Paper: What’s in a Domain? Multi-Domain Learning for Multi-Attribute Data

ACL ID N13-1080
Title What’s in a Domain? Multi-Domain Learning for Multi-Attribute Data
Venue Annual Conference of the North American Chapter of the Association for Computational Linguistics
Session Main Conference
Year 2013
Authors

Multi-Domain learning assumes that a sin- gle metadata attribute is used in order to di- vide the data into so-called domains. How- ever, real-world datasets often have multi- ple metadata attributes that can divide the data into domains. It is not always apparent which single attribute will lead to the best do- mains, and more than one attribute might im- pact classification. We propose extensions to two multi-domain learning techniques for our multi-attribute setting, enabling them to si- multaneously learn from several metadata at- tributes. Experimentally, they outperform the multi-domain learning baseline, even when it selects the single ?best? attribute.