基于情感特征向量空间模型的中文商品评论倾向分类算法

为了能够快速有效地将中文商品评论识别为好评或差评,提出一种算法。针对不同类别的商品,预先根据其评论语料构建领域情感词典,评论文本与情感词典集匹配提取情感特征,构建情感特征向量空间模型SF-VSM(Sentiment Feature Vector Space Model),解决传统的特征向量空间模型维数较高及特征选择误差问题。然后基于该模型结合改进的多项式朴素贝叶斯方法对评论进行情感倾向分类。实验结果表明,相比分别基于原始特征和基于χ2特征选取的朴素贝叶斯分类算法,该算法分类精度较高且分类速度快。     

中文文本情感词典构建方法

互联网海量文本的情感分析是当前的一个研究热点。介绍了一种中文文本情感词典构建方法,该方法选用若干个情感种子词,利用搜索引擎返回的共现数,通过改进的PMI（pointwise mutual information）算法计算情感词的情感权值。将构建的情感词典应用到文本情感分类实验中,在不同的语料环境下,对比基于情感词典和朴素贝叶斯分类器下的文本情感分类效果,实验结果表明,构建的情感词典,可有效用于情感特征选择和直接用于情感分类,并且分类性能稳定。     

结合卷积神经网络和词语情感序列特征的中文情感分析

目前基于词嵌入的卷积神经网络文本分类方法已经在情感分析研究中取得了很好的效果。此类方法主要使用基于上下文的词嵌入特征,但在词嵌入过程中通常并未考虑词语本身的情感极性,同时此类方法往往缺乏对大量人工构建情感词典等资源的有效利用。针对这些问题,该文提出了一种结合情感词典和卷积神经网络的情感分类方法,利用情感词典中的词条对文本中的词语进行抽象表示,在此基础上利用卷积神经网络提取抽象词语的序列特征,并用于情感极性分类。该文提出的相关方法在中文倾向性分析评测COAE2014数据集上取得了比目前主流的卷积神经网络以及朴素贝叶斯支持向量机更好的性能。     

基于Hadoop的朴素贝叶斯算法在中文微博情感分类中的研究与应用

通过对文本情感分类的研究,考虑微博文本信息的篇幅短小、情感符号丰富及大量网络词汇的特点,提出一种适用于中文微博情感分类的基于Map/Reduce的分布式朴素贝叶斯算法。算法通过构建适用于微博文本的情感词典来完成情感特征属性的提取,以期达到较为理想的分类效果。实验结果表明,这种方法能够很好地适用于微博情感分类,达到较理想的分类效果,满足针对海量的微博文本数据处理的可行性与高效性的需求。     

基于机器学习的剧本角色情感识别研究

针对DataFountain平台举办竞赛所提供的剧本角色情感数据集,采用中文分词、去停用词和绘制词云图等工具对数据进行预处理,利用词频-逆向文档频率(TF-IDF)算法提取文本特征,分别建立了基于支持向量机和朴素贝叶斯算法的机器学习分类识别模型。将建立的新模型应用于剧本角色情感的识别和分析研究,结果表明,朴素贝叶斯分类模型的识别效果要优于支持向量机分类模型;并且,当拉普拉斯平滑系数α=0.2时,朴素贝叶斯算法的分类准确率接近于80%。     

一种基于朴素贝叶斯的微博情感分类

本文基于二次情感特征提取算法,利用句法依存关系进行一次文本情感特征提取,在此基础上,利用情感词典,进行二次情感特征提取。构建朴素贝叶斯分类器,对采集的热门话题微博和酒店评论进行文本情感倾向性分类。主要比较了表情符号、标点符号,基于情感词典的特征提取和基于二次情感特征提取方法,在不同的组合下的分类性能,寻找更佳的微博文本情感分类预处理方法。并与酒店评论情感分类结果对比、分析,发现影响微博情感分类性能的原因。实验结果表明,二次特征提取方法在分类上取得更高的F1。实验最佳的分类预处理方式是"表情符号+标点符号+二次情感特征提取+BOOL值"。同时发现,朴素贝叶斯在酒店评论情感分类取得更高的分类性能,主要是微博评价对象多样化造成的。     

