Abstract
Clood is a cloud-based CBR framework based on a microservices architecture which facilitates the design and deployment of case-based reasoning applications of various sizes. This paper presents advances to the similarity module of Clood through the inclusion of enhanced similarity metrics such as word embedding and ontology-based similarity measures. Being cloud-based, costs can significantly increase if the use of resources such as storage and data transfer are not optimised. Accordingly, we discuss and compare alternative design decisions and provide justification for each chosen approach for Clood.
This research is funded by the iSee project (https://isee4xai.com) which received funding from EPSRC under the grant number EP/V061755/1. iSee is part of the CHIST-ERA pathfinder programme for European coordinated research on future and emerging information and communication technologies.
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References
Amailef, K., Lu, J.: Ontology-supported case-based reasoning approach for intelligent m-government emergency response services. Decis. Support Syst. 55(1), 79–97 (2013)
Amin, K., Lancaster, G., Kapetanakis, S., Althoff, K.-D., Dengel, A., Petridis, M.: Advanced similarity measures using word embeddings and siamese networks in CBR. In: Bi, Y., Bhatia, R., Kapoor, S. (eds.) IntelliSys 2019. AISC, vol. 1038, pp. 449–462. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-29513-4_32
Cer, D., et al.: Universal sentence encoder. arXiv preprint arXiv:1803.11175 (2018)
Díaz-Agudo, B., González-Calero, P.A., Recio-García, J.A., Sánchez-Ruiz-Granados, A.A.: Building CBR systems with jcolibri. Sci. Comput. Program. 69(1–3), 68–75 (2007)
Ghofrani, J., Lübke, D.: Challenges of microservices architecture: a survey on the state of the practice. ZEUS 2018, 1–8 (2018)
González-Calero, P.A., Díaz-Agudo, B., Gómez-Albarrán, M., et al.: Applying DLS for retrieval in case-based reasoning. In: Proceedings of the 1999 Description Logics Workshop (Dl 1999). Linkopings universitet. Citeseer (1999)
Hliaoutakis, A., Varelas, G., Voutsakis, E., Petrakis, E.G., Milios, E.: Information retrieval by semantic similarity. Int. J. Semant. Web Inf. Syst. (IJSWIS) 2(3), 55–73 (2006)
Khattak, F.K., Jeblee, S., Pou-Prom, C., Abdalla, M., Meaney, C., Rudzicz, F.: A survey of word embeddings for clinical text. J. Biomed. Inform. 100, 100057 (2019)
Lastra-Díaz, J.J., Goikoetxea, J., Taieb, M.A.H., García-Serrano, A., Aouicha, M.B., Agirre, E.: A reproducible survey on word embeddings and ontology-based methods for word similarity: linear combinations outperform the state of the art. Eng. Appl. Artif. Intell. 85, 645–665 (2019)
Lin, D., et al.: An information-theoretic definition of similarity. In: ICML, vol. 98, pp. 296–304 (1998)
Mikolov, T., Sutskever, I., Chen, K., Corrado, G.S., Dean, J.: Distributed representations of words and phrases and their compositionality. In: Advances in Neural Information Processing Systems 26 (2013)
Montero-Jiménez, J.J., Vingerhoeds, R., Grabot, B.: Enhancing predictive maintenance architecture process by using ontology-enabled case-based reasoning. In: 2021 IEEE International Symposium on Systems Engineering (ISSE), pp. 1–8. IEEE (2021)
Nkisi-Orji, I., Wiratunga, N., Palihawadana, C., Recio-García, J.A., Corsar, D.: Clood CBR: towards microservices oriented case-based reasoning. In: Watson, I., Weber, R. (eds.) ICCBR 2020. LNCS (LNAI), vol. 12311, pp. 129–143. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-58342-2_9
Qin, Y., et al.: Towards an ontology-supported case-based reasoning approach for computer-aided tolerance specification. Knowl.-Based Syst. 141, 129–147 (2018)
Rada, R., Mili, H., Bicknell, E., Blettner, M.: Development and application of a metric on semantic nets. IEEE Trans. Syst. Man Cybern. 19(1), 17–30 (1989)
Recio-Garía, J.A., Díaz-Agudo, B.: Ontology based CBR with jCOLIBRI. In: Ellis, R., Allen, T., Tuson, A. (eds.) SGAI 2006, pp. 149–162. Springer, London (2006). https://doi.org/10.1007/978-1-84628-666-7_12
Resnik, P.: Using information content to evaluate semantic similarity in a taxonomy. arXiv preprint cmp-lg/9511007 (1995)
Sánchez, D., Batet, M., Isern, D., Valls, A.: Ontology-based semantic similarity: a new feature-based approach. Expert Syst. Appl. 39(9), 7718–7728 (2012)
Schleier-Smith, J., et al.: What serverless computing is and should become: the next phase of cloud computing. Commun. ACM 64(5), 76–84 (2021)
Taibi, D., El Ioini, N., Pahl, C., Niederkofler, J.R.S.: Patterns for serverless functions (function-as-a-service): a multivocal literature review (2020)
Wu, Z., Palmer, M.: Verb semantics and lexical selection. arXiv preprint cmp-lg/9406033 (1994)
Xie, R., Tang, Q., Qiao, S., Zhu, H., Yu, F.R., Huang, T.: When serverless computing meets edge computing: architecture, challenges, and open issues. IEEE Wirel. Commun. 28(5), 126–133 (2021)
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Nkisi-Orji, I., Palihawadana, C., Wiratunga, N., Corsar, D., Wijekoon, A. (2022). Adapting Semantic Similarity Methods for Case-Based Reasoning in the Cloud. In: Keane, M.T., Wiratunga, N. (eds) Case-Based Reasoning Research and Development. ICCBR 2022. Lecture Notes in Computer Science(), vol 13405. Springer, Cham. https://doi.org/10.1007/978-3-031-14923-8_9
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