Xiao Luo


2022

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AGRank: Augmented Graph-based Unsupervised Keyphrase Extraction
Haoran Ding | Xiao Luo
Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)

Keywords or keyphrases are often used to highlight a document’s domains or main topics. Unsupervised keyphrase extraction (UKE) has always been highly anticipated because no labeled data is needed to train a model. This paper proposes an augmented graph-based unsupervised model to identify keyphrases from a document by integrating graph and deep learning methods. The proposed model utilizes mutual attention extracted from the pre-trained BERT model to build the candidate graph and augments the graph with global and local context nodes to improve the performance. The proposed model is evaluated on four publicly available datasets against thirteen UKE baselines. The results show that the proposed model is an effective and robust UKE model for long and short documents. Our source code is available on GitHub.

2021

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AttentionRank: Unsupervised Keyphrase Extraction using Self and Cross Attentions
Haoran Ding | Xiao Luo
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

Keyword or keyphrase extraction is to identify words or phrases presenting the main topics of a document. This paper proposes the AttentionRank, a hybrid attention model, to identify keyphrases from a document in an unsupervised manner. AttentionRank calculates self-attention and cross-attention using a pre-trained language model. The self-attention is designed to determine the importance of a candidate within the context of a sentence. The cross-attention is calculated to identify the semantic relevance between a candidate and sentences within a document. We evaluate the AttentionRank on three publicly available datasets against seven baselines. The results show that the AttentionRank is an effective and robust unsupervised keyphrase extraction model on both long and short documents. Source code is available on Github.

2018

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A Study on the Korean and Chinese Pronunciation of Chinese Characters and Learning Korean as a Second Language
Xiao Luo | Yike Yang | Jing Sun
Proceedings of the 32nd Pacific Asia Conference on Language, Information and Computation

2002

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Covering Ambiguity Resolution in Chinese Word Segmentation Based on Contextual Information
Xiao Luo | Maosong Sun | Benjamin K. Tsou
COLING 2002: The 19th International Conference on Computational Linguistics