Software Service with a Plug-in Architecture for Text Readability Assessment

2021;
: cc. 77 - 85
1
Lviv Polytechnic National University
2
Національний університет «Львівська політехніка»

The problem of developing a software service with a plug-in architecture for assessing the readability of text has been considered. The problem of text readability assessment has been analyzed. Approaches to the development of a software service for text readability assessment have been considered. The structure of the service for text readability assessment has been proposed. The structure of the service has been implemented using the Python programming language and the library Natural Language Toolkit (NLTK). The results of testing the service for text readability assessment have been presented.

  1. Gunning, R. (1952) The Technique of Clear Writing. McGraw-Hill, pp. 36-37.
  2. Flesch, R. (1948) A new readability yardstick. Journal of Applied Psychology. 32 (3), pp. 221-233.
    https://doi.org/10.1037/h0057532
  3. Farr, J.N., Jenkins, J.J. and Paterson, D.G. (1951) Simplification of Flesch Reading Ease Formula. Journal of Applied Psychology. 35 (5), pp. 333-337.
    https://doi.org/10.1037/h0062427
  4. McClure, G. (1987) Readability formulas: Useful or useless. (an interview with J. Peter Kincaid). IEEE Transactions on Professional Communication. 30, pp. 12-15.
    https://doi.org/10.1109/TPC.1987.6449109
  5. Kincaid, J.P., Aagard, J.A., O’Hara, J.W. and Cottrell, L.K. (1981) Computer Readability Editing System. IEEE Transactions on Professional Communication. 24 (1), pp. 38-42.
    https://doi.org/10.1109/TPC.1981.6447821
  6. Senter, R.J. and Smith, E.A. (1967) Automated Readability Index. Aerospace Medical Research Laboratories, University of Cincinnati, Wright-Patterson Air Force Base, Ohio, AMRL-TR-66-20. — 14 p.
  7. Coleman, M. and Liau, T. L. (1975) A computer readability formula designed for machine scoring. Journal of Applied Psychology, Vol. 60, pp. 283-284.
    https://doi.org/10.1037/h0076540
  8. Zhou, S., Jeong, H. and Green, P. (2017) How Consistent Are the Best-Known Readability Equations in Estimating the Readability of Design Standards?. IEEE Transactions on Professional Communication, vol. 60, no. 1, pp. 97-111.
    https://doi.org/10.1109/TPC.2016.2635720
  9. Karmakar, S. and Zhu, Y. (2010) Visualizing multiple text readability indexes. In: 2010 International Conference on Education and Management Technology, pp. 133-137.
    https://doi.org/10.1109/ICEMT.2010.5657684
  10. Karmakar, S. and Ying Zhu (2010) Visualizing text readability. In: 2010 6th International Conference on Advanced Information Management and Service (IMS), pp. 291-296.
  11. Iram, N., Zafar, S. and Zahra, R. (2018) Web content readability evaluation using fuzzy logic. In: International Conference on Advancements in Computational Sciences (ICACS), pp. 1-8.
    https://doi.org/10.1109/ICACS.2018.8333281
  12. Antunes, H. and Lopes, C. (2019) Readability of web content. In: 2019 14th Iberian Conference on Information Systems and Technologies (CISTI), pp. 1-4.
    https://doi.org/10.23919/CISTI.2019.8760889
  13. Naderi, B., Mohtaj, S., Karan, K. and Möller, S. (2019) Automated Text Readability Assessment for German Language: A Quality of Experience Approach. In: 2019 Eleventh International Conference on Quality of Multimedia Experience (QoMEX), pp. 1-3.
    https://doi.org/10.1109/QoMEX.2019.8743194
  14. Tra My, H., N., Suzuki, S. and Miyazaki, Y. (2017) Building Personalized Readability Equation and Personalized English Vocabulary List for Continued Study". In: 2017 6th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI), pp. 791-795.
    https://doi.org/10.1109/IIAI-AAI.2017.135
  15. Qumsiyeh, R. and Ng, Y. (2011) ReadAid: A Robust and Fully-Automated Readability Assessment Tool. In: 2011 IEEE 23rd International Conference on Tools with Artificial Intelligence, pp. 539-546.
    https://doi.org/10.1109/ICTAI.2011.87
  16. Liu, Y., Ji, M., Lin, S., Zhao, M. and Lyv, Z. (2021) Combining Readability Formulas and Machine Learning for Reader-oriented Evaluation of Online Health Resources. IEEE Access, vol. 9.
    https://doi.org/10.1109/ACCESS.2021.3077073
