Information system for image classification based on frequency curve proximity

With the size digital collections are currently reaching, retrieving the best match of a document from large collections by comparing hundreds of tags is a task that involves considerable algorithm complexity, even more so if the number of tags in the collection is not fixed. For these cases, similarity search appears to be the best retrieval method, but there is a lack of techniques suited for these conditions. This work presents a combination of machine learning algorithms put together to find the most similar object of a given one in a set of pre-processed objects based only on their metadata tags. The algorithm represents objects as character frequency curves and is capable of finding relationships between objects without an apparent association. It can also be parallelized using MapReduce strategies to perform the search. This method can be applied to a wide variety of documents with metadata tags. The case-study used in this work to demonstrate the similarity search technique is that of a collection of image objects in JavaScript Object Notation (JSON) containing metadata tags.     

基于元数据的对象关系映射研究

持久化框架较好地解决了关系型数据库的对象持久化问题,对象关系映射是持久化框架的核心内容。参考MOF标准,本文设计了面向对象和面向关系的元数据模型,在分析属性映射和关系映射的基础上,介绍了基于元数据的对象关系映射,最后讨论了利用XML技术的实现。     

On the impact of adaptive test question selection for learning efficiency

In this paper we present a method for adaptive selection of test questions according to the individual needs of students within a web-based educational system. It functions as a combination of three particular methods. The first method is based on the course structure and focuses on the selection of the most appropriate topic for learning. The second uses Item Response Theory to select the k-best questions with adequate difficulty for a particular learner. The last is based on the usage history and prioritizes questions according to specific strategies, e.g. to filter out the questions that were recently asked. We describe how these methods evaluate user answers to gather information concerning their characteristics for a more precise selection of further questions. We describe an evaluation of the impact of a proposed method through two different types of experiments in the domain of learning programming, which both showed that our method for adaptive test question selection increases the overall learning outcome, especially for lower than average performing students.     

数据仓库环境的元数据管理技术综述

数据仓库环境中元数据管理是重要的问题.文章对数据仓库中的元数据管理技术的研究、应用和产品进行综述.归纳了元数据管理的内容和功能,比较了元数据管理标准,讨论了各种体系结构的适用性,详细分析了互操作、变更管理机制的技术特点,介绍了模型管理研究的进展,分析比较商用产品的技术特征,展望进一步研究方向.     

Metadata Broadcasting for Personalized Service: A Practical Solution

As the number of broadcasting channels and programs increases rapidly, the importance of personalized service has been emphasized. In this paper, we propose a practical framework of metadata broadcasting to provide personalized service according to user preferences and various terminal/network conditions. First, we present an overall system architecture of a metadata broadcasting system and then propose several core technologies (particularly in the parts of metadata authoring, metadata encoding, and metadata‐based personalized content consumption). For interoperability, the proposed solution is designed to be compliant with the relevant standards of the TV‐Anytime Forum, MPEG‐7 Systems, and MPEG‐2 Systems. Considering a home network environment, we also propose a metadata‐based content adaptation scheme. Each component technology has been implemented individually, integrated into an end‐to‐end prototype broadcasting system, and successfully tested with a set of personalized service scenarios that are also developed in this study.     

Extending metadata with scenarios in adaptive distributed system

The traditional metadata cannot provide enough support for the adaptive distributed systems. In this paper, we propose a metadata extension that uses the scenarios as semantic aspect, describing the expected interaction sequence based on XML Schema. With such constraints, resource waste and further damages can be avoided by preventing the illegal interactions at runtime. This extension is more valid and user-friendly than the majority of the existing proposals, avoiding the potential inconsistency. A prototype has been developed to illustrate the applicability of the extended metadata. The experiments demonstrate that the prototype introduces an average overhead ratio of 6.4% in the inter-process interactions and only 0.27% in the remote interactions. The approach presented in this paper is suitable for the adaptive distributed systems and affords more guarantee of reliability.     

基于三层元数据驱动模型的制造企业知识搜索平台研究

研究将制造企业信息资源进行高度整合和挖掘处理的企业知识搜索平台，通过构建三层元数据驱动模型的方法进行数据的抽取、整合、挖掘，形成凝聚企业状态和活动核心内容的知识库，最终通过该平台实现对所整合抽取知识的智能搜索。     

分幅数字地形图元数据的高效提取

元数据是"关于数据的数据",在数字地形图测绘活动中,分幅数字地形图是最重要的成果形式之一,其图外要素包含着重要的地形图元数据信息.在AutoCAD环境下,如何从分幅数字地形图中快速、灵活、高效地提取出元数据信息是本文讨论的主要内容.     

校园信息数字化服务平台的建设探究

校园信息化建设是现代教育信息化发展的必由之路。本文通过对目前国内外信息数字化服务平台的现状调查,研究了开展信息数字化服务平台建设的主要问题与技术,提出适合学校教育自身特点的信息数字化服务平台建设方案,建立系统主要模块与基本结构,最后讨论了平台的后期维护。