Khizer Syed
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Research Areas
Biography and Research Information
OverviewAI-generated summary
Khizer Syed's research focuses on advancing entity resolution methodologies, particularly in contexts involving dynamic data such as household movement. His recent publications explore novel approaches to improve the accuracy and efficiency of identifying and linking records that represent the same real-world entity. This includes developing new metrics for comparative analysis of entity resolution results, such as the case count metric, and investigating the utility of generative AI, like Google Generative AI, for tasks such as household movement discovery.
Syed also investigates the application of graph-based structures, specifically group membership graphs, for enhancing household discovery. His work on name and address parsing incorporates pattern-based strategies and active learning to refine data processing. With an h-index of 2 and 7 total publications, his work contributes to the field of data management and information retrieval, aiming to improve the quality and coherence of datasets.
Metrics
- h-index: 2
- Publications: 7
- Citations: 13
Selected Publications
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Case count metric for comparative analysis of entity resolution results (2026)
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Entity Resolution with Household Movement Discovery Using Google Generative AI (2025)
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Improving Quality of Entity Resolution Using a Cascade Approach (2025)
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A Pattern-Based Approach to Name and Address Parsing with Active Learning (2025)
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Household Discovery with Group Membership Graphs (2024)
Collaboration Network
Top Collaborators
- Entity Resolution with Household Movement Discovery Using Google Generative AI
- Household Discovery with Group Membership Graphs
- A Pattern-Based Approach to Name and Address Parsing with Active Learning
- Improving Quality of Entity Resolution Using a Cascade Approach
- Case count metric for comparative analysis of entity resolution results
- Household Discovery with Group Membership Graphs
- A Pattern-Based Approach to Name and Address Parsing with Active Learning
- Household Discovery with Group Membership Graphs
- A Pattern-Based Approach to Name and Address Parsing with Active Learning
- Improving Quality of Entity Resolution Using a Cascade Approach
- Entity Resolution with Household Movement Discovery Using Google Generative AI
- Case count metric for comparative analysis of entity resolution results
- Household Discovery with Group Membership Graphs
- A Pattern-Based Approach to Name and Address Parsing with Active Learning
- A Pattern-Based Approach to Name and Address Parsing with Active Learning
- A Pattern-Based Approach to Name and Address Parsing with Active Learning
- Case count metric for comparative analysis of entity resolution results
- Case count metric for comparative analysis of entity resolution results
- Case count metric for comparative analysis of entity resolution results
- Case count metric for comparative analysis of entity resolution results
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