基于本体的信息检索研究

介绍了本体Ontology的概念和理论知识,提出一种基于本体的Web信息检索模型.该模型利用本体技术对Internet上的各类信息进行领域分类,规范用户信息检索模式,以达到快速、准确找到用户所需信息的目的.     

基于自动问答系统的信息检索技术研究进展

自动问答是根据用户以自然语言提出的问题给出一个明确的答案。近年来,自动问答越来越受到信息检索和自然语言处理的研究者的关注。典型的自动问答系统通常包含问题分析、文段检索和答案选择等部件。介绍了自动问答的最新研究进展和相关国际会议情况,着重阐述问题分类、查询扩展、文段检索和答案选择这四个热点技术的主要功能和常用方法,最后提出存在的一些问题和展望。     

综合纹理特征和语义信息的医学图像检索

提出一种结合图像分块纹理特征和语义信息的医学胸片图像检索方法。同时,介绍了颜色特征提取方法中的颜色相关图算法。据此,实现了一个图像检索原型系统,依据所设计的评价实验,将不同实验的检索结果进行了比较和分析。实验证明,结合图像分块纹理特征和语义信息的检索方法具有较好的检索效果。     

基于本体的信息检索模型研究

根据文档处理方式的不同,将基于本体的信息检索系统分为基于知识库的语义检索系统和基于语义网文档的信息检索系统两类。对这两个模型的实现原理和关键步骤进行了阐述;探讨了基于本体的信息检索模型中的关键技术,并指出当前研究中存在的不足;最后对基于本体的信息检索系统的研究热点和方向进行了展望。     

基于颜色特征的视频数据库检索系统

为了在视频数据库中提供有效的视频检索和浏览功能,必须建立高效的索引.由于视频数据具有层次性的结构,在镜头边界检测后,可以利用聚类方法按不同的相似性尺度对镜头关键帧进行处理,对视频数据建立索引.该系统采用颜色特征,使用Twin Comparison算法实现镜头检测和直方图平均法实现关键帧提取,对关键帧采用K均值聚类算法处理,建立视频数据库索引.实验结果表明该系统能较好地实现视频快速浏览和检索功能.     

一种基于Agent的因特网信息获取系统

文中在分析传统的搜索引擎和离线济览软件优缺点的基础上,提出了一种基本代理的因特网信息获取方案,并实现了集自动下载、全文检索和离线济览功能于一体的WebClone系统,使用户获取和共享因特网信息更加方便。     

MAPBOT: a Web based map information retrieval system

Many types of information are geographically referenced and interactive maps provide a natural user interface to such data. However, map presentation in geographical information systems and on the Web is closed related to traditional cartography and provides a very limited interactive experience. In this paper, we present MAPBOT, an interactive Web based map information retrieval system in which Web users can easily and efficiently search geographical information with the assistance of a user interface agent (UIA). Each kind of map feature such as a building or a motorway works as an agent called a Maplet. Each Maplet has a user interface level to assist the user to find information of interest and a graphic display level that controls the presence and the appearance of the feature on the map. The semantic relationships of Maplets are defined in an Ontology Repository provided by the system which is used by the UIA to assist a user to semantically and efficiently search map information interested. An Ontology Editor with a graphic user interface has been implemented to update the Ontology Repository. Visualization on the client is based on Scalable Vector Graphics which provides a high quality Web map.     

基于Ontology的Web信息检索系统研究

传统的信息检索技术以关键字匹配为主,缺乏语义推理能力,对用户的查询请求没有提供语义制导,因此造成信息的误检、漏检.将Ontology用于Web信息检索,分析了Ontology的语义表达能力,提出了基于Ontology的信息检索系统模型(MIRSO).MIRSO能够对用户提供语义制导,将用户的查询条件映射为领域Ontology的概念和关系,使用户的需求表达和信息内容精确匹配.实验结果表明,该方法能够提高信息检索系统的查准率.     

Evaluating information retrieval system performance based on user preference

One of the challenges of modern information retrieval is to rank the most relevant documents at the top of the large system output. This calls for choosing the proper methods to evaluate the system performance. The traditional performance measures, such as precision and recall, are based on binary relevance judgment and are not appropriate for multi-grade relevance. The main objective of this paper is to propose a framework for system evaluation based on user preference of documents. It is shown that the notion of user preference is general and flexible for formally defining and interpreting multi-grade relevance. We review 12 evaluation methods and compare their similarities and differences. We find that the normalized distance performance measure is a good choice in terms of the sensitivity to document rank order and gives higher credits to systems for their ability to retrieve highly relevant documents.     

基于本体的智能信息检索系统的构建方法

为了解决目前传统的信息检索工具返回大量无关的信息或漏检有用信息的问题,首先引入了本体的基本概念及其在信息检索中的用途,在此基础上提出了一种基于本体的智能信息检索系统模型.该模型首先使用基于SOM神经网络和分层聚类的两阶聚类算法自动的产生本体,免除了人工构造本体的繁琐,然后利用本体中概念及概念之间明确的关系描述,将用户提出的检索要求进行语义上的扩充,使信息检索过程更加智能化,大大提高了检索的查全率和查准率.     

