Martin, Andreas
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Martin, Andreas
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- PublikationNew hybrid techniques for business recommender systems(MDPI, 2022) Pande, Charuta; Witschel, Hans Friedrich; Martin, Andreas [in: Applied Sciences]Besides the typical applications of recommender systems in B2C scenarios such as movie or shopping platforms, there is a rising interest in transforming the human-driven advice provided, e.g., in consultancy via the use of recommender systems. We explore the special characteristics of such knowledge-based B2B services and propose a process that allows incorporating recommender systems into them. We suggest and compare several recommender techniques that allow incorporating the necessary contextual knowledge (e.g., company demographics). These techniques are evaluated in isolation on a test set of business intelligence consultancy cases. We then identify the respective strengths of the different techniques and propose a new hybridisation strategy to combine these strengths. Our results show that the hybridisation leads to substantial performance improvement over the individual methods.01A - Beitrag in wissenschaftlicher Zeitschrift
- PublikationReports of the AAAI 2019 Spring Symposium Series(American Association for Artificial Intelligence, 2019) Baldini, Ioana; Barrett, Clark; Chella, Antonio; Cinelli, Carlos; Gamez, David; Gilpin, Leilani H.; Hinkelmann, Knut; Holmes, Dylan; Kido, Takashi; Kocaoglu, Murat; Lawless, William F.; Lomuscio, Alessio; Macbeth, Jamie C.; Martin, Andreas; Mittu, Ranjeev; Patterson, Evan; Sofge, Donald; Tadepalli, Prasad; Takadama, Keiki; Wilson, Shomir [in: AI Magazine]The AAAI 2019 Spring Series was held Monday through Wednesday, March 25–27, 2019 on the campus of Stanford University, adjacent to Palo Alto, California. The titles of the nine symposia were Artificial Intelligence, Autonomous Machines, and Human Awareness: User Interventions, Intuition and Mutually Constructed Context; Beyond Curve Fitting — Causation, Counterfactuals and Imagination-Based AI; Combining Machine Learning with Knowledge Engineering; Interpretable AI for Well-Being: Understanding Cognitive Bias and Social Embeddedness; Privacy- Enhancing Artificial Intelligence and Language Technologies; Story-Enabled Intelligence; Towards Artificial Intelligence for Collaborative Open Science; Towards Conscious AI Systems; and Verification of Neural Networks.01A - Beitrag in wissenschaftlicher Zeitschrift