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Titlebook: Computational Linguistics and Intelligent Text Processing; 14th International C Alexander Gelbukh Conference proceedings 2013 Springer-Verl

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發(fā)表于 2025-3-21 19:44:19 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱(chēng)Computational Linguistics and Intelligent Text Processing
副標(biāo)題14th International C
編輯Alexander Gelbukh
視頻videohttp://file.papertrans.cn/233/232604/232604.mp4
概述Up-to-date results in computational linguistics and intelligent text processing.Fast-track conference proceedings.State-of-the-art research
叢書(shū)名稱(chēng)Lecture Notes in Computer Science
圖書(shū)封面Titlebook: Computational Linguistics and Intelligent Text Processing; 14th International C Alexander Gelbukh Conference proceedings 2013 Springer-Verl
描述This two-volume set, consisting of LNCS 7816 and LNCS 7817, constitutes the thoroughly refereed proceedings of the 13th International Conference on Computer Linguistics and Intelligent Processing, CICLING 2013, held on Samos, Greece, in March 2013. The total of 91 contributions presented was carefully reviewed and selected for inclusion in the proceedings. The papers are organized in topical sections named: general techniques; lexical resources; morphology and tokenization; syntax and named entity recognition; word sense disambiguation and coreference resolution; semantics and discourse; sentiment, polarity, subjectivity, and opinion; machine translation and multilingualism; text mining, information extraction, and information retrieval; text summarization; stylometry and text simplification; and applications.
出版日期Conference proceedings 2013
關(guān)鍵詞controlled natural language; dependency grammar; multilingual ontologies; semantic networks; unsupervise
版次1
doihttps://doi.org/10.1007/978-3-642-37256-8
isbn_softcover978-3-642-37255-1
isbn_ebook978-3-642-37256-8Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2013
The information of publication is updating

書(shū)目名稱(chēng)Computational Linguistics and Intelligent Text Processing影響因子(影響力)




書(shū)目名稱(chēng)Computational Linguistics and Intelligent Text Processing影響因子(影響力)學(xué)科排名




書(shū)目名稱(chēng)Computational Linguistics and Intelligent Text Processing網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱(chēng)Computational Linguistics and Intelligent Text Processing網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱(chēng)Computational Linguistics and Intelligent Text Processing被引頻次




書(shū)目名稱(chēng)Computational Linguistics and Intelligent Text Processing被引頻次學(xué)科排名




書(shū)目名稱(chēng)Computational Linguistics and Intelligent Text Processing年度引用




書(shū)目名稱(chēng)Computational Linguistics and Intelligent Text Processing年度引用學(xué)科排名




書(shū)目名稱(chēng)Computational Linguistics and Intelligent Text Processing讀者反饋




書(shū)目名稱(chēng)Computational Linguistics and Intelligent Text Processing讀者反饋學(xué)科排名




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Lili Yang,Soyoung Lee,Yusuf Ikbal Oldac interact better with users. Nevertheless, it seems that no previous published study has assessed whether the position of individual texts within on-going communication can be exploited to help detect their sentiments. This article assesses apparent sentiment anomalies in on-going communication – te
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Lili Yang,Soyoung Lee,Yusuf Ikbal Oldactext contents and extract the opinion of the users. In this paper, . and .-. are extracted from the text, and composite features are created using them. Part of Speech (POS) based features adjectives and adverbs are also extracted. Information Gain (IG) and Minimum Redundancy Maximum Relevancy (mRMR
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Sandra Hummel,Mana-Teresa Donneruch applications. This growing demand is supported by an increasing amount and availability of opinionated online information, mainly due to the proliferation and popularity of social media. The majority of work in sentiment analysis considers the polarity of word terms rather than the polarity of s
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Sandra Hummel,Mana-Teresa Donnerlysis. In this paper, we propose a multilingual approach for word polarity detection. We construct a word relatedness graph by using the relations in WordNet of a given language. We extend the graph by connecting the WordNets of different languages with the help of the Inter-Lingual-Index based on E
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