Abstract
Knowledge graphs have been used in a wide range of applications to support search, recommendation, and question answering (Q&A). For example, in Q&A systems, given a new question, we may use a knowledge graph to automatically identify the most suitable answers based on similarity evaluation. However, such systems may suffer from two major limitations. First, the knowledge graph constructed based on source data may contain errors. Second, the knowledge graph may become out of date and cannot quickly adapt to new knowledge. To address these issues, in this paper, we propose an interactive framework that refines and optimizes knowledge graphs through user votes. We develop an efficient similarity evaluation notion, called extended inverse P-distance, based on which the graph optimization problem can be formulated as a signomial geometric programming problem. We then propose a basic single-vote solution and a more advanced multi-vote solution for graph optimization. We also propose a split-and-merge optimization strategy to scale up the multi-vote solution. Extensive experiments based on real-life and synthetic graphs demonstrate the effectiveness and efficiency of our proposed framework.
Original language | English |
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Title of host publication | Proceedings - 2020 IEEE 36th International Conference on Data Engineering, ICDE 2020 |
Publisher | IEEE Computer Society |
Pages | 421-432 |
Number of pages | 12 |
ISBN (Electronic) | 9781728129037 |
DOIs | |
Publication status | Published - Apr 2020 |
Event | 36th IEEE International Conference on Data Engineering, ICDE 2020 - Dallas, United States Duration: 20 Apr 2020 → 24 Apr 2020 https://ieeexplore.ieee.org/xpl/conhome/9093725/proceeding (Link to conference proceedings) |
Publication series
Name | Proceedings - International Conference on Data Engineering |
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Volume | 2020-April |
ISSN (Print) | 1084-4627 |
Conference
Conference | 36th IEEE International Conference on Data Engineering, ICDE 2020 |
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Country/Territory | United States |
City | Dallas |
Period | 20/04/20 → 24/04/20 |
Internet address |
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Scopus Subject Areas
- Software
- Signal Processing
- Information Systems
User-Defined Keywords
- Data Cleaning
- Knowledge Graphs
- Query Processing
- Question Answering