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ECNU: Effective Semantic Relations Classification without Complicated Features or Multiple External Corpora.

, , , , and . SemEval@ACL, page 226-229. The Association for Computer Linguistics, (2010)

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ECNUCS: Recognizing Cross-lingual Textual Entailment Using Multiple Text Similarity and Text Difference Measures., , and . SemEval@NAACL-HLT, page 118-123. The Association for Computer Linguistics, (2013)ECNU at SemEval-2018 Task 12: An End-to-End Attention-based Neural Network for the Argument Reasoning Comprehension Task., , and . SemEval@NAACL-HLT, page 1094-1098. Association for Computational Linguistics, (2018)Are Negative Samples Necessary in Entity Alignment?: An Approach with High Performance, Scalability and Robustness., , , and . CIKM, page 1263-1273. ACM, (2021)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)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)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)Single turn Chinese emotional conversation generation based on information retrieval and question answering., , , and . IALP, page 103-106. IEEE, (2017)MRAEA: An Efficient and Robust Entity Alignment Approach for Cross-lingual Knowledge Graph., , , , and . WSDM, page 420-428. ACM, (2020)