Titlebook: CCKS 2022 - Evaluation Track; 7th China Conference Ningyu Zhang,Meng Wang,Shumin Deng Conference proceedings 2022 The Editor(s) (if applica

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High-Quality Article Classification Based on Named Entities of Knowledge Graph and Multi-head Attend high-quality articles to users. This paper explores how to combine named entities of knowledge graph and multi-head attention mechanism with quality article identification, not only the contents of articles. For the article classification task of CCKS 2022, we proposed an incorporating named entit

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Implementation and Optimization of Graph Computing Algorithms Based on Graph Database,e works can be generalized to graph computing and graph analysis tasks, such as shortest path search, hop-constrained reachability, PageRank, triangle counting, and closeness centrality computation. However, existing graph database query language (SPARQL, Gremlin, etc.) dose not implement these algo

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Knowledge-Enhanced Classification: A Scheme for Identification of High-Quality Articles,s classification problem, from TF-IDF to word2vec, then to RNN and LSTM, and now to transformer-based models, such as Bert, have achieved great improvement in NLU tasks. However, for many specific problems, such as recognition of high-quality article, directly inputting the text content into the tra

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,Learning to Answer Complex Visual Questions from Multi-View Analysis,y used in textbooks such as diagrams often contain complicated and abstract information (e.g. constructed graphs with logic and concepts). Therefore, Diagram Question answering (DQA) is a challenging but significant task, which is also helpful for machines to understand human cognitive behaviors and

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A Prompt-Based UIE Framework,y NLP tasks can be categorized as information extraction tasks, such as named entity extraction (NER), relation extraction (RE), event extraction (EE), etc. To dealing with different IE tasks of different situation, we propose a prompt-based universal information extraction framework which is friend

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,Multi-modal Representation Learning with Self-adaptive Threshold for Commodity Verification,xt. By definition, identical commodities are those that have identical key attributes and are cognitively identical to consumers. There are two main challenges: 1) The extraction and fusion of multi-modal representation. 2) The ability to verify identical commodities by comparing the similarity betw

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