Semantic Matchmaker

We could imagine an extension of a “publish and subscribe” scheme as the general way to build systems.

The basic idea here is a bit more biological and stochastic. The matching and negotiation processes would be used so that each Object Has Two Public Billboards, one for “requests for resources, help, etc.” and the other “Offers to the General Good”. The Semantic Matchmaker will make useful Loose Couplings, and very large, very robust systems can be made.

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Alan Kay, Is there Static Typing for a Smalltalk derivative? quora

BELLUR, Umesh, GUPTA, Amit and VADODARIA, Harin, 2008. Semantic matchmaking algorithms. INTECH Open Access Publisher Rijeka. pdf [Accessed 30 December 2023].

BENER, Ayse B., OZADALI, Volkan and ILHAN, Erdem Savas, 2009. Semantic matchmaker with precondition and effect matching using SWRL. Expert systems with applications. Online. 2009. Vol. 36, no. 5, p. 9371–9377. Available from: https://www.sciencedirect.com/science/article/pii/S0957417409000475 [Accessed 30 December 2023]. CASSAR, Gilbert, BARNAGHI, Payam, WANG, Wei and MOESSNER, Klaus, 2012. A hybrid semantic matchmaker for IoT services. In: 2012 IEEE International Conference on Green Computing and Communications. Online. IEEE. 2012. p. 210–216. Available from: https://ieeexplore.ieee.org/abstract/document/6468315/ [Accessed 30 December 2023]. HEIDARI, Golsa and ZAMANIFAR, Kamran, 2021. A Three Phase Semantic Web Matchmaker.. Online. 6 July 2021. arXiv. arXiv:2107.05368. Available from: http://arxiv.org/abs/2107.05368 [Accessed 30 December 2023]. Since using environments that are made according to the service oriented architecture, we have more effective and dynamic applications. Semantic matchmaking process is finding valuable service candidates for substitution. It is a very important aspect of using semantic Web Services. Our proposed matchmaker algorithm performs semantic matching of Web Services on the basis of input and output descriptions of semantic Web Services matching. This technique takes advantages from a graph structure and flow networks. Our novel approach is assigning matchmaking scores to semantics of the inputs and outputs parameters and their types. It makes a flow network in which the weights of the edges are these scores, using FordFulkerson algorithm, we find matching rate of two web services. So, all services should be described in the same Ontology Web Language. Among these candidates, best one is chosen for substitution in the case of an execution failure. Our approach uses the algorithm that has the least running time among all others that can be used for bipartite matching. The importance of problem is that in real systems, many fundamental problems will occur by late answering. So system`s service should always be on and if one of them crashes, it would be replaced fast. Semantic web matchmaker eases this process. arXiv:2107.05368 [cs] KARABULUT, Erkan and SOFIA, Rute C., 2023. An Analysis of Machine Learning-Based Semantic Matchmaking. IEEE Access. Online. 2023. Vol. 11, p. 27829–27842. Available from: https://ieeexplore.ieee.org/abstract/document/10076794/ [Accessed 30 December 2023]. KAWAMURA, Takahiro, DE BLASIO, Jacques-Albert, HASEGAWA, Tetsuo, PAOLUCCI, Massimo and SYCARA, Katia, 2004. Public Deployment of Semantic Service Matchmaker with UDDI Business Registry. In: MCILRAITH, Sheila A., PLEXOUSAKIS, Dimitris and VAN HARMELEN, Frank (eds.), The Semantic Web – ISWC 2004. Online. Berlin, Heidelberg: Springer Berlin Heidelberg. p. 752–766. Lecture Notes in Computer Science. ISBN 978-3-540-23798-3. [Accessed 30 December 2023]. KLUSCH, Matthias and KAPAHNKE, Patrick, 2012. The iSeM matchmaker: A flexible approach for adaptive hybrid semantic service selection. Journal of Web Semantics. Online. 2012. Vol. 15, p. 1–14. Available from: https://www.sciencedirect.com/science/article/pii/S1570826812000777 [Accessed 30 December 2023]. MOHEBBI, Keyvan, IBRAHIM, Suhaimi, ZAMANI, Mazdak and KHEZRIAN, Mojtaba, 2014. UltiMatch-NL: a web service matchmaker based on multiple semantic filters. PLoS one. Online. 2014. Vol. 9, no. 8, p. e104735. Available from: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0104735 [Accessed 30 December 2023]. RUTA, Michele, SCIOSCIA, Floriano, IEVA, Saverio, CAPURSO, Giovanna and DI SCIASCIO, Eugenio, 2019. Semantic matchmaking as a way for attitude discovery. In: 2019 IEEE 8th International Workshop on Advances in Sensors and Interfaces (IWASI). Online. IEEE. 2019. p. 85–90. Available from: https://ieeexplore.ieee.org/abstract/document/8791270/ [Accessed 30 December 2023]. XU, Bin, ZHANG, Po, LI, Juan-Zi and YANG, Wen-Jun, 2006. A Semantic Matchmaker for Ranking Web Services. Journal of Computer Science and Technology. Online. July 2006. Vol. 21, no. 4, p. 574–581. DOI 10.1007/s11390-006-0574-y. [Accessed 30 December 2023].