From International Center for Computational Logic
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Innovating Sales and Planning of Complex Industrial Products Exploiting Artificial Intelligence

Industrial products and services are increasingly configured, planned and sold through online shops partially validating dependencies between basic systems and purchase options. Additional customer requests are described as flow text, not being processed automatically today and thus, requiring time-consuming back office support. InnoSale develops methods to increase the expressiveness of validation rules (rule-based expert systems) and to suggest relevant purchase options (case-based reasoning). Sales engineers will be supported in finding previous customer requests & orders and other suitable solutions quickly (natural language processing, intelligent search) as well as identifying similarities between customers (evolutional clustering). Based on different data sources (historical, internal, external) dynamic pricing algorithms are also one project scope (trend prediction, machine learning, artificial neural networks, Q-Learning). User experience will be improved supported by combining deep learning systems with augmented reality techniques and 3D modelling.

Proceedings Articles

Larry Gonzalez, Alex Ivliev, Stephan Mennicke, Markus Krötzsch
Efficient Dependency Analysis for Existential Rules
Proceedings of the 15th Alberto Meldenzon International Workshop on Foundations of Data Management (AMW'23). Santiago, Chile, May 2023
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Larry González, Alex Ivliev, Markus Krötzsch, Stephan Mennicke
Efficient Dependency Analysis for Rule-Based Ontologies
In Ulrike Sattler, Aidan Hogan, Maria Keet, Valentina Presutti, João Paulo A. Almeida, Hideaki Takeda, Pierre Monnin, Giuseppe Pirrò, Claudia d’Amato, eds., The Semantic Web – ISWC 2022, volume 13489 of Lecture Notes in Computer Science, 267-283, October 2022. Springer
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