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1.
为了准确挖掘出同一主题的大量网络新闻的线索发展脉络,该文提出了一种基于条件随机场模型的网络新闻主题线索发掘方法。首先,根据新闻主题线索句的识别规则提取出相关特征,并应用到条件随机场模型中提取出主题线索句;然后,按照时间顺序构建原始线索链;最后,对语义相近的原始线索链进行合并处理,获得最终的新闻主题发展脉络。实验结果表明,该方法在主题线索句识别上有较好的效果,最终得到的主题线索脉络能够较清晰地展现新闻发展趋势。  相似文献   

2.
网络评论短文本的细粒度情感分析是文本挖掘的研究热点,评价对象作为细粒度情感分析的基础,在识别文本过程中具有重要作用,如何充分利用上下文信息并对其进行有效表示是评价对象识别的难点所在。提出一种结合词特征与语义特征的评价对象识别方法。针对商品评论语料,使用条件随机场进行评价对象识别,在词特征、依存句法特征的基础上引入语义特征,并将各特征进行组合,以充分利用上下文信息,提高评价对象的识别准确性。在手机评论和酒店评论2个数据集上进行实验,结果表明,该方法的识别准确性较高,且F值分别高达75.36%和82.64%。  相似文献   

3.
在线评论文本通常涉及多个评价对象,对象的表达方式有显式和隐式之分,针对不同对象的情感倾向可能不会完全一致.关键评价对象是评论中最受关注的对象,其相应的情感语义对整条评论的情感观点起主导作用.本文构建了融合关键对象识别与深层自注意力机制的Bi-LSTM模型,以提升短文本情感分类的效果.使用CNN处理文本,基于卷积层输出结果识别关键评价对象,并在此基础上完成深层自注意力的学习.将对象信息与文本信息进行融合,利用注意力机制强化的Bi-LSTM模型得到评论文本的情感分类结果.在酒店评论数据集上进行实验,与之前基于深度学习的模型相比,本文方法在精确率、召回率和F-score评价指标方面均有更好的表现.  相似文献   

4.
在电商网站评论文本中,评价对象和评价属性的缺省识别对文本情感分析具有重要地作用。针对电商网站评论文本中评价对象和评价属性缺省问题,该文提出了一种基于条件随机场的评价对象缺省项识别方法。首先利用情感词典识别观点句,将缺省项识别问题转换成序列标注问题,综合词法特征和依存句法特征,使用条件随机场模型进行训练,并在测试集上对待识别的观点句进行序列标注,通过标注结果判定缺省项的位置。实验结果表明,该方法具有较高的准确率和召回率,验证了该方法的有效性。  相似文献   

5.
突发公共事件网络在线评论序列的特征分析*   总被引:1,自引:0,他引:1  
针对网络评论这种新型文本的特点,给出了一组描述网络评论序列特征的指标,提出了一种基于网络评论倾向性的网络评论序列特征分析方法,并结合实例对网络评论序列的特征、网络新闻与其评论序列的关系,特别是谣言对评论序列的影响进行了分析。  相似文献   

6.
中文产品评论中评价对象的识别研究   总被引:1,自引:0,他引:1       下载免费PDF全文
在中文产品评论中利用无监督的识别评价对象,准确率和召回率较低。为此,提出一种中文产品评论中的评价对象识别方法。对特殊词、评价对象非完整性、评价对象非稳定性等情况过滤噪声,利用评价对象在评论文本中与评价短语规则出现频率较高的特征,进行置信度排序。实验结果表明,对于14 799篇数码类评论文章,该方法的准确率、召回率和F值分别为0.605、0.780、0.681。  相似文献   

7.
针对网购评论命名实体识别中重要词汇被忽略的问题,在评论短文本处理基础上,借鉴多头注意力机制、词汇贡献度和双向长短时记忆条件随机场提出一种基于MA-BiLSTM-CRF模型的网购评论命名实体识别方法。首先,用词向量和词性向量的组合来表示评论文本语义信息;其次,用BiLSTM提取文本特征;然后,引入多头注意力机制从多层面、多角度提升模型性能;最后,用条件随机场(CRF)识别命名实体。实验结果表明,该方法能提升网购评论实体识别效果。  相似文献   