基于多特征融合的汉语情感分类研究*

中文情感分类一般分成基于情感词典和基于特征分类两种方法进行研究,但没有考虑过将两种方法得到的特征进行融合来提高分类效果。基于特征分类的方法忽视了特征词在情感词典的褒贬性以及词倾向性的强弱。用基于特征分类方法得到的文本特征建立朴素贝叶斯模型,根据特征词在情感词典中的褒贬性及其通过点对互信息方法得到的词性强弱调整情感词的正负后验概率权重,实现两种特征的融合,提高分类效果并降低了特征维数。     

一种级联式微博情感分类器的构建方法

该文从统计学方法与机器学习的分类思想出发,对中文微博文本的情感类别进行研究。针对微博文本的特点,提出了一种级联式微博情感分类器模型,该模型首先构建基于情感词典和新浪表情符号词典的微博情感初级分类模型;然后根据基准词构建基于类别倾向相似度的二级分类模型,对初级模型未能确定情感类别的微博进行再次分类,并对初级模型的词典进行更新;最后采用朴素贝叶斯分类器构建三级分类模型,对以上还未确定情感类别的微博进行三级分类。通过与NLPCC2014微博情感分类评测参赛结果进行比较,说明了所提方法的有效性。     

使用机器学习方法进行新闻的情感自动分类

本文主要研究机器学习方法在新闻文本的情感分类中的应用,判断其是正面还是负面。我们利用朴素贝叶斯和最大熵方法进行新闻及评论语料的情感分类研究。实验表明,机器学习方法在基于情感的文本分类中也能取得不错的分类性能,最高准确率能达到90%。同时我们也发现,对于基于情感的文本分类,选择具有语义倾向的词汇作为特征项、对否定词正确处理和采用二值作为特征项权重能提高分类的准确率。总之,基于情感的文本分类是一个更具挑战性的工作。     

基于二元搭配词的微博情感特征选择

分析和监测微博文本中所包含的情感信息,能够挖掘用户行为,为微博舆情监管提供借鉴。但微博文本具有长度较短、不规范、存在大量变形词和新词等特点,仅以情感词为特征对微博进行分类的方法准确率较低,难以满足实际使用。为此,基于微博语料构建二元搭配词库,并根据PMI-IR算法结合语料库统计信息,提出搭配词组情感权值的计算方法PMI-IR-P。结合情感词典,采用统计方法生成微博情感特征向量,利用机器学习中的C4.5算法构建分类模型,对微博文本进行情感倾向分类。分别使用不同的数据集用于构建搭配词库及分类模型,并与基于情感词典的分类方法以及朴素贝叶斯分类方法进行对比。实验结果表明,提出的情感特征通过运用C4.5算法对微博文本情感分类的准确率达到87%,具有较好的效果。     

Only connect: teaching, technology and telesis

Abstract This paper describes an approach to the design of interactive multimedia materials being developed in a European Community project. The developmental process is seen as a dialogue between technologists and teachers. This dialogue is often problematic because of the differences in training, experience and culture between them. Conditions needed for fruitful dialogue are described and the generic model for learning design used in the project is explained.     

European Community policy and the market

Abstract This paper starts with some reflections on the policy considerations and priorities which are shaping European Commission (EC) research programmes. Then it attempts to position the current projects which seek to capitalise on information and communications technologies for learning in relation to these priorities and the apparent realities of the marketplace. It concludes that while there are grounds to be optimistic about the contribution EC programmes can make to the efficiency and standard of education and training, they are still too technology driven.     

一种自适应子融合集成多分类器方法

融合集成方法已经广泛应用在模式识别领域,然而一些基分类器实时性能稳定性较差,导致多分类器融合性能差,针对上述问题本文提出了一种新的基于多分类器的子融合集成分类器系统。该方法考虑在度量层融合层次之上通过对各类基多分类器进行动态选择,票数最多的类别作为融合系统中对特征向量识别的类别,构成一种新的自适应子融合集成分类器方法。实验表明,该方法比传统的分类器以及分类融合方法识别准确率明显更高,具有更好的鲁棒性。     

Avoiding semantic and temporal gaps in developing software intensive systems

Development of software intensive systems (systems) in practice involves a series of self-contained phases for the lifecycle of a system. Semantic and temporal gaps, which occur among phases and among developer disciplines within and across phases, hinder the ongoing development of a system because of the interdependencies among phases and among disciplines. Such gaps are magnified among systems that are developed at different times by different development teams, which may limit reuse of artifacts of systems development and interoperability among the systems. This article discusses such gaps and a systems development process for avoiding them.     

