참고문헌
- 안광모, 김윤석, 김영훈, 서영훈 (2013). Levenshtein 거리를 이용한 영화평 감성 분류. 디지털콘텐츠학회 논문지, 14(4), 581-587. http://dx.doi.org/10.9728/dcs.2013.14.4.581 Ahn, K. M., Kim, Y. S., Kim, Y. H., & Seo, Y. H. (2013). Sentiment classification of movie reviews using levenshtein distance. Journal of Digital Contents Society, 14(4), 581-587. http://dx.doi.org/10.9728/dcs.2013.14.4.581
- 황미녕, 조민희, 황명권, 정도헌, 성원경 (2011). 기술 용어의 용어지배값을 이용한 활용주기 모델링 방법. 한국정보과학회 학술발표논문집, 38(1C), 139-141. Hwang, M. N., Cho, M., Hwang, M., Jeong, D. H., & Sung, W. K. (2011). A utility cycle modeling method for technological terms based on term dominance value. Proceedings of the KIISE Conference, 38(1C), 139-141.
- Abe, A., & Tsumoto, S. (2010). Analysis of research keys as temporal patterns of technical term usage in bibliographical data. Lecture Notes in Computer Science book series (LNCS, volume 6496), International Conference on Active Media Technology AMT 2010, 150-157. https://doi.org/10.1007/978-3-642-15470-6_16
- Cormode, G., & Muthukrishnan, S. (2007). The string edit distance matching problem with moves. ACM Transactions on Algorithms, NY, USA, 3(1), No.2. https://doi.org/10.1145/1186810.1186812
- Fortune (2017). Apple just acquired this little-known artificial intelligence startup. Retrieved from http://fortune.com/2017/05/13/apple-lattice/
- Gartner (2018). Dark data (Gartner IT Glossary). Retrieved from https://www.gartner.com/it-glossary/dark-data
- Heidorn, P. B. (2008). Shedding light on the dark data in the long tail of science. Library Trends, 57(2), 280-299. https://doi.org/10.1353/lib.0.0036
- Hwang, M. N., Cho, M. H., Hwang. M., Lee, M., & Jeong, D. H. (2014). Technical terms trends analysis method for technology opportunity discovery. Information, An International Interdisciplinary Journal, 17(3), 877-883.
- Jain, P., Hitzler, P., Sheth, A. P., Verma, K., & Yeh, P. Z. (2010). Ontology alignment for linked open data. Lecture Notes in Computer Science book series (LNCS, volume 6496) ISWC 2010: The Semantic Web, 402-417. https://doi.org/10.1007/978-3-642-17746-0_26
- Jeong, D. H., Hwang, M., & Sung, W. K. (2011). Generating knowledge map for acronymexpansion recognition. In the Proceedings on U- and E-Service Science and Technology (UNESST 2011), 287-293. https://doi.org/10.1007/978-3-642-27210-3_38
- Jeong, D. H., Hwang, M., Kim, J., Jung, H., & Sung, W. K. (2013). Acronym-expansion recognition based on knowledge map system. Information, An International Interdisciplinary Journal, 12(A), 8403-8408.
- Kim, J., Hwang, M., Jeong, D. H., & Jung, H. (2012). Technology trends analysis and forecasting application based on decision tree. Expert Systems with Applications and Statistical Feature Analysis, 39(2012), 12618-12625. https://doi.org/10.1016/j.eswa.2012.05.021
- Li, Q., Li, Y., Gao, J., Su, L., Zhao, B., Demirbas, M., Fan, W., & Han, J. (2014). A confidenceaware approach for truth discovery on long-tail data. Journal Proceedings of the VLDB Endowment, 8(4), 425-436. https://doi.org/10.14778/2735496.2735505
- Noia, T. D., Mirizzi, R., Ostuni, V. C., Romito, D., & Zanker, M. (2012). Linked open data to support content-based recommender systems. Proceedings of the 8th International Conference on Semantic Systems, 1-8. https://doi.org/10.1145/2362499.2362501
- Paulheim, H., & Fümkranz, J. (2012). Unsupervised generation of data mining features from linked open data. Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics, No. 31. https://doi.org/10.1145/2254129.2254168
- Reis, D. C., Golgher, P. B., Silva, A. S., & Laender, A. F. (2004). Automatic web news extraction using tree edit distance. Proceedings of the 13th International Conference on World Wide Web, 502-511. https://doi.org/10.1145/988672.988740
- Veritas (2016). Veritas global databerg report finds 85% of stored data is either dark or Redundant, Obsolete, or Trivial (ROT). Retrieved from https://www.veritas.com/news-releases/2016-03-15-veritas-global-databerg-report-finds-85-percent-of-stored-data
- Wikipedia (2018a). Long tail. Retrieved from https://en.wikipedia.org/wiki/Long_tail
- Wikipedia (2018b). X-ray diffraction (redirection). Retrieved from https://en.wikipedia.org/wiki/X-ray_crystallography
- Wikipedia (2018c). High-performance liquid chromatography. Retrieved from https://en.wikipedia.org/wiki/High-performance_liquid_chromatography
- Wikipedia (2018d). Edit distance. Retrieved from https://en.wikipedia.org/wiki/Edit_distance
- Wu, F., Hoffmann, R., & Weld, D. S. (2008). Information extraction from Wikipedia: moving down the long tail. Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 731-739. https://doi.org/10.1145/1401890.1401978
- Zhang, C., Shin, J., Ré, C., Cafarella, M., & Niu, F. (2016). Extracting databases from dark data with deepdive. Proceedings of the 2016 International Conference on Management of Data, 847-859. https://doi.org/10.1145/2882903.2904442