Demand-Weighted Completeness Prediction for a Knowledge Base Article Swipe
Andrew Hopkinson
,
Amit Gurdasani
,
Dave Palfrey
,
Arpit Mittal
·
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.18653/v1/n18-3025
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.18653/v1/n18-3025
In this paper we introduce the notion of Demand-Weighted Completeness, allowing estimation of the completeness of a knowledge base with respect to how it is used. Defining an entity by its classes, we employ usage data to predict the distribution over relations for that entity. For example, instances of person in a knowledge base may require a birth date, name and nationality to be considered complete. These predicted relation distributions enable detection of important gaps in the knowledge base, and define the required facts for unseen entities. Such characterisation of the knowledge base can also quantify how usage and completeness change over time. We demonstrate a method to measure Demand-Weighted Completeness, and show that a simple neural network model performs well at this prediction task.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.18653/v1/n18-3025
- https://www.aclweb.org/anthology/N18-3025.pdf
- OA Status
- gold
- Cited By
- 5
- References
- 14
- Related Works
- 20
- OpenAlex ID
- https://openalex.org/W2799150749
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2799150749Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.18653/v1/n18-3025Digital Object Identifier
- Title
-
Demand-Weighted Completeness Prediction for a Knowledge BaseWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2018Year of publication
- Publication date
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2018-01-01Full publication date if available
- Authors
-
Andrew Hopkinson, Amit Gurdasani, Dave Palfrey, Arpit MittalList of authors in order
- Landing page
-
https://doi.org/10.18653/v1/n18-3025Publisher landing page
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https://www.aclweb.org/anthology/N18-3025.pdfDirect link to full text PDF
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://www.aclweb.org/anthology/N18-3025.pdfDirect OA link when available
- Concepts
-
Completeness (order theory), Computer science, Knowledge base, Artificial intelligence, Base (topology), Data mining, Measure (data warehouse), Relation (database), Machine learning, Mathematics, Mathematical analysisTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
5Total citation count in OpenAlex
- Citations by year (recent)
-
2021: 3, 2020: 2Per-year citation counts (last 5 years)
- References (count)
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14Number of works referenced by this work
- Related works (count)
-
20Other works algorithmically related by OpenAlex
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| abstract_inverted_index.characterisation | 88 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 94 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 4 |
| citation_normalized_percentile.value | 0.7961138 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |