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16th APWeb Workshops

作者： Su, Ziyan Zhou, Bin Li, Aiping Han, Yi Natl Univ Def Technol Coll Comp Changsha Hunan Peoples R China

ISBN: (纸本)9783319111193;9783319111186

Analysis on microblog sentiment is very important for microblog monitoring and guidance of public opinion. According to the problem that precision of Chinese microblog sentiment analysis was low, this paper proposed a model for analysis on Chinese microblog sentiment based on syntax parsing and the support vector machine algorithm. Firstly, this paper built a fundamental dictionary of emotion based on existing emotional words resources, and expanded the dictionary by computing similarity of words. Then, it computed emotional values of microblogs by syntax parsing and judged their emotional tendencies. Finally, it selected a certain percentage of positive and negative emotional microblogs as a training set. It utilized the support vector machine algorithm to classify microblogs that didn't belong to the training set and got all emotional tendencies of microblogs. Experimental results showed that the model proposed by this paper could achieve 77.3% precision. So the model is effective.

关键词： fundamental emotional dictionary word similarity calculation syntax parsing training set selection support vector machine

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A survey of syntactic-semantic parsing based on constituent and dependency structures

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Science China(Technological Sciences) 2020年第10期63卷 1898-1920页

作者： ZHANG MeiShan School of New Media and Communication Tianjin UniversityTianjin 300072China

Syntactic and semantic parsing has been investigated for decades,which is one primary topic in the natural language processing *** article aims for a brief survey on this *** parsing community includes many tasks,which are difficult to be covered *** we focus on two of the most popular formalizations of parsing:constituent parsing and dependency *** parsing is majorly targeted to syntactic analysis,and dependency parsing can handle both syntactic and semantic *** article briefly reviews the representative models of constituent parsing and dependency parsing,and also dependency graph parsing with rich ***,we also review the closely-related topics such as cross-domain,cross-lingual and joint parsing models,parser application as well as corpus development of parsing in the article.

关键词： syntax parsing semantic parsing constituent parsing dependency parsing semantic graph parsing

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Emergence of cognitive priming and structure building from the hierarchical interaction of canonical microcircuit models

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BIOLOGICAL CYBERNETICS 2019年第3期113卷 273-291页

作者： Kunze, Tim Haueisen, Jens Knoesche, Thomas R. Max Planck Inst Human Cognit & Brain Sci Leipzig Germany Ilmenau Univ Technol Inst Biomed Engn & Informat Ilmenau Germany

The concept of connectionism states that higher cognitive functions emerge from the interaction of many simple elements. Accordingly, research on canonical microcircuits conceptualizes findings on fundamental neuroanatomical circuits as well as recurrent organizational principles of the cerebral cortex and examines the link between architectures and their associated functionality. In this study, we establish minimal canonical microcircuit models as elements of hierarchical processing networks. Based on a combination of descriptive time simulations and explanatory state-space mappings, we show that minimal canonical microcircuits effectively segregate feedforward and feedback information flows and that feedback information conditions basic processing operations in minimal canonical microcircuits. Further, we derive and examine two prototypical meta-circuits of cooperating minimal canonical microcircuits for the neurocognitive problems of priming and structure building. Through the application of these findings to a language network of syntax parsing, this study embodies neurocognitive research on hierarchical communication in light of canonical microcircuits, cell assembly theory, and predictive coding.

关键词： Canonical microcircuit Hierarchical model Neural computations Adaptive mechanisms State-dependent operation syntax parsing

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Graph-Based Lexicon Regularization for PCFG With Latent Annotations

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IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING 2015年第3期23卷 441-450页

作者： Zeng, Xiaodong Wong, Derek F. Chao, Lidia S. Trancoso, Isabel Univ Macau Dept Comp & Informat Sci Lab NLP2CT Macau Peoples R China Univ Lisbon Inst Super Tecn INESC ID P-1000029 Lisbon Portugal

