Abstract
User interface is an important element of software system since it provides the means for utilizing applications’ functionalities. There is number of publications that propose guidance for proper interface design, including adaptive approach. Following paper introduces general idea for definition of interface design in a way that allows for easy computing of user interface effectiveness. The introduced factor can be used for recommendation of interface changes and adjustment.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Beel, J., Breitinger, C., Langer, S., Lommatzsch, A., Gipp, B.: Towards reproducibility in recommender-systems research. User Model. User Adap. Inter. 26(1), 69–101 (2016)
Bobadilla, J., Ortega, F., Hernando, A., Gutiérrez, A.: Recommender systems survey. Knowl. Based Syst. 46, 109–132 (2013)
Cooley, R., Mobasher, B., Srivastava, J.: Web mining: information and pattern discovery on the world wide web. In: Proceedings Ninth IEEE International Conference on Tools with Artificial Intelligence, pp. 558–567, November 1997. https://doi.org/10.1109/TAI.1997.632303
Isinkaye, F., Folajimi, Y., Ojokoh, B.: Recommendation systems: principles, methods and evaluation. Egypt. Inform. J. 16(3), 261–273 (2015)
Krótkiewicz, M.: A novel inheritance mechanism for modeling knowledge representation systems. Comput. Sci. Inform. Syst. (2017). https://doi.org/10.2298/CSIS170630046K
Krótkiewicz, M.: Association-oriented database model – n-ary associations. Int. J. Softw. Eng. Knowl. Eng. 27(02), 281–320 (2017). https://doi.org/10.1142/S0218194017500103
Krótkiewicz, M.: Cyclic value ranges model for specifying flowing resources in unified process metamodel. Enterp. Inform. Syst., 1–23 (2018). https://doi.org/10.1080/17517575.2018.1472810
Krótkiewicz, M., Jodłowiec, M.: Modeling autoreferential relationships in association-oriented database metamodel. In: Świątek, J., Borzemski, L., Wilimowska, Z. (eds.) ISAT 2017. AISC, vol. 656, pp. 49–62. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-67229-8_5
Kukla, E., Nguyen, N.T., Sobecki, J., Danilowicz, C., Lenar, M.: Determination of learning scenarios in intelligent web-based learning environment. In: Orchard, B., Yang, C., Ali, M. (eds.) IEA/AIE 2004. LNCS (LNAI), vol. 3029, pp. 759–768. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-24677-0_78
Malski, M.: A Method for web-based user interface recommendation using collective knowledge and multi-attribute structures. In: Jędrzejowicz, P., Nguyen, N.T., Hoang, K. (eds.) ICCCI 2011. LNCS (LNAI), vol. 6922, pp. 346–355. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-23935-9_34
Mican, D., Tomai, N.: Association-rules-based recommender system for personalization in adaptive web-based applications. In: Daniel, F., Facca, F.M. (eds.) ICWE 2010. LNCS, vol. 6385, pp. 85–90. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-16985-4_8
Montaner, M., López, B., de la Rosa, J.L.: A taxonomy of recommender agents on the internet. Artif. Intell. Rev. 19(4), 285–330 (2003). https://doi.org/10.1023/A:1022850703159
Shahabi, C., Banaei-Kashani, F.: A framework for efficient and anonymous web usage mining based on client-side tracking. In: Kohavi, R., Masand, B.M., Spiliopoulou, M., Srivastava, J. (eds.) WebKDD 2001. LNCS (LNAI), vol. 2356, pp. 113–144. Springer, Heidelberg (2002). https://doi.org/10.1007/3-540-45640-6_6
Sobecki, J.: Ant colony metaphor applied in user interface recommendation. New Gener. Comput. 26(3), 277 (2008). https://doi.org/10.1007/s00354-008-0045-9
Srivastava, J., Cooley, R., Deshpande, M., Tan, P.N.: Web usage mining: discovery and applications of usage patterns from web data. SIGKDD Explor. Newsl. 1(2), 12–23 (2000). https://doi.org/10.1145/846183.846188
Wojtkiewicz, K., Jodłowiec, M., Krótkiewicz, M.: Association-oriented database metamodel: modelling language (2017). https://doi.org/10.13140/RG.2.2.18483.73769
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this paper
Cite this paper
Krótkiewicz, M., Wojtkiewicz, K., Martins, D. (2018). Influence Power Factor for User Interface Recommendation System. In: Nguyen, N., Pimenidis, E., Khan, Z., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2018. Lecture Notes in Computer Science(), vol 11055. Springer, Cham. https://doi.org/10.1007/978-3-319-98443-8_21
Download citation
DOI: https://doi.org/10.1007/978-3-319-98443-8_21
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-98442-1
Online ISBN: 978-3-319-98443-8
eBook Packages: Computer ScienceComputer Science (R0)