7 Result(s)
within
Qiong Dai
Information Systems Applications (incl. Internet)
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Chapter and Conference Paper
Multi-order Proximity Graph Structure Embedding
Graph embedding methods convert the flexible graph structure into low-dimensional representations while maintaining the graph structure information. Most existing methods focus on learning low- or high-order g...
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Chapter and Conference Paper
Discriminative Representation Learning for Cross-Domain Sentiment Classification
Cross-domain sentiment classification aims to solve the lack of labeled data in the target domain by using the knowledge of the source domain. Most existing approaches mainly focus on learning transferable fea...
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Chapter and Conference Paper
HEAM: Heterogeneous Network Embedding with Automatic Meta-path Construction
Heterogeneous information network (HIN) embedding is widely used in many real-world applications. Meta-path used in HINs can effectively extract semantic information among objects. However, the meta-path faces...
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Chapter and Conference Paper
Category-Level Adversarial Network for Cross-Domain Sentiment Classification
Cross-domain sentiment classification utilizes useful information in the source domain to improve the sentiment classification accuracy in the target domain which has few or no labeled data. Most existing meth...
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Chapter and Conference Paper
Improving Transformer with Sequential Context Representations for Abstractive Text Summarization
Recent dominant approaches for abstractive text summarization are mainly RNN-based encoder-decoder framework, these methods usually suffer from the poor semantic representations for long sequences. In this pap...
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Chapter and Conference Paper
Triple-Bit Quantization with Asymmetric Distance for Nearest Neighbor Search
Binary embedding is an effective way for nearest neighbor (NN) search as binary code is storage efficient and fast to compute. It tries to convert real-value signatures into binary codes while preserving simi...
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Chapter and Conference Paper
Fast Search of Binary Codes with Distinctive Bits
Although distance between binary codes can be computed fast in hamming space, linear search is not practical for large scale dataset. Therefore attention has been paid to the efficiency of performing approxima...
