@inproceedings{53f0dfd53a50415c9ac0ac643a3903b2,
title = "Webbrain: Joint neural learning of large-scale commonsense knowledge",
abstract = "Despite the emergence and growth of numerous large knowledge graphs, many basic and important facts about our everyday world are not readily available on the Web. To address this, we present Web- Brain, a new approach for harvesting commonsense knowledge that relies on joint learning from Web-scale data to fill gaps in the knowledge acquisition. We train a neural network model to learn relations based on large numbers of textual patterns found on the Web. At the same time, the model learns vector representations of general word semantics. This joint approach allows us to generalize beyond the explicitly extracted information. Experiments show that we can obtain representations of words that reflect their semantics, yet also allow us to capture conceptual relationships and commonsense knowledge.",
author = "Jiaqiang Chen and Niket Tandon and Hariman, {Charles Darwis} and {de Melo}, Gerard",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2016.; 15th International Semantic Web Conference, ISWC 2016 ; Conference date: 17-10-2016 Through 21-10-2016",
year = "2016",
doi = "10.1007/978-3-319-46523-4_7",
language = "American English",
isbn = "9783319465227",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "102--118",
editor = "Paul Groth and Elena Simperl and Alasdair Gray and Marta Sabou and Markus Krotzsch and Freddy Lecue and Fabian Flock and Yolanda Gil",
booktitle = "The Semantic Web - 15th International Semantic Web Conference, ISWC 2016, Proceedings",
address = "Germany",
}