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Towards a knowledge graph-based approach for context-aware points-of-interest recommendations

Published: 22 April 2021 Publication History

Abstract

Context-aware Recommender Systems (CARS) are becoming an integral part of the everyday life by providing users the ability to retrieve relevant information based on their contextual situation. To increase the predictive power considering many parameters, such as mood, hunger level and user preferences, information from heterogeneous sources should be leveraged. However, these data sources are typically isolated and unexplored and the efforts for integrating them are exacerbated by variety of data structures used for their modelling and costly pre-processing operations. We propose a Knowledge Graph-based approach to allow integration of data according to abstract semantic models for Points-of-Interests (POI)s recommendation scenarios. By enriching data with information about attributes, relationships and their meaning, additional knowledge can be derived from what already exists. We demonstrate the applicability of the proposed approach with a concrete example showing benefits of the retrieving the dispersed data with a unified access mechanism.

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Cited By

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  • (2024)SemanticFormer: Holistic and Semantic Traffic Scene Representation for Trajectory Prediction Using Knowledge GraphsIEEE Robotics and Automation Letters10.1109/LRA.2024.34263869:9(7381-7388)Online publication date: Sep-2024
  • (2022)A Survey on Knowledge Graph-Based Methods for Automated DrivingKnowledge Graphs and Semantic Web10.1007/978-3-031-21422-6_2(16-31)Online publication date: 13-Nov-2022

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cover image ACM Conferences
SAC '21: Proceedings of the 36th Annual ACM Symposium on Applied Computing
March 2021
2075 pages
ISBN:9781450381048
DOI:10.1145/3412841
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 22 April 2021

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Author Tags

  1. context-aware POI recommendations
  2. knowledge graphs
  3. ontology-based data integration

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SAC '21
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SAC '21: The 36th ACM/SIGAPP Symposium on Applied Computing
March 22 - 26, 2021
Virtual Event, Republic of Korea

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Cited By

View all
  • (2024)SemanticFormer: Holistic and Semantic Traffic Scene Representation for Trajectory Prediction Using Knowledge GraphsIEEE Robotics and Automation Letters10.1109/LRA.2024.34263869:9(7381-7388)Online publication date: Sep-2024
  • (2022)A Survey on Knowledge Graph-Based Methods for Automated DrivingKnowledge Graphs and Semantic Web10.1007/978-3-031-21422-6_2(16-31)Online publication date: 13-Nov-2022

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