基于LDA主题特征的自动文摘方法

近年来概率主题模型受到了研究者的广泛关注,LDA(Latent Dirichlet Allocation)模型是主题模型中具有代表性的概率生成模型之一,它能够检测文本的隐含主题。提出一个基于LDA模型的主题特征,该特征计算文档的主题分布与句子主题分布的距离。结合传统多文档自动文摘中的常用特征,计算句子权重,最终根据句子的分值抽取句子形成摘要。实验结果证明,加入LDA模型的主题特征后,自动文摘的性能得到了显著的提高。     

基于LDA重要主题的多文档自动摘要算法

提出了基于LDA(latent Dirichlet allocation)重要主题的多文档自动摘要算法。该算法与已有的基于主题模型的多文档自动摘要算法主要有两点区别:第一,在计算句子主题与文档主题相似度问题上,引入并定义了主题重要性的概念,将LDA模型建立的主题分成重要和非重要主题两类,计算句子权重时重点考虑句子主题和文档重要主题的相似性;第二,该方法同时使用句子的词频、位置等统计特征和LDA特征组成的向量计算句子的权重,既突出了传统的统计特征的显著优势,又结合了LDA模型的主题概念。实验表明,该算法在DUC2002标准数据集上取得了较好的摘要效果。     

主题模型LDA的多文档自动文摘

近年来使用概率主题模型表示多文档文摘问题受到研究者的关注.LDA (latent dirichlet allocation)是主题模型中具有代表性的概率生成性模型之一.提出了一种基于LDA的文摘方法,该方法以混乱度确定LDA模型的主题数目,以Gibbs抽样获得模型中句子的主题概率分布和主题的词汇概率分布,以句子中主题权重的加和确定各个主题的重要程度,并根据LDA模型中主题的概率分布和句子的概率分布提出了2种不同的句子权重计算模型.实验中使用ROUGE评测标准,与代表最新水平的SumBasic方法和其他2种基于LDA的多文档自动文摘方法在通用型多文档摘要测试集DUC2002上的评测数据进行比较,结果表明提出的基于LDA的多文档自动文摘方法在ROUGE的各个评测标准上均优于SumBasic方法,与其他基于LDA模型的文摘相比也具有优势.     

基于动态主题建模的Web论坛文档摘要

针对论坛文档由于自身特点缺乏有效的文档摘要方法的现状,提出一种基于LDA主题模型的论坛文档摘要方法.在主题建模中考虑了Web论坛文档中帖子和帖子之间的回复关系,并把主题的分布变为随文档变化而变化的一个动态过程,来解决主题的依赖和偏移问题.在使用GibbsEM采样算法来确定动态主题模型的参数后,通过计算句子中主题权重之和来确定各个主题的重要程度;最后根据动态主题模型中主题的概率分布计算各句子的权重并得到文档的摘要.实验结果表明,新方法在各个ROUGE评测标准上均优于其他各种对比的摘要方法.     

主题信息的中文多文档自动文摘系统

多文档自动文摘能够帮助人们自动、快速地获取信息,使用主题模型构建多文档自动文摘系统是一种新的尝试,其中主题模型采用浅层狄利赫雷分配（LDA）。该模型是一个多层的产生式概率模型,能够检测文档中的主题分布。使用LDA为多文档集合建模,通过计算句子在不同主题上的概率分布之间的相似度作为句子的重要度,并根据句子重要度进行文摘句的抽取。实验结果表明,该方法所得到的文摘性能优于传统的文摘方法。     

基于PV-DM模型的多文档摘要方法

当前的基于词向量的多文档摘要方法没有考虑句子中词语的顺序,存在异句同向量问题以及在小规模训练数据上生成的摘要冗余度高的问题。针对这些问题,提出基于PV-DM(Distributed Memory Model of Paragraph Vectors)模型的多文档摘要方法。该方法首先构建单调亚模(Submodular)目标函数;然后,通过训练PV-DM模型得到句子向量计算句子间的语义相似度,进而求解单调亚模目标函数;最后,利用优化算法抽取句子生成摘要。在标准数据集Opinosis上的实验结果表明该方法优于当前主流的多文档摘要方法。     

融合多信息句子图模型的多文档摘要抽取

针对现有多文档抽取方法不能很好地利用句子主题信息和语义信息的问题,提出一种融合多信息句子图模型的多文档摘要抽取方法。首先,以句子为节点,构建句子图模型;然后,将基于句子的贝叶斯主题模型和词向量模型得到的句子主题概率分布和句子语义相似度相融合,得到句子最终的相关性,结合主题信息和语义信息作为句子图模型的边权重;最后,借助句子图最小支配集的摘要方法来描述多文档摘要。该方法通过融合多信息的句子图模型,将句子间的主题信息、语义信息和关系信息相结合。实验结果表明,该方法能够有效地改进抽取摘要的综合性能。     

基于潜在狄利克雷分布模型的多文档情感摘要

针对当前方法难以获取评论文本全局情感倾向性的问题,提出一种基于潜在狄利克雷分布(LDA)模型的多文档情感摘要方法。该方法首先对给定的句子进行情感分析,抽取带有主观性评价的句子;然后,应用LDA模型表示已抽取的句子,并通过词汇的重要度和句子的特征计算句子的权重;最终提取情感文摘。实验结果表明,该方法能够有效地识别情感关键句,在准确率、召回率和F值上均有不错的效果。     

一种结合主题模型的推荐算法

针对传统协同过滤推荐算法存在的冷启动、数据稀疏以及相似度度量的准确性问题,基于LDA主题模型对文本隐式主题挖掘的有效性和KL散度在主题分布相似性度量的准确性,提出了结合LDA主题模型的矩阵分解推荐算法。首先,利用改进的LDA算法输出项目-主题分布,并用困惑度作为主题数设置的修正函数;然后分别基于余弦相似度和KL散度计算得到项目相似度矩阵,将得到的相似度矩阵结合原评分训练集输出预评分,再将预评分填充到训练集;最后将训练集输入ALS矩阵分解算法得到推荐结果。通过MovieLens数据集的实验结果表明,该算法在不同隐式参数设定下均能得到比ALS推荐算法以及更小的预测误差,并且最优预测误差小于传统推荐算法。该实验说明了通过集成LDA主题模型的ALS算法效果要优于其他推荐算法。     

结合LDA和谱聚类的多文档摘要

自动文摘技术的目标是致力于将冗长的文档内容压缩成较为简短的几段话,将信息全面、简洁地呈现给用户,提高用户获取信息的效率和准确率。所提出的方法在LDA（Latent Dirichlet Allocation）的基础上,使用Gibbs抽样估计主题在单词上的概率分布和句子在主题上的概率分布,结合LDA参数和谱聚类算法提取多文档摘要。该方法使用线性公式来整合句子权重,提取出字数为400字的多文档摘要。使用ROUGE自动摘要评测工具包对DUC2002数据集评测摘要质量,结果表明,该方法能有效地提高摘要的质量。     

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。     

How do children do mathematics with LOGO?

Abstract  This paper considers some results of a study designed to investigate the kinds of mathematical activity undertaken by children (aged between 8 and 11) as they learned to program in LOGO. A model of learning modes is proposed, which attempts to describe the ways in which children used and acquired understanding of the programming/mathematical concepts involved. The remainder of the paper is concerned with discussing the validity and limitations of the model, and its implications for further research and curriculum development.