Titlebook: Database Systems for Advanced Applications; 26th International C Christian S. Jensen,Ee-Peng Lim,Chih-Ya Shen Conference proceedings 2021 T

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Unpaired Multimodal Neural Machine Translation via Reinforcement Learning to collect. To tackle this problem, multimodal content, especially image, has been introduced to help build an NMT system without parallel corpora. In this paper, we propose a reinforcement learning (RL) method to build an NMT system by introducing a sequence-level supervision signal as a reward. B

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Multimodal Named Entity Recognition with Image Attributes and Image Knowledgety types. The existing efforts are often flawed in two aspects. Firstly, they may easily ignore the natural prejudice of visual guidance brought by the image. Secondly, they do not further explore the knowledge contained in the image. In this paper, we novelly propose a novel neural network model wh

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A Semi-structured Data Classification Model with Integrating Tag Sequence and Ngramfication plays an important role in many data analysis applications. In addition to content information, semi-structured data also contain structural information. Thus, combining the structure and content features is a crucial issue in semi-structured data classification. In this paper, we propose a

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Inferring Deterministic Regular Expression with Unorder and Countingn this paper, schemata are inferred from unordered XML documents. We extend the single-occurrence regular expressions (SOREs) to single-occurrence regular expressions with unorder and counting (SOREUCs), and give an inference algorithm for SOREUCs. First, we present a . (FAUC). Then, we construct an

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