一种支持信息检索的安全网络文件存储模型

网络技术的发展使利用网络进行文件存储和共享逐渐成为一种重要的网络应用模式。如何在网络上存储文件并实现安全有效的共享成为一个必须解决的问题。当前对安全的网络存储模型的研究大都集中在安全方面,对共享所必须的信息检索支持不充分,这大大影响了数据的共享性。本文提出了一种新型的网络存储系统模型,该模型综合运用了压缩、加密和信息检索等技术,能有效地解决信息发布中的网络存储的安全性和共享性问题。在原型系统上进行的实验表明,该模型具有良好的性能。     

Crossing textual and visual content in different application scenarios

This paper deals with multimedia information access. We propose two new approaches for hybrid text-image information processing that can be straightforwardly generalized to the more general multimodal scenario. Both approaches fall in the trans-media pseudo-relevance feedback category. Our first method proposes using a mixture model of the aggregate components, considering them as a single relevance concept. In our second approach, we define trans-media similarities as an aggregation of monomodal similarities between the elements of the aggregate and the new multimodal object. We also introduce the monomodal similarity measures for text and images that serve as basic components for both proposed trans-media similarities. We show how one can frame a large variety of problem in order to address them with the proposed techniques: image annotation or captioning, text illustration and multimedia retrieval and clustering. Finally, we present how these methods can be integrated in two applications: a travel blog assistant system and a tool for browsing the Wikipedia taking into account the multimedia nature of its content.

A research on social network-based personalized semantic retrieval model

Personalized semantic retrieval extends the query process and optimizes query results by mapping user preference of information to ontology. It can fetch different results according to the same queries from different users. This paper proposes a personalized semantic retrieval model based on social network. It implements the organization, presentation, acquisition and maintenance of user preference data. Finally, it uses these personalization data in the process of information retrieval.     

Chinese-based research on subject-covered information retrieval supervised by textual semantic domain

By means of analysis of artificial intervention in ready-retrieved text, training set used to compare with new texts from large-scale real texts corpus is provided. It is based on the data-originated presentation of training set that a special formula to calculate semantic cohesion between new texts and training set is devised. The semantic cohesion of new text is the average value of semantic evaluation of all elements involved, and semantic evaluation of an element depends on its semantic relevance with the training set and on the semantic ratio of its domain to synonymous domain. In terms of empirical verification a conclusion is drawn that semantic cohesion is the key measurement standard of textual retrieval. Despite the advantages of textual retrieval, limitations of formula-raised condition and analyst＇s accomplishments make the analysis involved in this paper imperfect.     

设计素描中材质感的表现在时装画中的应用

本文介绍了设计素描的概念和研究要素,指出设计素描中材质感的表现形式——线和明暗,并从时装面料和服饰配件两方面阐述了线和明暗在时装画中的应用,为我们认识、理解和感悟设计素描在服装设计中的作用提供了切入点。     

Hybrid information retrieval policies based on cooperative cache in mobile P2P networks

The concept of Peer-to-Peer (P2P) has been introduced into mobile networks, which has led to the emergence of mobile P2P networks, and originated potential applications in many fields. However,mobile P2P networks are subject to the limitations of transmission range, and highly dynamic and unpredictable network topology, giving rise to many new challenges for efficient information retrieval. In this paper, we propose an automatic and economical hybrid information retrieval approach based on cooperative cache. In this method, the region covered by a mobile P2P network is partitioned into subregions, each of which is identified by a unique ID and known to all peers. All the subregions then constitute a mobile Kademlia (MKad) network. The proposed hybrid retrieval approach aims to utilize the floodingbased and Distributed Hash Table (DHT)-based schemes in MKad for indexing and searching according to the designed utility functions. To further facilitate information retrieval, we present an effective cache update method by considering all relevant factors. At the same time, the combination of two different methods for cache update is also introduced. One of them is pull based on time stamp including two different pulls: an on-demand pull and a periodical pull, and the other is a push strategy using update records. Furthermore, we provide detailed mathematical analysis on the cache hit ratio of our approach. Simulation experiments in NS-2 showed that the proposed approach is more accurate and efficient than the existing methods.     

一种主动感知的纹理图像检索方法(英文)

基于Contourlet变换和支持向量机提出了一种新的纹理图像检索方法。在这种方法中,能量和广义高斯分布参数被用做Contourlet子带图像的特征。通过这种表示,提出了由一类和二类支持向量机组成的两阶段检索算法来完成感知相似性测度。通过具有640个纹理图像的VisTex库和具有1760个纹理图像的Brodatz库证明了所提方法的有效性。实验结果表明,对于这两个纹理库,新的纹理图像检索方法的平均检索率分别达99.38%和98.07%。     

一种多模态信息融合的视频检索模型

针对包含复杂语义信息的视频检索的需要,提出了一种基于关系代数的多模态信息融合视频检索模型,该模型充分利用视频包含的文本、图像、高层语义概念等多模态特征,构造了对应于多个视频特征的查询模块,并创新地使用关系代数表达式对查询得到的多模态信息进行融合。实验表明,该模型能够充分发挥多模型视频检索及基于关系代数表达式的融合策略在复杂语义视频检索中的优势,得到较好的查询结果。     

基于ROI多特征和相关反馈的图像检索算法

本文提出了一种基于感兴趣区域(ROI)综合多特征和相关反馈的图像检索算法.在对图像进行四叉树分解的基础上,由用户选择感兴趣区域,综合颜色、纹理和形状三种底层特征进行多层感兴趣区域检索;由相关反馈技术体现用户感知的主观性,通过调整感兴趣区域、特征问、特征内的权重来提高查准率.给出了改进的CBIR通用模型和特征权重模型.实现了一个图像检索原型系统,将不同实验结果进行了比较和分析,实验结果表明,该文提出的方法具有良好的检索效果.