多媒体网络舆情语义识别的关键技术分析
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摘要
[目的/意义]为多媒体网络舆情语义识别研究中的方法选择提供支持。[方法/过程]将多媒体网络舆情语义识别分为多媒体网络舆情信息的特征识别与多媒体网络舆情语义的深度识别两部分,并提出多媒体网络舆情语义识别的具体流程,定义了多媒体网络舆情语义的深度识别算法的比较指标,并对语义的深度识别方法进行了全面的比较。[结果/结论]对在多媒体网络舆情语义识别研究过程中的技术进行了对比,对语义识别技术的选择进行了总结,并提出了今后的研究方向。
[Purpose/significance] This paper tries to provide references for the techniques selection of semantic recognition of MNPO( Multimedia network public opinion). [Method/process] MNPO can be divided into the feature recognition of MNPO and the deep semantic recognition of MNPO,the specific processes of semantic recognition of MNPO are proposed,and the indicators for the comparison of deep semantic recognition algorithms of MNPO are defined to make a comparative study on deep semantic recognition of MNPO. [Result/conclusion] The paper compares specific techniques of semantic recognition of MNPO,summarizes how to select semantic recognition techniques,and proposes the direction of future study.
[Purpose/significance] This paper tries to provide references for the techniques selection of semantic recognition of MNPO( Multimedia network public opinion). [Method/process] MNPO can be divided into the feature recognition of MNPO and the deep semantic recognition of MNPO,the specific processes of semantic recognition of MNPO are proposed,and the indicators for the comparison of deep semantic recognition algorithms of MNPO are defined to make a comparative study on deep semantic recognition of MNPO. [Result/conclusion] The paper compares specific techniques of semantic recognition of MNPO,summarizes how to select semantic recognition techniques,and proposes the direction of future study.
引文
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[2] ALTINEL B,GANIZ M C. A new hybrid semi-supervised algorithm for text classification with class-based semantics[J].Knowledge-Based Systems,2016,108(C):50-64.
[3] ALTINEL B,DIRI B,GANIZ M C. A novel semantic smoothing kernel for text classification with class-based weighting[J]. Knowledge-Based Systems,2015,89:265-277.
[4] ZHU Y,WANG S,YUE L,et al. Multiple-facial action unit recognition by shared feature learning and semantic relation modeling[C]//International Conference on Pattern Recognition. IEEE Computer Society,2014:1663-1668.
[5] KOVALENKO M,ANTOSHCHUK S,SIECK J. Human action recognition using a semantic-probabilistic network[C]. International Conference on Emerging Trends in Networks and Computer Communications. IEEE,2015:67-72.
[6]毕强,刘健,鲍玉来.基于语义相似度的文本聚类研究[J].现代图书情报技术,2016(12):9-16.
[7]曹劲松.网络舆情的基本特点[J].新闻与写作,2009(12):39-40.
[8]黄微,李瑞,孟佳林.大数据环境下多媒体网络舆情传播要素及运行机理研究[J].图书情报工作,2015,59(21):38-44+62.
[9] REN F,SOHRAB M G. Class-indexing-based term weighting for automatic text classification[J]. Information Sciences,2013,236(1):109-125.
[10] PORIA S,CAMBRIA E,GELBUKH A. Aspect extraction for opinion mining with a deep convolutional neural network[M].Elsevier Science Publishers B. V,2016.
[11] AYADI M E,HASSAN A K S O,ABDEL-NABY A,et al.Text-independent speaker identification using robust statistics estimation[J]. Speech Communication,2017,92:52-63.
[12] HE S,ZHAO H. Automatic syllable segmentation algorithm of Chinese speech based on MF-DFA[J]. Speech Communication,2017,92:42-51.
[13]韩文静,李海峰,阮华斌,马琳.语音情感识别研究进展综述[J].软件学报,2014,25(1):37-50.
[14] LI M,MONGA V. Compact video fingerprinting via structural graphical models[J]. IEEE Transactions on Information Forensics&Security,2013,8(11):1709-1721.
[15]王思力,王斌.基于双字耦合度的中文分词交叉歧义处理方法[J].中文信息学报,2007(5):14-17,30.
[16]韩冬煦,常宝宝.中文分词模型的领域适应性方法[J].计算机学报,2015,38(2):272-281.
[17] MIKOLOV T,CHEN K,CORRADO G,et al. Efficient estimation of word representations in vector space[J]. Computer Science,2013.
[18]阳树洪.灰度图像阈值分割的自适应和快速算法研究[D].重庆:重庆大学,2014.
[19]吴建.基于区域生长算法的彩色遥感图像分割[J].广西大学学报:自然科学版,2011,36(6):981-986.
[20]赵婕,张春美,张小勇,姚峰林.基于区域边界最优映射的图像分割算法[J].计算机应用研究,2016,33(1):307-310.
[21]江晓亮.基于模糊聚类及活动轮廓模型的图像分割技术研究[D].成都:西南交通大学,2016.
[22]张荣祥,郑世杰,夏庆观.基于Hilbert扫描和小波变换的自适应图像分割[J].中国图象图形学报,2008(4):666-671.
[23]张明月.基于深度学习的图像分割研究[D].长春:吉林大学,2017.
[24]李虹,徐小力,吴国新,丁春艳,赵学梅.基于MFCC的语音情感特征提取研究[J].电子测量与仪器学报,2017,31(3):448-453.
[25]彭书勇.基于CELMDAN的公共场所异常声音特征提取方法[D].重庆:重庆大学,2016.
[26]张玉珍,杨明,王建宇,戴跃伟.基于运动补偿和自适应双阈值的镜头分割[J].计算机科学,2010,37(9):282-286.
[27] KAR T, KANUNGO P. A motion and illumination resilient framework for automatic shot boundary detection[J]. Signal Image&Video Processing,2017(1):1-8.
[28]孙中华.基于颜色与目标轮廓特征的视频分割方法[D].长春:吉林大学,2004.
[29] GU L,LIU J,QU A. Performance evaluation and scheme selection of shot boundary detection and keyframe extraction in content-based video retrieval[J]. International Journal of Digital Crime&Forensics,2017,9(4):15-29.
[30] FAN J,ZHOU S,SIDDIQUE M A. Fuzzy color distribution chart-based shot boundary detection[J]. Multimedia Tools&Applications,2017,76(7):10169-10190.