本体映射过程中的综合相似度计算

论文以相似度计算为基本思想提出一种综合相似度的映射算法.该算法首先利用wordnet进行语言层面上的相似度计算,在进行语言层面上相似度计算的同时考虑概念自身的微观结构(概念的密度和深度).引入密度制约参数和深度制约参数.然后基于概念实例计算概念相似度,给出了本体的综合相似度计算方法.最后采用学术领域内的SWRC本体和医...     

用本体论来解决协同编著中的一致性问题

协同编著是一个群体认知和创造的过程。不同背景的人对同一个主题的理解产生的自然差异会导致主题的偏移。目前,国内外协同编著研发还没有很好地解决协同编著过程发散而又要求主题一致性收敛的问题。利用本体论中的领域本体,为实现人人交互提供一种共享的语义基础,从而为解决协同编著中的主题一致性问题提供一种研究思路。另外,可以用协议本体解决系统之间的通信问题并提出了基于本体论的协同编著模型的构想。     

一种基于概念格的本体合并方法

提出了一种基于概念格的,并利用叙词表的方法进行本体合并.为了进一步获得提取本体概念的相关指导,提高本体概念抽取的自动化程度,提出最小外延集概念,从而更方便有效地进行本体合并.     

模糊本体及其演化研究

本体是共享概念模型的规范说明,但以往的描述方法不能表示资源间关系的模糊性及其演化.针对这一问题,引入了模糊本体的概念并给出了形式化的描述,用模糊资源描述框架(FRDF)对模糊本体进行表示,提出了一种模糊本体演化算法,并用实验进行了验证.     

基于本体的语义Web服务注册平台研究

提出了一种基于本体的语义Web服务注册模型,结合Jena实现语义Web服务的语义查询和推理.应用元模型互操作框架(MFI)中的本体注册元模型标准,以实现与其他注册模型的语义互操作,并给出了一个基于该模型的语义Web服务注册平台.     

Sentiment analysis on Twitter: A text mining approach to the Syrian refugee crisis

The use of social media has become an integral part of daily routine in modern society. Social media portals offer powerful public platforms where people can freely share their opinions and feelings about various topics with large crowds. In the current study, we investigated the public opinions and sentiments towards the Syrian refugee crisis, which has affected millions of people and has become a widely discussed, polarizing topic in social media around the world. To analyze public sentiments about the topic on Twitter, we collected a total of 2381,297 relevant tweets in two languages including Turkish and English. Turkish sentiments were considered important as Turkey has welcomed the largest number of Syrian refugees and Turkish tweets carried information to reflect public perception of a refugee hosting country first handedly. We performed a comparative sentiment analysis of retrieved tweets. The results indicated that the sentiments in Turkish tweets were significantly different from the sentiments in English tweets. We found that Turkish tweets carried slightly more positive sentiments towards Syrians and refugees than neutral and negative sentiments, nevertheless the sentiments of tweets were almost evenly distributed among the three major categories. On the other hand, the largest number of English tweets by a significant margin contained neutral sentiments, which was followed by the negative sentiments. In comparison to the ratio of positive sentiments in Turkish tweets, 35% of all Turkish tweets, the proportion of English tweets contained remarkably less positive sentiments towards Syrians and refugees, only 12% of all English tweets.     

Logistics service design for cross-border E-commerce using Kansei engineering with text-mining-based online content analysis

With the rapid development of cross-border e-commerce, the demand for and importance of cross-border logistics service (CBLS) also increase. A satisfactory CBLS can help promote business activities in cross-border e-commerce. Because customers’ logistical needs are increasingly complex and the logistics market is increasingly competitive, a CBLS provider has to be devoted to continually improving and differentiating services to maintain its competitive advantage. Kansei engineering (KE) is an approach to design the elements which satisfy customers’ affective and emotional perceptions into services and products. In this study, the KE approach is applied to derive ideas for the development of CBLS. For this purpose, Partial Least Squares (PLS) is used to analyze the relationships between the feelings of customers and service elements of CBLS. Moreover, this study demonstrates the applications of text mining techniques to analyze the online contents regarding CBLS. Online content mining assists in identifying the service elements and Kansei words for CBLS. Importantly, the relationship between the feelings of customers and service elements of CBLS obtained by online content mining provides complementary results for CBLS design.Relevance to industry: this study offers an exemplification on applying the integration of Kansei engineering and online content analysis to obtain ideas for the process Kansei design in service industry. Our findings imply that in addition to conventional customer survey, user generated online content analysis should be effective way of catching customer-oriented design elements; they provide complementary effects for Kansei design.     

A fast compression-based similarity measure with applications to content-based image retrieval

Compression-based similarity measures are effectively employed in applications on diverse data types with a basically parameter-free approach. Nevertheless, there are problems in applying these techniques to medium-to-large datasets which have been seldom addressed. This paper proposes a similarity measure based on compression with dictionaries, the Fast Compression Distance (FCD), which reduces the complexity of these methods, without degradations in performance. On its basis a content-based color image retrieval system is defined, which can be compared to state-of-the-art methods based on invariant color features. Through the FCD a better understanding of compression-based techniques is achieved, by performing experiments on datasets which are larger than the ones analyzed so far in literature.     

结合DL-safe规则发现日志本体频繁模式的方法

为发现语义Web使用记录中所蕴含的有效信息,本文提出了一种挖掘日志本体频繁Web访问模式的方法。该方法引入应用访问规则集和观察集分别表示日志信息动态变化的语义规则和使用事实,并在DL安全的限定下将日志本体和应用访问规则集相结合构成一个推理过程可判定的混合知识库。在此基础上,利用日志本体中事件整分关系的语义构建访问模式学习的事务模型,并采用ILP的方法学习生成频繁用户访问模式树,解决了推理访问模式中非描述逻辑原子的问题。实验结果表明该方法的可用性和有效性。     

缺失数据的主曲线恢复方法

介绍了缺失数据属性值的一些处理方法,给出了一种新的基于主曲线的缺失数据属性值的恢复方法,详细地描述了利用该方法对缺失属性值进行恢复的步骤,这种方法能根据数据的特性对缺失属性值进行预测,处理的问题带有一般性,并用具体实验数据验证实验该方法的有效性,通过和其他方法进行比较验证了它的精确性.     

KTP激光联合不同方法治疗鼻泪管阻塞

目的:观察KTP激光联合不同方法治疗鼻泪管阻塞的疗效,并对其进行分析。方法:采用KTP激光疏通鼻泪管后,再分别注入典必殊眼膏或植入硅胶管,随访六个月。结果:两组有效率分别为90.24%,97.56%,治愈率为63.41%,75.61%(P<0.05)。结论:KTP激光联合不同方法治疗鼻泪管阻塞是一种安全有效值得推广的好方法。     

用动态激光散射技术对冠心病危重病人血红蛋白结构的研究

目的:研究冠心病危重病人血红蛋白结构大小,为临床的诊断和治疗提供新信息。方法利用动态激光散射技术,分别对分散于pH=7.4、8.0缓冲液中的6例冠心病危重病人血红蛋白的粒径分布进行检测。结果:(1)在pH=7.4时冠心病危重病人的血红蛋白粒径保持为四聚体结构(5.62nm左右),与健康人相同。(2)pH=8.0时以粒径3.16nm左右为主,为单聚体结构,粒径4.22nm左右其次,为二聚体结构,粒径5.62nm左右非常少,为四聚体结构,与健康人在碱性环境下的粒径一致。结论:冠心病人危重病人血红蛋白的结构大小与健康人在相同条件下一致,没有发生病变。