Abstract
The classification of brands refers to classify the brands of products to different categories. It is important in e-commerce and online advertising. Distributed representation is obtained from deep learning, a new area of machine learning research. The main advantage of it is that such a representation can capture various dimensions of both semantic and syntactic information. We use distributed representation to classify brands and compare this method with the approach based on normalized Google distance.
Publisher
Trans Tech Publications, Ltd.
Reference15 articles.
1. A. Z. Broder, Computational advertising and recommender systems, in Proceedings of the 2008 ACM conference on Recommender systems, 2008, pp.1-2.
2. A. Broder, et al., A semantic approach to contextual advertising, in Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval, 2007, pp.559-566.
3. Z. Wu and M. Palmer, Verbs semantics and lexical selection, in Proceedings of the 32nd annual meeting on Association for Computational Linguistics, 1994, pp.133-138.
4. P. Resnik, Using information content to evaluate semantic similarity in a taxonomy, in Proceedings of the 14th International Joint Conference on Artificial Intelligence, 1995, pp.448-453.
5. K. W. Gan and P. W. Wong, Annotating information structures in Chinese texts using HowNet, in Proceedings of the second workshop on Chinese language processing, 2000, pp.85-92.