This paper aims at learning a better probabilistic context-free grammar with latent annotations (PCFG-LA) by using a graph propagation (GP) technique. We propose leveraging the GP to regularize the lexical model of the grammar. The proposed approach constructs k-nearest neighbor (k-NN) similarity graphs over words with identical pre-terminal (part-of-speech) tags, for propagating the probabilities of latent annotations given the words. The graphs demonstrate the relationship between words in syntactic and semantic levels, estimated by using a neural word representation method based on Recursive autoencoder (RAE). We modify the conventional PCFG-LA parameter estimation algorithm, expectation maximization (EM), by incorporating a GP process subsequent to the M-step. The GP encourages the smoothness among the graph vertices, where different words under similar syntactic and semantic environments should have approximate posterior distributions of nonterminal subcategories. The proposed PCFG-LA learning approach was evaluated together with a hierarchical split-and-merge training strategy, on parsing tasks for English, Chinese and Portuguese. The empirical results reveal two crucial findings: 1) regularizing the lexicons with GP results in positive effects to parsing accuracy;and 2) learning with unlabeled data can also expand the PCFG-LA lexicons.

关键词： Graph propagation natural language processing neural word representation syntax parsing

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Lexicon expansion for latent variable grammars

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PATTERN RECOGNITION LETTERS 2014年第1期42卷 47-55页

作者： Zeng, Xiaodong Wong, Derek F. Chao, Lidia S. Trancoso, Isabel He, Liangye Huang, Qiuping Univ Macau Dept Comp & Informat Sci NLP2CT Macau Peoples R China Inst Super Tecn INESC ID Lisbon Portugal

This study investigates the use of unlabeled data, i.e., raw texts, to strengthen latent variable probabilistic context-free grammars, in particular lexical models. A graph-based lexicon expansion approach is proposed to achieve this goal. It aims to discover additional lexical knowledge from a large amount of unlabeled data to help the syntax parsing. The proposed approach is based on a transductive graph-based label propagation technique. The approach builds k-nearest-neighbor (k-NN) similarity graphs over the words of labeled and unlabeled data, for propagating lexical emission probabilities. The intuition is that different word under similar syntactic environment should have approximate lexical emission distributions. The derived words, together with lexical emission probabilities, are incorporated into the parsing. This approach is very effective in parsing out-of-vocabulary (OOV) words. Empirical results for English, Chinese, and Portuguese revealed its effectiveness. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Latent variable grammar syntax parsing Graph-based label propagation

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A Highly Efficient VLSI Architecture for H.264/AVC Level 5.1 CABAC Decoder

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2012年第2期22卷 272-281页

作者： Liao, Yuan-Hsin Li, Gwo-Long Chang, Tian-Sheuan PixArt Imagine Inc Hsinchu 300 Taiwan Natl Chiao Tung Univ Dept Elect Engn Hsinchu 300 Taiwan

In this paper, a high throughput context-based adaptive binary arithmetic coding decoder design is proposed. This decoder employs a syntax element prediction method to solve pipeline hazard problems. It also uses a new hybrid memory two-symbol parallel decoding in order to enhance performance as well as to reduce costs. The critical path delay of the two-symbol binary arithmetic decoding engine is improved by 28% with an efficient mathematical transform. Experimental results show that the throughput of our proposed design can reach 485.76 Mbins/s in the high bit-rate coding and 446.2 Mbins/s on average at 264MHz operating frequency, which is sufficient to support H.264/AVC level 5.1 real-time decoding.

关键词： Binary arithmetic coding CABAC entropy decoding H.264/AVC syntax parsing

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Automatic Synthesis of Parsers and Validation of Bitstreams Within the MPEG Reconfigurable Video Coding Framework

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JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY 2011年第2期63卷 215-225页

作者： Lucarz, Christophe Piat, Jonathan Mattavelli, Marco Ecole Polytech Fed Lausanne Multimedia Architectures Res Grp Microelect Syst Lab Lausanne Switzerland IETR INSA Rennes F-35043 Rennes France

