By Maosong Sun, Yang Liu, Jun Zhao (eds.)
This ebook constitutes the refereed lawsuits of the thirteenth China nationwide convention on Computational Linguistics, CCL 2014, and of the 1st foreign Symposium on common Language Processing in accordance with evidently Annotated gigantic info, NLP-NABD 2014, held in Wuhan, China, in October 2014. The 27 papers provided have been rigorously reviewed and chosen from 233 submissions. The papers are prepared in topical sections on observe segmentation; syntactic research and parsing the internet; semantics; discourse, coreference and pragmatics; textual entailment; language assets and annotation; sentiment research, opinion mining and textual content class; large‐scale wisdom acquisition and reasoning; textual content mining, open IE and computing device examining of the internet; laptop translation; multilinguality in NLP; underresourced languages processing; NLP applications.
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Extra info for Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data: 13th China National Conference, CCL 2014, and Second International Symposium, NLP-NABD 2014, Wuhan, China, October 18-19, 2014. Proceedings
This is because the artistic creation was signiﬁcantly inﬂuenced by ideological factors in the Cultural Revolution (1967-1977) but reached its peak accompanying economic development. This analysis illustrates that the frequency change of topics can reﬂect the culture change. 32 N. Sun et al.
Fig. 5. The normalized frequency of the cluster “话 剧(drama), 作 品(words), 创 作(creation), 戏剧(drama), 文学(literature), 演员(actor), 音乐(music), 连环画(comic strip), 绘 画(drawing), 语 言(language), 诗 歌(poetry), 故 事(story), 诗 人(poet), 杂 技(acrobatics), 现 实 主 义(realism), 文 艺(literature and art), 作 家(writer), 电 影(movie), 油画(painting), 歌剧(opera), 影片(ﬁlm), 民歌(folk song), 小说(novel), 纪 录片(documentary), 美术(art), 编排(arrange), 艺术(art), 鲁迅(Xun Lu)” (blue line) compare with the frequency of the cluster of exploiting class and revolution (red line).
Table 4. Accuracy on test set, excluding punctuation, for unlabeled attachment score (UAS), labeled attachment score (LAS) and Complete Match (CM) Maltparser Top CoNLL 2009 (Transition-based) Che et al. 11 6 Related Works Yamada and Matsumoto  is in the light of the target nodes, and determines what kind of action to do. This can be treated as a multi-class classification problem. It also Improving Multi-pass Transition-Based Dependency Parsing 21 uses the the left and right context information of the target nodes and their children’s information to exclude ambiguity.
In: Proceedings of the Thirteenth Conference on Computational Natural Language Learning: Shared Task, pp. 97–102. : Vine pruning for efficient multi-pass dependency parsing. In: Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 498–507. : A transition-based dependency parser using a dynamic parsing strategy. : Statistical dependency analysis with support vector machines. In: Proceedings of the International Workshop on Parsing Technologies (IWPT), vol.