Abstract
Traditional Open Directory Project (ODP)-based text classification methods effectively capture topics of texts by utilizing the hierarchical structure of explicitly human-built knowledge base. However, they only consider term weighting approaches, ignoring the important semantic similarity between words. In this paper, we consider the semantics of words by incorporating the implicit text representation, such as word2vec word embeddings, into the ODP-based text classification. In contrast to common usage of word2vec, we utilize the input and output vectors. This allows us to calculate a combined typical and topical similarity between words of category and document, which is more effective at text classification. To this end, we first incorporate the dual word embeddings of word2vec into the ODP-based text classification to obtain semantically richer category and document representations. Subsequently, we use the combination of the input and output vectors to improve the semantic similarity between category and document. Our evaluation results using a real-world dataset show the efficacy of our proposed approach, exhibiting a significant improvement of 9% and 37% in terms of Fl-score and precision at k, over the state-of-the-art techniques.
Original language | English |
---|---|
Title of host publication | Proceedings of 2018 IEEE 17th International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2018 |
Editors | Newton Howard, Sam Kwong, Yingxu Wang, Jerome Feldman, Bernard Widrow, Phillip Sheu |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 179-186 |
Number of pages | 8 |
ISBN (Electronic) | 9781538633601 |
DOIs | |
Publication status | Published - 2018 Oct 4 |
Event | 17th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2018 - Berkeley, United States Duration: 2018 Jul 16 → 2018 Jul 18 |
Publication series
Name | Proceedings of 2018 IEEE 17th International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2018 |
---|
Other
Other | 17th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2018 |
---|---|
Country/Territory | United States |
City | Berkeley |
Period | 18/7/16 → 18/7/18 |
Bibliographical note
Publisher Copyright:© 2018 IEEE.
Keywords
- Machine Learning
- Text Classification
- Word embeddings
ASJC Scopus subject areas
- Artificial Intelligence
- Information Systems
- Cognitive Neuroscience