Web Intelligence
Mining, understanding and personalizing the Web and its content, including language and conversational AI.
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Learning from ideography and labels: a schema-aware radical-guided associative model for Chinese text classification
H Tao, G Zhu, E Chen, S Tong, K Zhang, T Xu, Q Liu, YS Ong. Cited by 5
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Anti-forensic deepfake personas and how to spot them
NH Ngoc, A Chan, HTT Binh, YS Ong. Cited by 4
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Who wants to shop with you: Joint product–participant recommendation for group-buying service
X Sha, Z Sun, J Zhang, YS Ong. Cited by 9
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Momentum contrastive pre-training for question answering
M Hu, M Li, Y Wang, I King. Cited by 5
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Personality is to a Conversational Agent What Perfume is to a Flower
FLI Dutsinma, D Pal, P Roy, H Thapliyal. Cited by 10
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Knowledge-aware neural networks with personalized feature referencing for cold-start recommendation
X Zhang, Y Chen, C Gao, Q Liao, S Zhao, I King. Cited by 19
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Retrieval-augmented multilingual keyphrase generation with retriever-generator iterative training
Y Gao, Q Yin, Z Li, R Meng, T Zhao, B Yin, I King, MR Lyu. Cited by 21
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Multispace evolutionary search for large-scale optimization with applications to recommender systems
L Feng, Q Shang, Y Hou, KC Tan, YS Ong. Cited by 30
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Learning binarized graph representations with multi-faceted quantization reinforcement for top-k recommendation
Y Chen, H Guo, Y Zhang, C Ma, R Tang, J Li, I King. Cited by 45
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Revisiting bundle recommendation: Datasets, tasks, challenges and opportunities for intent-aware product bundling
Z Sun, J Yang, K Feng, H Fang, X Qu, YS Ong. Cited by 47
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Daisyrec 2.0: Benchmarking recommendation for rigorous evaluation
Z Sun, H Fang, J Yang, X Qu, H Liu, D Yu, YS Ong, J Zhang. Cited by 56
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Towards efficient post-training quantization of pre-trained language models
H Bai, L Hou, L Shang, X Jiang, I King, MR Lyu. Cited by 73