{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T22:35:15Z","timestamp":1776206115792,"version":"3.50.1"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,8]]},"abstract":"<jats:p>The usefulness of tabular data such as web tables critically depends on understanding their semantics. This study focuses on column type prediction for tables without any meta data. Unlike traditional lexical matching-based methods, we propose a deep prediction model that can fully exploit a table\u2019s contextual semantics, including table locality features learned by a Hybrid NeuralNetwork (HNN), and inter-column semantics features learned by a knowledge base (KB) lookup and query answering algorithm. It exhibits good performance not only on individual table sets, but also when transferring from one table set to another.<\/jats:p>","DOI":"10.24963\/ijcai.2019\/289","type":"proceedings-article","created":{"date-parts":[[2019,7,28]],"date-time":"2019-07-28T03:46:05Z","timestamp":1564285565000},"page":"2088-2094","source":"Crossref","is-referenced-by-count":26,"title":["Learning Semantic Annotations for Tabular Data"],"prefix":"10.24963","author":[{"given":"Jiaoyan","family":"Chen","sequence":"first","affiliation":[{"name":"Department of Computer Science, University of Oxford, UK"}]},{"given":"Ernesto","family":"Jimenez-Ruiz","sequence":"additional","affiliation":[{"name":"The Alan Turing Institute, London, UK"},{"name":"Department of Informatics, University of Oslo, Norway"}]},{"given":"Ian","family":"Horrocks","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Oxford, UK"},{"name":"The Alan Turing Institute, London, UK"}]},{"given":"Charles","family":"Sutton","sequence":"additional","affiliation":[{"name":"The Alan Turing Institute, London, UK"},{"name":"School of Informatics, The University of Edinburgh, UK"}]}],"member":"10584","event":{"name":"Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}","theme":"Artificial Intelligence","location":"Macao, China","acronym":"IJCAI-2019","number":"28","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"start":{"date-parts":[[2019,8,10]]},"end":{"date-parts":[[2019,8,16]]}},"container-title":["Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2019,7,28]],"date-time":"2019-07-28T03:48:17Z","timestamp":1564285697000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2019\/289"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2019,8]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2019\/289","relation":{},"subject":[],"published":{"date-parts":[[2019,8]]}}}