TY - GEN
T1 - Utilizing probase in open directory project-based text classification
AU - Jun, So Young
AU - Aliyeva, Dinara
AU - Lee, Ji Min
AU - Lee, Sang-Geun
N1 - Funding Information:
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (number 2015R1A2A1A10052665).
PY - 2018/10/12
Y1 - 2018/10/12
N2 - Open Directory Project (ODP) has been successfully utilized in text classification due to its representation ability of various categories. However, ODP includes a limited number of entities, which play an important role in classification tasks. In this paper, we enrich the semantics of ODP categories with Probase entities. To effectively incorporate Probase entities in ODP categories, we first represent each ODP category and Probase entity in terms of concepts. Next, we measure the semantic relevance between an ODP category and a Probase entity based on the concept vector. Finally, we use Probase entity to enrich the semantics of the ODP categories. Our experimental results show that the proposed methodology exhibits a significant improvement over state-of-the-art techniques in the ODP-based text classification.
AB - Open Directory Project (ODP) has been successfully utilized in text classification due to its representation ability of various categories. However, ODP includes a limited number of entities, which play an important role in classification tasks. In this paper, we enrich the semantics of ODP categories with Probase entities. To effectively incorporate Probase entities in ODP categories, we first represent each ODP category and Probase entity in terms of concepts. Next, we measure the semantic relevance between an ODP category and a Probase entity based on the concept vector. Finally, we use Probase entity to enrich the semantics of the ODP categories. Our experimental results show that the proposed methodology exhibits a significant improvement over state-of-the-art techniques in the ODP-based text classification.
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U2 - 10.1109/FUZZ-IEEE.2018.8491626
DO - 10.1109/FUZZ-IEEE.2018.8491626
M3 - Conference contribution
AN - SCOPUS:85060477192
T3 - IEEE International Conference on Fuzzy Systems
BT - 2018 IEEE International Conference on Fuzzy Systems, FUZZ 2018 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE International Conference on Fuzzy Systems, FUZZ 2018
Y2 - 8 July 2018 through 13 July 2018
ER -