Video coding technology has evolved in the past years into a variety of different and complex algorithms. So far the specifications of such standard algorithms have been done case by case, providing monolithic textual and reference software specifications, but without paying any attention to the possibility of further improvements of such monolithic standards. The MPEG Reconfigurable Video Coding (RVC) framework is a new ISO/IEC standard, currently under its final stage of development aiming at providing video codec specifications at the level of coding tools instead of monolithic descriptions. The possibility to select a subset of standard video coding algorithms to specify a decoder that satisfies application specific constraints is very attractive. However, such possibility to reconfigure codecs requires systematic procedures and tools capable of describing the new bitstream syntaxes of such new codecs. Moreover, it becomes also necessary to generate the associated parsers, capable of parsing the new bitstreams. This paper further explains the problem and describes the technologies used to describe new bitstream syntaxes. Additionally, the paper describes the methodologies and the tools for the validation of bitstream syntaxes descriptions as well as a systematic procedure for automatically synthesizing parsers from the bitstream descriptions.

关键词： Reconfigurable video coding RVC MPEG syntax parsing Dataflow models CAL

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Latent Syntactic Structure-Based Sentiment Analysis 2

Latent Syntactic Structure-Based Sentiment Analysis

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2nd IEEE International Conference on Computational Intelligence and Applications (ICCIA)

作者： Hangya, Viktor Szanto, Zsolt Farkas, Richard Univ Szeged Dept Comp Algorithms & Artificial Intelligence Arpad Ter 2 H-6720 Szeged Hungary

ISBN: (纸本)9781538620304

People share their opinions about things like products, movies and services using social media channels. The analysis of these textual contents for sentiments is a gold mine for marketing experts, thus automatic sentiment analysis is a popular area of applied artificial intelligence. We propose a latent syntactic structure-based approach for sentiment analysis which requires only sentence-level polarity labels for training. Our experiments on three domains (movie, IT products, restaurant) show that a sentiment analyzer that exploits syntactic parses and has access only to sentence-level polarity annotation for in-domain sentences can outperform state-of-the-art models that were trained on out-domain parse trees with sentiment annotation for each node of the trees. In practice, millions of sentence-level polarity annotations are usually available for a particular domain thus our approach is applicable for training a sentiment analyzer for a new domain while it can exploit the syntactic structure of sentences as well.

关键词： sentiment analysis syntax parsing text classification

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syntaxNet Errors from the Linguistic Point of View 6th

SyntaxNet Errors from the Linguistic Point of View

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6th International Conference on Analysis of Images, Social Networks, and Texts (AIST)

作者： Durandin, Oleg Malafeev, Alexey Zolotykh, Nikolai Natl Res Univ Higher Sch Econ Nizhnii Novgorod Russia Lobachevsky State Univ Nizhny Novgorod Nizhnii Novgorod Russia

ISBN: (纸本)9783319730134;9783319730127

The paper deals with Google's universal parser syntaxNet. The system was used to analyze the Universal Dependencies linguistic corpora. We conducted an error analysis of the output of the parser to reveal to what extent the error types are connected with or preconditioned by the language types. In particular, we carried out several experiments, clustering the languages based on the frequency of different errors made by syntaxNet, and studied the similarity of the resulting clustering with the traditional typology of languages. Three types of errors were separately considered: part-of-speech tagging, dependency labeling, and attachment errors. We show that there is indeed a correlation between error frequencies and language types, which might indicate that to further improve the performance of a universal parser, one needs to take into account language-specific morphological and syntactic structures.

关键词： Natural language processing syntax parsing syntaxNet Error analysis Linguistic typology

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Designing and Realization on Surface Syntactic Analysis Based on Rule and Statistical Approach

Designing and Realization on Surface Syntactic Analysis Base...

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7th World Congress on Intelligent Control and Automation

作者： Wang, Chengmin Peng, Jun Feng, Xuping Xiang, Yi You, Mingying Lei, Liang Chongqing Univ Sci & Technol Coll Elect Informat Engn Chongqing 400042 Peoples R China

ISBN: (纸本)9781424421138

Language is the main carrier of social information. In order to make use of the information existing in the form of natural language, we should extract and analyze it with the technique of dealing with natural language. In dealing with natural language, syntax analysis which is of vital importance should be the bridge between grammar analysis and semantic analysis. Based on rule and statistical approach, this paper discusses the designing and realization on surface syntactic analysis of Chinese language from the aspects of theory and algorithm.

关键词： natural language processing syntax parsing rule syntactic

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