Designing economic np control charts: A programmed simulation approach

This paper presents control charts models and the necessary simulation software for the location of economic values of the control parameters. The simulation program is written in FORTRAN, requires only 10K of main storage, and can run on most mini and micro computers. Two models are presented - one describes the process when it is operating at full capacity and the other when the process is operating under capacity. The models allow the product quality to deteriorate to a further level before an existing out-of-control state is detected, and they can also be used in situations where no prior knowledge exists of the out-of-control causes and the resulting proportion defectives.     

The development of robot art

Going through a few examples of robot artists who are recognized worldwide, we try to analyze the deepest meaning of what is called “robot art” and the related art field definition. We also try to highlight its well-marked borders, such as kinetic sculptures, kinetic art, cyber art, and cyberpunk. A brief excursion into the importance of the context, the message, and its semiotics is also provided, case by case, together with a few hints on the history of this discipline in the light of an artistic perspective. Therefore, the aim of this article is to try to summarize the main characteristics that might classify robot art as a unique and innovative discipline, and to track down some of the principles by which a robotic artifact can or cannot be considered an art piece in terms of social, cultural, and strictly artistic interest. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Explanation and prediction: an architecture for default and abductive reasoning

Although there are many arguments that logic is an appropriate tool for artificial intelligence, there has been a perceived problem with the monotonicity of classical logic. This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of our assumptions. The two activities of predicting what is expected to be true and explaining observations are considered in a simple theory formation framework. Properties of each activity are discussed, along with a number of proposals as to what should be predicted or accepted as reasonable explanations. An architecture is proposed to combine explanation and prediction into one coherent framework. Algorithms used to implement the system as well as examples from a running implementation are given.     

Three Process Perspectives: Organizations, Teams, and People

This paper provides the author's personal views and perspectives on software process improvement. Starting with his first work on technology assessment in IBM over 20 years ago, Watts Humphrey describes the process improvement work he has been directly involved in. This includes the development of the early process assessment methods, the original design of the CMM, and the introduction of the Personal Software Process (PSP)^SM and Team Software Process (TSP){^SM}. In addition to describing the original motivation for this work, the author also reviews many of the problems he and his associates encountered and why they solved them the way they did. He also comments on the outstanding issues and likely directions for future work. Finally, this work has built on the experiences and contributions of many people. Mr. Humphrey only describes work that he was personally involved in and he names many of the key contributors. However, so many people have been involved in this work that a full list of the important participants would be impractical.     

基于复小波噪声方差显著修正的SAR图像去噪

提出了一种基于复小波域统计建模与噪声方差估计显著性修正相结合的合成孔径雷达(Synthetic Aperture Radar,SAR)图像斑点噪声滤波方法。该方法首先通过对数变换将乘性噪声模型转化为加性噪声模型,然后对变换后的图像进行双树复小波变换(Dualtree Complex Wavelet Transform,DCWT),并对复数小波系数的统计分布进行建模。在此先验分布的基础上,通过运用贝叶斯估计方法从含噪系数中恢复原始系数,达到滤除噪声的目的。实验结果表明该方法在去除噪声的同时保留了图像的细节信息,取得了很好的降噪效果。     

基于QTE的蒙古文显示机制研究与实现

蒙古语言是中国蒙古族使用的通用语言,由于蒙古文区别于其他文字的书写方式和其自身变形机制等特点,在很多通用的文字处理引擎中都不被支持。在嵌入式产品开发与应用领域中Linux加QTE已经成为流行方式。该文给出了一种在QTE环境上实现基于标准Unicode的蒙古文点阵显示和变形算法, 并自定义了支持蒙古文的QTE组件,扩展了QTE功能,为在Linux加QTE方式的嵌入式体系结构中处理蒙古文提供了一种解决方法。