Name
Abstract | ||
|---|---|---|
We focus on the problem of interlinking Wikipedia tables with fine-grained table relations: equivalent and subPartOf. Such relations allow us to harness semantically related information by accessing related tables or facts therein. Determining the type of a relation is not trivial. Relations are dependent on the schemas, the cell-values, and the semantic overlap of the cell values in tables.
We propose TableNet, an approach for interlinking tables with subPartOf and equivalent relations. TableNet consists of two main steps: (i) for any source table we provide an efficient algorithm to find candidate related tables with high coverage, and (ii) a neural based approach that based on the table schemas and data, determines with high accuracy the fine-grained relation.
Based on an extensive evaluation with more than 3.2M tables, we show that TableNet retains more than 88% of relevant tables pairs, and assigns table relations with an accuracy of 90%.
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Year | DOI | Venue |
|---|---|---|
2019 | 10.1145/3308558.3313629 | WWW '19: The Web Conference on The World Wide Web Conference WWW 2019 |
DocType | Volume | ISBN |
Journal | abs/1902.01740 | 978-1-4503-6674-8 |
Citations | PageRank | References |
4 | 0.41 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Besnik Fetahu | 1 | 148 | 19.26 |
| Avishek Anand | 2 | 102 | 11.61 |
| Maria Koutraki | 3 | 4 | 0.41 |