  17. Decasper, D., Dittia, Z., Parulkar, G. and Plattner, B. (2000) Router plugins: a software architecture for next-generation routers. IEEE/ACM Transactions on Networking, vol. 8, no. 1, pp. 2-15.
    https://doi.org/10.1109/90.836474
  18. Zhu, J., Yin, Q., Zhu, R., Guo, C., Wang, H. and Wu, Q. (2008) A Plugin-Based Software Production Line Integrated Framework". In: International Conference on Computer Science and Software Engineering, pp. 562-565.
    https://doi.org/10.1109/CSSE.2008.562
  19. Schleinzer, B., Cabac, L., Moldt, D. and Duvigenau, M. (2008) From Agents and Plugins to Plugin-Agents, Concepts for Flexible Architectures. In: New Technologies, Mobility and Security, pp. 1-5.
    https://doi.org/10.1109/NTMS.2008.ECP.49
  20. Adhikari, S. and Jones, B. (2019) A Modular Plugin Architecture for Literate Programming Editors“. In: Proceedings of the of 2019 SoutheastCon (IEEE Region 3 Technical, Professional, and Student Conference), pp. 1-4.
    https://doi.org/10.1109/SoutheastCon42311.2019.9020617
  21. Minh Vu and Thompson, C. (2005) E2 agent plugin architecture. In: International Conference on Integration of Knowledge Intensive Multi-Agent Systems, pp. 26-31.
  22. Bako, B., Borchert, A., Heidenbluth, N. and J. Mayer (2006) Linearly Ordered Plugins through Self-Organization. In: International Conference on Autonomic and Autonomous Systems (ICAS’06).
  23. Ricci, F., Rokach, L., Shapira, B. and Kantor, P. (eds.) (2015) Recommender Systems Handbook. 2nd ed., Springer. — 1020 p.
    https://doi.org/10.1007/978-1-4899-7637-6
  24. Aggarwal, C. (2016) Recommender Systems: The Textbook. Springer. — 519 p.
    https://doi.org/10.1007/978-3-319-29659-3
  25. Schrage, M. (2020) Recommendation Engines. The MIT Press. — 296 p.
    https://doi.org/10.7551/mitpress/12766.001.0001
  26. Falk, K. (2019) Practical Recommender Systems. Manning Publications. — 432 p.
  27. Robillard, M., Maalej, W., Walker, R. and Zimmermann, T. (eds.) (2014) Recommendation Systems in Software Engineering. Springer-Verlag Berlin Heidelberg. — 560 p.
    https://doi.org/10.1007/978-3-642-45135-5
  28. Jannach, D. (2010) Recommender Systems: An Introduction. Cambridge University Press. — 352 p.
    https://doi.org/10.1017/CBO9780511763113
  29. Jie Lu, Qian Zhang, Guangquan Zhang (2020) Recommender Systems: Advanced Developments. WSPC. — 362 p.
    https://doi.org/10.1142/11947
  30. Suresh Kumar Gorakala (2017) Building Recommendation Engines. Packt Publishing. — 357 p.
  31. Schilit, B., Adams, N. and Want, R. (1994) Context-aware computing applications. In: Proceedings of the IEEE Workshop on “Mobile Computing Systems and Applications”, IEEE Computer Society, pp. 85-90.
    https://doi.org/10.1109/WMCSA.1994.16
  32. Perera, C., Zaslavsky, A., Christen, P. and Georgakopoulos, D. (2014) Context Aware Computing for The Internet of Things: A Survey. IEEE Communications Surveys & Tutorials, vol. 16, no. 1, First Quarter, pp. 414-454.
    https://doi.org/10.1109/SURV.2013.042313.00197
  33. Grifoni, P., D’Ulizia, A., and Ferri, F. (2018) Context- Awareness in Location Based Services in the Big Data Era, In: Skourletopoulos, G., Mastorakis, G., Mavromoustakis, C., Dobre C. and Pallis, E. (eds.) Mobile Big Data. Lecture Notes on Data Engineering and Communications Technologies, Springer, vol. 10, pp. 85-127.
    https://doi.org/10.1007/978-3-319-67925-9_5
  34. Capurso, N., Bo Mei, Tianyi Song and Xiuzhen Cheng (2018) A survey on key fields of context awareness for mobile devices. Journal of Network and Computer Applications, Volume 118, pp. 44-60.
    https://doi.org/10.1016/j.jnca.2018.05.006
  35. Sutton, R.S., Barto, A.G. (2018) Reinforcement Learning: An Introduction. 2nd ed., A Bradford Book. — 532 p.
  36. Weber, C., Elshaw, M. and Mayer, N. (eds.) (2008) Reinforcement Learning: Theory and Applications. Vienna: I-Tech Education and Publishing. — 424 p.
    https://doi.org/10.5772/54
  37. Wiering, M., van Otterlo, M. (eds.) (2012) Reinforcement Learning: State-of-the-Art. Springer. — 672 p.
    https://doi.org/10.1007/978-3-642-27645-3
  38. Bertsekas, D. (2019) Reinforcement Learning and Optimal Control. Athena Scientific. — 388 p.