Abstract | ||
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A large number of HTML Tables on the Web contain relational data which can be used to augment knowledge bases such as DB-pedia, Yago, or Wikidata. A large part of this data is time-dependent, i.e., the correctness of a fact depends on a specific temporal scope. In order to use this data for knowledge base augmentation, we need temporal meta-information. Existing methods rely on timestamps within the table itself or its context as temporal meta-information. Yet, the relationship between these timestamps and data within a table is often unclear. Additionally, timestamps are rather sparse, and there are many web tables for which no timestamps exist. Knowledge-Based-Trust (KBT) uses the overlap with ground-truth to estimate the trustworthiness of a dataset. This paper introduces Timed-KBT, which overcomes the dependence on sparse and possibly misinterpreted timestamps by propagating temporal meta-information from a knowledge base to web table data using KBT. It also derives a trust score that estimates the correctness of the data and the assigned temporal meta-information. We evaluate Timed-KBT on the use case of fusing data from a large corpus of web tables for filling missing facts in a knowledge base. Our evaluation shows that Timed-KBT yields an increase in F-0.25-Measure of 19.01 % when compared to KBT and 9.44 % when compared to a method that relies solely on timestamps extracted from the table and its context. |
Year | Venue | DocType |
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2017 | CEUR Workshop Proceedings-Series | Conference |
Volume | ISSN | Citations |
1959 | 1613-0073 | 0 |
PageRank | References | Authors |
0.34 | 0 | 2 |
Name | Order | Citations | PageRank |
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Yaser Oulabi | 1 | 19 | 1.38 |
Christian Bizer | 2 | 8448 | 524.93 |