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182 Computer Science & Information Technology (CS & IT) [4] Tabei,Y., Saigo, H., Yamanishi, Y. & Puglisi, S. J. (2016) “Scalable partial least squares regression on grammar-compressed data matrices”, in 22 nd KDD, pp. 1875—1884. [5] Maruyama, S., Tanaka, Y., Sakamoto, H., & Takeda, M. (2010) “Context-sensitive grammar transform: Compression and pattern matching”, IEICE Transactions on Information and Systems, vol. E93.D, no. 2, pp. 219–226. [6] Tabei, Y. (2016) “Recent development of grammar compression”, Information Processing Society of Japan Magazine, vol. 57, no. 2, pp. 172–178. [7] Jez, A. (2016) “A really simple approximation of smallest grammar”, Theoretical Computer Science, vol. 616, pp. 141 – 150. [8] De la Higuera, C. (2010) Grammatical inference: learning automata and grammars. Cambridge University Press. [9] José Neto, J. (2001) “Adaptive rule-driven devices - general formulation and case study”, in CIAA 2001 6th International Conference on Implementation and Application of Automata, ser. Lecture Notes in Computer Science, B. W. Watson and D. Wood, Eds., vol. 2494. Pretoria, South Africa: Springer-Verlag, pp. 234–250. [10] Rocha, R. L. A. & José Neto, J. (2000) “Adaptive automaton, limits and complexity compared to the Turing machine”, in Proceedings of the I LAPTEC, pp. 33–48. [11] Fukunaga, S., Takabatake, Y., I, T. & Sakamoto, H. (2016) “Online grammar compression for frequent pattern discovery”, CoRR, vol. abs/1607.04446. [12] Takabatake, Y., Tabei, Y., & Sakamoto, H. (2015) Online Self-Indexed Grammar Compression. Springer International Publishing, pp. 258–269. [13] Charikar, M., Lehman, E., Liu, D., Panigrahy, R., Prabhakaran, M., Sahai, A. & Shelat, A. (2005) “The smallest grammar problem.” IEEE Trans. Inf. Theory, vol. 51, no. 7, pp. 2554–2576. [14] Nevill-Manning, C. G. & Witten, I. H. (1997) “Identifying hierarchical structure in sequences: A linear-time algorithm”, J. Artif. Intell. Res.(JAIR) vol. 7, pp. 67–82. [15] Larsson, N. J. & Moffat, A. (1999) “Offline dictionary-based compression”, in Data Compression Conference, 1999. Proceedings. DCC ’99, pp. 296–305. [16] Rytter, W. (2002) Application of Factorization to the Approximation of Grammar-Based Compression. Berlin, Heidelberg: Springer Berlin Heidelberg, pp. 20–31. [17] Ziv, J. & Lempel, A. (2006) “A universal algorithm for sequential data compression”, IEEE Trans. Inf. Theor., vol. 23, no. 3, pp. 337–343. [18] Sakamoto, H., (2005) “A fully linear-time approximation algorithm for grammar-based compression”, Journal of Discrete Algorithms, vol. 3, no. 2–4, pp. 416–430. [19] Jez, A. (2015) “Approximation of grammar-based compression via recompression”, Theoretical Computer Science, vol. 592, pp. 115–134. [20] Maruyama, S. & Tabei, Y. (2014) “Fully online grammar compression in constant space.” in DCC, Bilgin, A., Marcellin, M. W., Serra-Sagristà, J. & Storer, J. A. Eds. IEEE, pp. 173–182. [21] Cormode, G. & Muthukrishnan, S. (2007) “The string edit distance matching problem with moves”, ACM Transactions on Algorithms (TALG) vol. 3, no. 1, pp. 2:1–2:19.
Computer Science & Information Technology (CS & IT) 183 [22] José Neto, J. (1994) “Adaptive automata for context-sensitive languages”, SIGPLAN Notices, vol. 29, no. 9, pp. 115–124. [23] José Neto, J. & Iwai, M. K. (1998) “Adaptive automata for syntax learning” in Anais da XXIV Conferência Latinoamericana de Informática - CLEI 98, pp. 135–149. [24] Matsuno, I. P. (2006) “Um estudo dos processos de inferência de gramáticas regulares e livres de contexto baseados em modelos adaptativos”, Master’s Thesis, Escola Politécnica da Universidade de São Paulo, São Paulo, Brasil. [25] Cereda, P. R. M. & José Neto, J. (2015) “A recommendation engine based on adaptive automata”, in Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 2: ICEIS, pp. 594–601. [26] Cereda, P. R. M. & José Neto, J. (2016) “AA4J: uma biblioteca para implementação de autômatos adaptativos” in Memórias do X Workshop de Tecnologia Adaptativa – WTA 2016, 2016, pp. 16–26. [27] Iwai, M. K. (2000) “Um formalismo gramatical adaptativo para linguagens dependentes de contexto”, PhD Thesis, Escola Politécnica da Universidade de São Paulo, São Paulo, Brasil. AUTHORS Newton Kiyotaka Miura is a researcher at Olos Tecnologia e Sistemas and a PhD candidate in Computer Engineering at Departamento de Engenharia de Computação e Sistemas Digitais, Escola Politécnica da Universidade de São Paulo. He received his Electrical Engineering degree from Escola Politécnica da Universidade de São Paulo (1989) and holds a master’s degree in Systems Engineering from the University of Kobe, Japan (1993). His research interests include adaptive technology, adaptive automata, adaptive devices and natural language processing. João José Neto is an associate professor at Escola Politécnica da Universidade de São Paulo and coordinates the Language and Adaptive Technology Laboratory of Departamento de Engenharia de Computação e Sistemas Digitais. He received his Electrical Engineering degree (1971), master's degree (1975) and PhD in Electrical Engineering (1980) from Escola Politécnica da Universidade de São Paulo. His research interests include adaptive devices, adaptive technology, adaptive automata and applications in adaptive decision making systems, natural language processing, compilers, robotics, computer assisted teaching, intelligent systems modelling, automatic learning processes and adaptive technology inferences.
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Computer Science & Information Tech
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Volume Editors Dhinaharan Nagamalai
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Organization General Chair Nataraja
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Fourth International Conference on
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INVESTIGATING BINARY STRING ENCODIN
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USE OF ADAPTIVE COLOURED PETRI NETW
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4. METHODOLOGY Computer Science & I
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DIVING PERFORMANCE ASSESSMENT BY ME
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NEW NON-COPRIME CONJUGATE-PAIR BINA
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TOWARDS A MULTI-FEATURE ENABLED APP
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