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Recognizing cross-lingual textual entailment with co-training using similarity and difference views., , , and . IJCNN, page 3705-3712. IEEE, (2014)Measuring short Text Semantic Similarity using multiple measurements., and . ICMLC, page 808-813. IEEE, (2013)Towards a One-stop Solution to Both Aspect Extraction and Sentiment Analysis Tasks with Neural Multi-task Learning., , and . IJCNN, page 1-8. IEEE, (2018)A comprehensive comparative study on term weighting schemes for text categorization with support vector machines., , , and . WWW (Special interest tracks and posters), page 1032-1033. ACM, (2005)Memory-Based Model with Multiple Attentions for Multi-turn Response Selection., , and . ICONIP (2), volume 11302 of Lecture Notes in Computer Science, page 296-307. Springer, (2018)MRAEA: An Efficient and Robust Entity Alignment Approach for Cross-lingual Knowledge Graph., , , , and . WSDM, page 420-428. ACM, (2020)A Simple Temporal Information Matching Mechanism for Entity Alignment between Temporal Knowledge Graphs., , , , , and . COLING, page 2075-2086. International Committee on Computational Linguistics, (2022)The Integration of Multiple Feature Representations for Protein Protein Interaction Classification Task., and . LBM (Short Papers), volume 319 of CEUR Workshop Proceedings, CEUR-WS.org, (2007)Extracting Entities and Relations with Joint Minimum Risk Training., , , , , , and . EMNLP, page 2256-2265. Association for Computational Linguistics, (2018)LightEA: A Scalable, Robust, and Interpretable Entity Alignment Framework via Three-view Label Propagation., , , and . EMNLP, page 825-838. Association for Computational Linguistics, (2022)