基于元搜索引擎的专业式智能网络信息检索系统

随着网络信息资源的迅速增加和实时更新,如何及时准确地获取自己所需的有用信息是现代网络信息检索技术需要解决的主要问题。介绍了一种基于元搜索引擎的新型专业式智能网络信息检索系统。该系统建立专业词库和用户知识库,结合人工智能的Agent技术,能够很好地对用户的兴趣进行自适应学习,以实现个性化的信息检索,既保证了查全率,又提高了检索结果的查准率。     

基于Web挖掘的个性化信息检索系统总体设计

随着网络信息的急速膨胀,为了方便用户快速查找所需信息,满足不同用户的个性化需求,在传统的信息检索系统的基础上发展个性化信息检索已成为必然.本文研究了个性化信息检索系统的整体架构设计,描述了该系统的主要功能模块和各个功能模块的工作机制.     

User-private information retrieval based on a peer-to-peer community

Private information retrieval (PIR) is normally modeled as a game between two players: a user and a database. The user wants to retrieve some item from the database without the latter learning which item is retrieved. Most current PIR protocols are ill-suited to provide PIR from a search engine or large database: (i) their computational complexity is linear in the size of the database; (ii) they assume active cooperation by the database server in the PIR protocol. If the database cannot be assumed to cooperate, a peer-to-peer (P2P) user community is a natural alternative to achieve some query anonymity: a user gets her queries submitted on her behalf by other users in the P2P community. In this way, the database still learns which item is being retrieved, but it cannot obtain the real query histories of users, which become diffused among the peer users. We name this relaxation of PIR user-private information retrieval (UPIR). A peer-to-peer UPIR system is described in this paper which relies on an underlying combinatorial structure to reduce the required key material and increase availability. Extensive simulation results are reported and a distributed key management version of the system is described.     

基于SIFT特征的图像检索

提出一种多尺度图像检索算法,该算法基于SIFT特征提取,它将一幅图像转换成特征向量的集合,图像间的相似距离是通过计算两幅图像特征向量间的欧氏距离来实现的.实验结果很好地说明了该算法具有尺度、平移、旋转不变性,一定的仿射、光照不变性以及算法能很好地应用在特定形状特征目标的检索中.     

基于自然语言理解的智能化多媒体信息检索系统研究

多媒体信息由于维度高、数据量大、可解释性差等特征制约了其检索性能,提出了基于自然语言理解的智能化多媒体信息检索系统模型。该系统基于自然语言理解、数据挖掘、自反馈等技术的运用,在一定程度上扩大了检索范围,提高了检索准确率。     

基于最大加权区域互信息的声呐图像检索系统

针对声呐图像检索的实际需求,设计基于最大加权区域互信息的声呐图像检索系统。对声呐图像进行分割,产生n个子区域;计算例图与图像库中各个图像子区域之间的互信息,结合声呐图像目标物体的特点,对区域互信息进行加权;取加权区域互信息中的最大值作为图像互信息,并照其大小进行图像排序,经门限处理后,将排在前面的图像作为检索结果输出。仿真实验结果表明:基于最大加权区域互信息的检索方法更加适用于声呐图像检索,尤其是在处理两幅背景相同前景不同或者前景相同背景不同的图像时更有优势。     

基于语义的信息检索模型

由于查询与文档中词语的不匹配现象导致一些相关的文档不能被成功地检索出来,在信息检索的研究与实现中,这是影响检索效果的一个很关键的问题。把概念图和知网结合起来,提出对应的相关反馈算法,重新计算词项权重,利用向量空间模型和语义相似度进行语义检索,并给出了语义检索模型。实验结果显示该方法取得了良好的效果。     

Adaptive content-based music retrieval system

This paper presents a tunable content-based music retrieval (CBMR) system suitable the for retrieval of music audio clips. The audio clips are represented as extracted feature vectors. The CBMR system is expert-tunable by altering the feature space. The feature space is tuned according to the expert-specified similarity criteria expressed in terms of clusters of similar audio clips. The main goal of tuning the feature space is to improve retrieval performance, since some features may have more impact on perceived similarity than others. The tuning process utilizes our genetic algorithm. The R-tree index for efficient retrieval of audio clips is based on the clustering of feature vectors. For each cluster a minimal bounding rectangle (MBR) is formed, thus providing objects for indexing. Inserting new nodes into the R-tree is efficiently performed because of the chosen Quadratic Split algorithm. Our CBMR system implements the point query and the n-nearest neighbors query with the O(logn) time complexity. Different objective functions based on cluster similarity and dissimilarity measures are used for the genetic algorithm. We have found that all of them have similar impact on the retrieval performance in terms of precision and recall. The paper includes experimental results in measuring retrieval performance, reporting significant improvement over the untuned feature space.     

基于政务网的搜索引擎及信息检索系统设计

对于政务网产生的政务信息越来越多,信息组织分散,信息结构多样的现实问题,如何统一并有效地管理是新一代搜索引擎及信息检索系统开发需要解决的问题。文章探讨了政务网信息采集和检索业务的应用目标,分析了系统的应用需求,从设计和实现的角度阐述了系统的开发思路、总体框架和主要功能。     

基于嵌入式ARM_linux的远程基站信息获取系统设计

针对远距离测量系统中基站之间距离远、现场获取信息困难的问题,提出了基于嵌入式ARM_linux的远程基站信息获取方案。根据Windows和linux环境下socket网络编程原理,设计了VC＋＋系统管理的PC机客户端,并采用Qt／Embedded编程实现了ARM9服务端。实验结果表明,系统能够有效获取远程基站的数据信息,适用于远程测试及设备远程健康管理和诊断技术中。