英语中两种名词属格的认知对比

英语中,名词属格有两种形式即’s属格结构和＂名词＋of＋名词＂结构。由于这两种结构表达的都是所属关系,在译成汉语时都译成＂的＂,所以引起很多学者的关注。但是以往的研究和努力都是在划分两种属格的语义关系,通过区分语义关系的不同来找出两者用法上的差异。利用认知语言学的原型范畴理论探讨两种名词属格的属性及其互补性可以帮助英语学习者更清晰明了地掌握两种结构的使用规则,在应用中做出正确的选择和判断。     

基于自适应背景模型的动态场景目标检测

背景建模一直是运动目标检测中的一个重要课题。该文提出一个适用于动态背景的基于非参数估计的前景背景对比模型。模型通过核函数估计的方法模拟了像素点五维特征向量的概率分布,并在图像序列中滚动更新。实验证明,上述算法能够在一般目标检测,特别是动态场景(摇动树枝等)的检测中取得较好的效果。     

Semantic-Oriented Knowledge Transfer for Review Rating

With the rapid development of Web 2.0, more and more people are sharing their opinions about online products, so there is much product review data. However, it is difficult to compare products directly using ratings because many ratings are based on different scales or ratings are even missing. This paper addresses the following question: given textual reviews, how can we automatically determine the semantic orientations of reviewers and then rank different items? Due to the absence of ratings in many reviews, it is difficult to collect sufficient rating data for certain specific categories of products (e.g., movies), but it is easier to find rating data in another different but related category (e.g., books). We refer to this problem as transfer rating, and try to train a better ranking model for items in the interested category with the help of rating data from another related category. Specifically, we developed a ranking-oriented method called TRate for determining the semantic orientations and for ranking different items and formulated it in a regularized algorithm for rating knowledge transfer by bridging the two related categories via a shared latent semantic space. Tests on the Epinion dataset verified its effectiveness.     

壮语亲属词语义关系量变的回归分析

壮语亲属词中的汉借词使早期的亲属语义关系发生了量变，且这种量变在壮语方言中具有随机性。文章以“亲属语义关系”为因变量，亲属词的“变异均值”为自变量，用回归分析的方法确定了两个变量间单向正相关的因果属性。     

TSPN: Term-based semantic peer-to-peer networks

In this paper, we propose Term-based Semantic Peer-to-Peer Networks (TSPN) to achieve semantic search. For each peer, TSPN builds a full text index of its documents. Through the analysis of resources, TSPN obtains series of terms, and distributes these terms into the network. Thus, TSPN can use query terms to locate appropriate peers to perform semantic search. Moreover, unlike the traditional structured P2P networks, TSPN uses the terms, not the peers, as the logical nodes of DHT. This can with-stand the impact of network churn. The experimental results show that TSPN has better performance compared with the existing P2P semantic searching algorithms.     

一种面向网店商品搜索的中文分词系统设计

文章设计新的数据结构对网店商品的原始数据进行加工处理,形成一个存储所有商品信息的词条字典。结合全切分算法,实现对用户输入关键词的完全切分,并通过和词条字典的匹配得到所有候选的词条组合。为了消除分词过程中的歧义和不合理的词条组合,系统结合商品类目树的存储结构,通过算法和引入权值计算的方法对词条组合进行排序,得到最佳结果。     

山西方言惯用语的结构、语义及认知研究

山西方言惯用语在语义上具有描绘性和贬义性的特点.在惯用语的语义形成过程中,人类的隐喻和转喻思维对惯用语的语义扩展起了非常重要的作用.     

灰度和彩色图象分割的一种改进算法

图象边缘检测技术是图象处理中最重要的内容之一,且已在图象分析和识别区域中得到广泛的应用。但由于边缘点不连续和难以把存在大量碎边缘的高细节区提取出来这两个原因,而不能直接实现完整意义上的图象分割。为了提高图象分割的边缘准确性和区域一致性以及降低分割错误率,提出用边缘生长的方法来解决不连续的边缘点链接问题,以便间接地将高细节区围成一个区域。该算法也可以嵌入到其他利用边缘信息的分割算法中。     

日语学习和信息关系的分析

语言是交际的工具 ,是信息的载体。语言利用声音、文字、媒体等手段得以传播 ,使学习者受到刺激 ,作出反应 ,进行记忆。本文将从信息、语义网络、表达诸方面分析日语学习特点。     

程序树层次化结构统计模型及MOSES改进算法

为提高MOSES效率,提出了一种新的程序树层次化结构统计模型.该模型通过统计分析同类群,自动发现子树特征来指导优化.该模型不需要hBOA算法那样对变量集合进行建模,也不需要像MRTS算法那样遍历小规模的种群来发现潜在的有指导意义的子树.通过解决人工蚂蚁问题对算法进行了测试,结果表明改进后的MOSES算法更加高效.