary validation of the method proposed in this paper the feasibility. It can also be found that application of computational linguistics research and practice are closely related, taking out many of the words in the cluster and machine translation, speech processing and information retrieval related to the calculation model in the language, grammar patterns and analysis, broken words and statistical language model type is the calculation is the subject of interest to linguists.