Abstract
The bag-of-words model is widely used in many AI applications. In this paper, we propose the task of hierarchical conceptual labeling (HCL), which aims to generate a set of conceptual labels with a hierarchy to represent the semantics of a bag of words. To achieve it, we first propose a denoising algorithm to filter out the noise in a bag of words in advance. Then the hierarchical conceptual labels are generated for a clean word bag based on the clustering algorithm of Bayesian rose tree. The experiments demonstrate the high performance of our proposed framework.
This paper was supported by National Natural Science Foundation of China under No. 61732004.
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Notes
- 1.
In this paper, the words in BoWs are also called instances.
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Jiang, H. et al. (2019). Hierarchical Conceptual Labeling. In: Li, G., Yang, J., Gama, J., Natwichai, J., Tong, Y. (eds) Database Systems for Advanced Applications. DASFAA 2019. Lecture Notes in Computer Science(), vol 11448. Springer, Cham. https://doi.org/10.1007/978-3-030-18590-9_18
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DOI: https://doi.org/10.1007/978-3-030-18590-9_18
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