ITM Web Conf.
Volume 12, 2017The 4th Annual International Conference on Information Technology and Applications (ITA 2017)
|Number of page(s)||5|
|Section||Session 5: Information Processing Methods and Techniques|
|Published online||05 September 2017|
- V. I. Levenshtein, Binary Codes Capable of Correcting Deletions, Insertions and Reversals. Soviet Physics Doklady, 1966, 10:707–710. [Google Scholar]
- M. A. Hasan, W. S. Spangler, T. Griffin, and A. Alba, “COA: finding novel patents through text analysis,” in KDD’09: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining. New York, NY, USA: ACM, 2009, pp. 1175–1184. [CrossRef] [Google Scholar]
- X. Jin, et al., “Patent Maintenance Recommendation with Patent Information Network Model.” IEEE, International Conference on Data Mining IEEE, 2011: 280–289. [Google Scholar]
- Yu, Wen Der, and J. Y. Hsu. “Content-based text mining technique for retrieval of CAD documents.” Automation in Construction 31.5 (2013):65–74. [CrossRef] [Google Scholar]
- Yafooz, Wael M. S., et al., “Dynamic Semantic Textual Document Clustering Using Frequent Terms and Named Entity.” IEEE, International Conference on System Engineering and Technology IEEE, 2013:336–340. [EDP Sciences] [Google Scholar]
- Roberta A, Sinoara, et al., “Named entities as privileged information for hierarchical text clustering.” International Database Engineering & Applications Symposium ACM, 2014:57–66. [Google Scholar]
- Montalvo, Soto, R. Martínez, and V. Fresno, “NESM: a named entity based proximity measure for multilingual news clustering.” Procesamiento Del Lenguaje Natural 48(2012):81–88. [Google Scholar]
- H. P. Zhang, et al., “HHMM-based Chinese lexical analyzer ICTCLAS.” Sighan Workshop on Chinese Language Processing Association for Computational Linguistics, 2003: pages. 758–759. [Google Scholar]
- J. Zhu, M. Zhu, Q. Wang, T. Xiao, Niuparser: A Chinese Syntactic and Semantic Parsing Toolkit, in: Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing: System Demonstrations, 2015, pp. 145–150. [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.