8.
在分析应用视频数据的过程中,视频分段是分析,组织,应用视频数据的基础。由于视频数据的多样性,传统的分段方法不能给出令人满意的结果,一般需要通过人机交互来进行。文中将较为成熟的文本分析、语音处理、图像处理三种技术进行综合,互为补充,对视频流进行分割。文本分析的对象是语音转换成的文本、标题、注释等。语音处理包括语音识别和语音信号分析。语音识别将视频中的自然语言转换为文字。语音信号分析对视频材料中的语音成分进行基础分析。图像处理主要用来处理视频中的图像部分。文章阐述了视频流的分段层次,文本分析,语音处理算法以及镜头突变,镜头渐变识别算法的思想。  相似文献   

9.
本文以电商平台上的产品评论文本为研究对象,针对产品评论中特征词和观点词的识别问题进行了研究.首先构建特征-观点对二分网络,再给出特征-观点对二分网络中节点重要性排序算法,最后将此算法应用到实际的评论文本数据中以检验算法的有效性.  相似文献   

10.
面向特定领域的产品评价对象自动识别研究   总被引:2,自引:0,他引:2  
产品评价对象的自动识别是文本观点信息抽取和倾向性分析中的重要研究课题之一。该文针对汽车评论,提出了一种不依赖外部资源的无指导评价对象自动识别方法。该方法首先综合使用词形模板和词性模板,采用模糊匹配方法和剪枝法抽取候选评价对象。然后,从候选对象集中,采用双向Bootstrapping方法识别出产品评价对象。最后,通过采用K均值聚类方法对产品评价对象进行聚类,实现从评价对象中自动抽取产品名称和产品属性。实验结果表明,该方法对产品评价对象识别的F值达到58.5%,产品名称识别的F值达到69.48%。
  相似文献   

11.
近年来电影行业蓬勃发展,相关的信息抽取和分析技术日益受到行业内的重视,其中对电影主创人物的分析尤为重要。而电影评论作为观影群体的主要反馈信息,具有重要的分析价值。如何从影评中自动抽取主创人名成为重要的基础工作。然而评论中观众对人物的称谓方式多样复杂,而且新电影的影评中往往存在大量人名未登录词,传统方法难以有效识别。针对影评的这些特点,该文提出一种基于多特征Bi-LSTM-CRF的影评人名识别方法。该方法通过利用外部人名语料和未标注影评提取字符级的特征,并采用Bi-LSTM-CRF模型进行人名字符序列标注。实验结果表明,该方法能够有效识别影评中的复杂称谓和人名未登录词,从而有效地抽取影评中的人名实体。  相似文献   

12.
周杰  林琛  李弼程 《计算机应用》2010,30(4):1011-1014
首先对网络新闻评论数据的特点进行归纳总结,选取不同的特征集、特征维度、权重计算方法和词性等因素进行分类测试,并对实验结果进行分析比较。对比结果表明:情感词和论据词语搭配效果优于仅使用情感词作为评论特征;另外该类数据中特征维度对分类准确率的影响减小,且TF-IDF权重计算方法仍优于布尔型权重;在词性选择上,名词和动词词性比形容词和副词取得更好的分类效果。  相似文献   

13.
Merchants, as well as customers, have noticed the importance of online product reviews and numeric ratings in electronic commerce websites. It is valuable if merchants can discover some potential customer value from the sheer volume of data. This paper contributes a semantic text analytics approach that can dig out the customers’ most basic concerns about their online purchase choices. More specifically, based on the hypothesis that the product reviews and overall ratings estimated by same person in a tiny time interval have a great relevance, we dexterously utilize this relevance to realize the embedded customer value. In the proposed method, take the single lens reflex camera for example, an innovative aspect extraction method that comprehensively considers the product ontology and results of the topic modeling method latent Dirichlet allocation is applied. As a result, 8 specific aspects are identified from the experimental results. For each aspect, a self-contained review feature corpus is created as an extension of some seed terms. After aspect-based sentence segmentation and context-sensitive sentiments preprocessing, aspect-oriented sentiment analysis is applied. Multiple regression analysis is then used as a statistical measure to discover determinant aspects of overall ratings. The results reveal that cost performance, image quality and product integrity are the three most influential aspects. The practical implication of our research is that merchants can efficiently modify their products, to satisfy more customers and also boost sales performance.  相似文献   

