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Multi-Criteria Knowledge-Based Recommender System for Decision Support in Complex Business Processes
Abstrakt
In this paper, we present a concept of a multi-criteria knowledge-based Recommender System (RS) designed to provide decision support in complex business process (BP) scenarios. The developed approach is based on the knowledge aspects of Stylistic Patterns, Business Sentiment and Decision-Making Logic extracted from the BP unstructured texts. This knowledge serves as an input for a multi-criteria RS algorithm. The output is prediction of the BP complexity, based on which the algorithm modifies the type and the way of decision support, ranging from full to minimal automation. We show how the algorithm can be applied in the real-life scenarios by the example of the IT ticketing case study. We also evaluate the BP complexity prediction quality using both quantitative (data-based) and qualitative (interview-based) approach in the case study
Autorzy (2)
-
Aleksandra Revina magistr
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Pełna treść
- Wersja publikacji
- Accepted albo Published Version
- Licencja
-
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Informacje szczegółowe
- Kategoria:
- Aktywność konferencyjna
- Typ:
- publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
- ISSN:
- 1613-0073
- Język:
- angielski
- Rok wydania:
- 2019
- Opis bibliograficzny:
- Revina A., Rizun N.: Multi-Criteria Knowledge-Based Recommender System for Decision Support in Complex Business Processes// / : CEUR-WS.org, 2019, s.16-22
- Weryfikacja:
- Politechnika Gdańska
wyświetlono 221 razy
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