By Kaixu Zhang, Jinsong Su, Changle Zhou (auth.), Maosong Sun, Min Zhang, Dekang Lin, Haifeng Wang (eds.)
This publication constitutes the refereed complaints of the twelfth China nationwide convention on Computational Linguistics, CCL 2013, and of the 1st overseas Symposium on ordinary Language Processing in response to certainly Annotated sizeable facts, NLP-NABD 2013, held in Suzhou, China, in October 2013. The 32 papers offered have been conscientiously reviewed and chosen from 252 submissions. The papers are geared up in topical sections on observe segmentation; open-domain query answering; discourse, coreference and pragmatics; statistical and desktop studying equipment in NLP; semantics; textual content mining, open-domain info extraction and computer examining of the net; sentiment research, opinion mining and textual content type; lexical semantics and ontologies; language assets and annotation; computer translation; speech popularity and synthesis; tagging and chunking; and large-scale wisdom acquisition and reasoning.
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Extra info for Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data: 12th China National Conference, CCL 2013 and First International Symposium, NLP-NABD 2013, Suzhou, China, October 10-12, 2013. Proceedings
2. Boundary Segmentation and Manual Segmentation Fig. 3. 3 indicates the good performance in named entity recognition, especially in long sentences, using punctuations and implicit BICs. , are characters (single character word) with strong boundary strength. They are quite worthy to be used in boundary computing. As for future work, it would be natural for researchers to enhance the implicit Natural Annotation utilization as well as modeling both cohesion and autonomy of a string. 3 Segmentation Examples (a) ⊏⌭≁ ᵾ呿 ҄⸣ ᵡ䮅ส ᵾ⪎⧟ ࡈॾ ሹڕ㹼 ᵾዊ оз 俆䜭 ⭼ 㗔Շ ઼ࣣࣘ ⁑㤳 ԓ㺘 а䎧 䗎ᰗ䗾ᯠ (b) ᵜᣕ䇟 ᒯь咔ኡᐲ ⴤ䗮 俉 ҍ嗉Ⲵ 䊚ॾᇒ䖖у㓯 ᰕᔰ 䙊 (c) ⪦᯿㠚⋫৯ ᨀҶ ᡀ Ⲵ㓿傼 (d) ࡊࡊ൘ 㤡ഭ 俆䜭 Ֆᮖ Ѫҹਆ 㤡ഭ ᭯ᓌ 䟺᭮ Ც࡙ ᙫ㔏 Ⳟ䈪࠷⢩ 䘋㹼Ҷ йཙ ⑨䈤 ⍫ࣘⲴ Ც࡙ ཆ䮯 ഐ㣿ቄ㩘 ሶҾ nᰕ 䎦䎤 㾯⨝⢉ 俆䜭 傜ᗧ䟼 Chinese Natural Chunk Research Based on Natural Annotations in Massive Scale Corpora 6 23 Summary and Future Work A natural sentence is made up of words, among which exist cohesion and transition relations.
1 Semi-supervised K-means Cluster To avoid the shortcomings of Brown clustering algorithm, we propose a semisupervised K-means clustering method to map each character to its corresponding concepts based on its context. Chinese Word Segmentation with Character Abstraction 39 Table 1. Top Clusters derived with Brown algorithm. ) 㕆ᓧᕅⸯ䱯ᡚ≹৸ௌᗞࡈޛᗵ㓿ഭेԜˎ䍴ޜ 䗁ڕ੨➔Ժ⭊↖ত⅒ঊᶘг䈎享⍾ѝӜᡁᴸᣅਨ Diﬀerent with unsupervised clustering methods, we ﬁrst use HowNet Knowledge Database as a initial guide for semantic concepts, then we use k-means algorithm to cluster on large-scale unlabeled texts.
References 1. : A hybrid markov/semi-markov conditional random ﬁeld for sequence segmentation. In: Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing, pp. 465–472. Association for Computational Linguistics (2006) 2. : Class-based n-gram models of natural language. Computational Linguistics 18(4), 467–479 (1992) 3. : Discriminative training methods for hidden markov models: Theory and experiments with perceptron algorithms. In: Proceedings of the 2002 Conference on Empirical Methods in Natural Language Processing (2002) 4.