14.
This paper describes a person identification method for mobile service robots using image and range data. Person identification is a necessary function in order for mobile service robots to locate the target person for those services. Among various sensory features, image-based appearance features have often been used for person identification. They are, however, not effective in severe illumination environments such as a strong backlight. Therefore, we use two illumination-independent features, height and gait, in addition to appearance features for a more robust identification. To this end, we have developed a new method of extracting the gait feature (step length and speed), based on a maximum likelihood estimation of supporting leg positions in accumulated range data. We combine these features and use an online boosting approach to create the specific person classifier. It allows the robot to identify the specific person robustly even in a severe illumination environment. We tested our multi-feature person identification method, combined with a range data-based person tracker, in a specific person following scenario to demonstrate the effectiveness of this method.  相似文献   

15.
肿瘤是当前医学领域尚未完全攻克的难题,针对这一现象,提出了一种借用人工免疫系统模型,通过嵌入式技术等实现手段,探讨了利用人工智能技术治疗肿瘤病患者的方法。该思路的重点在于利用人工免疫网络具备联想、耐受与自稳等特性,通过将其以适当的方式作用于人体,达到激发人体固有免疫系统,恢复原有免疫功能、提升人体抵抗病原侵入的能力,从而达到自愈的目的。详细介绍了系统的设计方法、硬件构成和应用情况,在一定程度上为人工免疫网络的应用研究拓宽了思路。  相似文献   

16.
由于人体指纹具有唯一性和不变性,使得指纹识别与传统身份识别的方法相比具有更高的安全性和易用性.本文阐述了生物特征识别的发展历史、应用背景,并着重介绍指纹识别系统的工作流程、分类及研究现状.  相似文献   

17.
This paper describes a person identifcation method for a mobile robot which performs specifc person following under dynamic complicated environments like a school canteen where many persons exist.We propose a distance-dependent appearance model which is based on scale-invariant feature transform(SIFT) feature.SIFT is a powerful image feature that is invariant to scale and rotation in the image plane and also robust to changes of lighting condition.However,the feature is weak against afne transformations and the identifcation power will thus be degraded when the pose of a person changes largely.We therefore use a set of images taken from various directions to cope with pose changes.Moreover,the number of SIFT feature matches between the model and an input image will decrease as the person becomes farther away from the camera.Therefore,we also use a distance-dependent threshold.The person following experiment was conducted using an actual mobile robot,and the quality assessment of person identifcation was performed.  相似文献   

18.
基于无监督的显著性学习方法提出一种新颖的人物识别方法。它在训练程序部分不需要身份标签就能提取出突出的特征。首先利用相邻约束斑块匹配在图片对之间构建稠密对应。该方法在处理由于较大的视觉角度变化和人物姿势变化而引起的图片对之间不对应的情况非常有效。其次,它应用一种无监督的方法来学习人物的显著性。为了提高实验的性能,在斑块匹配过程中融合了这种人物的显著性特征。在VIPeR数据集上进行的实验证实了该方法的正确性,且性能略优于文献中提出的eBiCov方法及eLDFV方法。  相似文献   

19.
20.
E-commerce websites are now favourite for shopping comfortably at home without any burden of going to market. Their success depends upon the reviews written by the consumers who used particular products and subsequently shared their experiences with that product. The reviews also affects the buying decision of customer. Because of this reason the activity of fake reviews posting is increasing. The brand competitors of the product or the company itself may involve in posting fraud reviews to gain more profit. Such fraudulent reviews are spam review that badly affects the decision choice of the prospective consumer of the products. Many customers are misguided due to fake reviews. The person, who writes the fake reviews, is called the spammer. Identification of spammers is indirectly helpful in identifying whether the reviews are spam or not. The detection of review spammers is serious concern for the E-commerce business. To help researchers in this vibrant area, we present the state of art approaches for review spammer detection. This paper presents a comprehensive survey of the existing spammer detection approaches describing the features used for individual and group spammer detection, dataset summary with details of reviews, products and reviewers. The main aim of this paper is to provide a basic, comprehensive and comparative study of current research on detecting review spammer using machine learning techniques and give future directions. This paper also provides a concise summary of published research to help potential researchers in this area to innovate new techniques.  相似文献   

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