Published November 8, 2017
| Version v1
Poster
Open
Applying Situation-Person-Driven Semantic Similarity On Location-Specific Cognitive Frames For Improving Location Prediction
Authors/Creators
- 1. Robert Bosch GmbH and Karlsruhe Institute of Technology (KIT)
- 2. Karlsruhe Institute of Technology (KIT)
Description
In this paper, within the scope of optimizing location prediction systems and in line with the Ontology Design Pattern technique, we propose a way to encapsulate the user's transient experience when visiting locations into n-ary relational objects, which we call Location-Specific Cognitive Frames.
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KESW2017_AntoniosKaratzoglou_zenodo.pdf
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Additional details
Related works
- Is identical to
- 10.13140/RG.2.2.15120.51209 (DOI)
References
- Karatzoglou, A., Sentürk, H., Jablonski, A., Beigl, M.: Applying Articial Neural Networks on Two-Layer Semantic Trajectories for Predicting the Next Semantic Location. Proc. 26th ICANN, (2017)
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- Ashbrook, Daniel and Starner, Thad: Using GPS to learn significant locations and predict movement across multiple users. PUC Vol.7, Nr.5, 275–286, (2003)
- Wannous, R., Malki, J., Boujou A., Vincent, C.: Modelling mobile object activities based on trajectory ontology rules considering spatial relationship rules. Modeling approaches and algorithms for advanced computer applications, 249-258 (2013)