An Ontology-Driven Recommender System for Engineering Projects
Doctoral thesis
Permanent lenke
http://hdl.handle.net/11250/2560714Utgivelsesdato
2018Metadata
Vis full innførselSamlinger
Sammendrag
Knowledge and information resources in enterprises are rapidly growing. The International Data Corporation (IDC) forecasts that significant yearly growth of data will result that the so-called global datasphere will have grown to 163 zettabytes (ZB) by 2025, which is 10 times of the 16.1 ZB of data generated in 2016. This happens while IT staff to manage it will grow less than 1.5 times (Reinsel, Gantz, & Rydning, 2017). A substantial number of these resources are documents that are potentially valuable for intentional reuse. Knowledge workers and engineers in particular, require specific knowledge and information embedded in different types of knowledge objects stored in internal or external resources (Hertzum & Pejtersen, 2000). However, identifying relevant knowledge from a large number of unstructured enterprise resources is challenging for users. There is a strong need for an approach that identifies users’ required information and automatically explores their preferred documents.
This PhD project focuses on improving knowledge access, sharing, and reuse challenges that people, engineers, are faced with in their daily (knowledge-based) work tasks. The proposed solution is a recommender system in professional settings to provide relevant documents for users in specific work contexts based on domain-specific ontologies. A prototype has been developed and validated on a multidisciplinary engineering use case and its performance has been evaluated. The results show that the developed system is a useful tool for improving information access in traditional engineering Projects compared to the currently applied solutions. The main contributions of this thesis are:
C1: In-depth analysis of the context of users and the document corpus in an engineering setting by applying information retrieval tools and semantic annotation.
C2. Proposing a framework for a knowledge access system combining recommendation approaches, ontologies, and information retrieval and extraction tools.
C3. Construction of a contextual ontology as knowledge domain, derived from users’ work contexts and evaluating its retrievability and coverage against existing documents as resources of knowledge and information.
C4. Validation of the concept of the recommender system for improving knowledge and information Access in engineering context by developing a system that uses the proposed ontology-based profiling approach and evaluating the performance of the developed system on a case-study.
Består av
Paper 1: Mehrpoor, Mahsa; Gjærde, Andreas; Sivertsen, Ole Ivar. Intelligent Services: A Semantic Recommender System for Knowledge Representation in Industry. I: 2014 International Conference on Engineering, Technology and Innovation (ICE 2014). IEEE conference proceedings - Is not included due to copyright available at https://doi.org/ 10.1109/ICE.2014.6871539Paper 2: Mehrpoor, Mahsa; Gulla, Jon Atle; Ahlers, Dirk; Kristensen, Kjetil; Ghodrat, Soroush; Sivertsen, Ole Ivar. Using Process Ontologies to Contextualize Recommender Systems in Engineering Projects for Knowledge Access Improvement. I: Proceedings of the 16th European Conference on Knowledge Management
Paper 3: Mehrpoor, Mahsa; Ahlers, Dirk; Gulla, Jon Atle; Kristensen, Kjetil; Sivertsen, Ole Ivar. Investigating contextual ontologies and document corpus characteristics for information access in engineering settings. - This is an Accepted Manuscript of an article published by Taylor & Francis Group in Journal of IT Cases and Applications 2017 ;Volum 19.(1) s. 10-33 https://doi.org/10.1080/15228053.2017.1313557
Paper 4: Development and Evaluation of a Knowledge Access System for Engineering Workspaces Based on Recommendation and Filtering - Is not included due to copyright
Paper 5: Ahlers, Dirk; Mehrpoor, Mahsa; Kristensen, Kjetil; Krogstie, John. Challenges for Information Access in Multi-Disciplinary Product Design and Engineering Settings. ICDIM2015 - Is not included due to copyright available at https://doi.org/10.1109/ICDIM.2015.7381865
Paper 6: Ahlers, Dirk; Mehrpoor, Mahsa. Everything is Filed under 'File' — Conceptual Challenges in Applying Semantic Search to Network Shares for Collaborative Work. I: Hypertext'15 Proceedings of the 26th ACM Conference on Hypertext & Social Media - Is not included due to copyright available at https://doi.org/10.1145/2700171.2791046
Paper 7: Kristensen, Kjetil; Krogstie, John; Ahlers, Dirk; Mehrpoor, Mahsa. LEAP Collaboration System. I: Taking the LEAP The Methods and Tools of the Linked Engineering and Manufacturing Platform (LEAP). - Is not included due to copyright available at https://doi.org/10.1016/B978-0-12-805263-1.00005-0