%A Xu Deshan, Li Hui, Zhang Yunliang %T A Method of Keywords Annotation Based on Linked Triples %0 Journal Article %D 2015 %J Data Analysis and Knowledge Discovery %R 10.11925/infotech.1003-3513.2015.09.05 %P 31-37 %V 31 %N 9 %U {https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/abstract/article_4126.shtml} %8 2015-09-25 %X

[Objective] Build an auto-indexing system by triple acquirement and NLP for Chinese scientific and technical literatures based on Ontology management and service platform. [Methods] Merging Ontology knowledge bases and vocabularies by Web services, the system can identify the terms and unlisted words through matching vocabulary and words combination, as well as link them with the triples in the knowledge bases for building a conceptual relational network. [Results] This system can process 86 articles per second with recall rate of 65% and precision rate of 69%. [Limitations] It takes a lot of time to match terms because no index is built. The performance of Chinese word segmentation and POS tagging are influenced by the noise data such as spaces, line break, and so on. [Conclusions] Data cleaning process and algorithm optimization of keywords selecting need continuous study for supporting the deep mining and enhancing the efficiency of the system.