The challenge of commercial document retrieval,Part I: Major issues,and a framework based on search exhaustivity,determinacy of representation and document collection size

With the growing focus on what is collectively known as “knowledge management”, a shift continues to take place in commercial information system development: a shift away from the well-understood data retrieval/database model, to the more complex and challenging development of commercial document/information retrieval models. While document retrieval has had a long and rich legacy of research, its impact on commercial applications has been modest. At the enterprise level most large organizations have little understanding of, or commitment to, high quality document access and management. Part of the reason for this is that we still do not have a good framework for understanding the major factors which affect the performance of large-scale corporate document retrieval systems. The thesis of this discussion is that document retrieval—specifically, access to intellectual content—is a complex process which is most strongly influenced by three factors: the size of the document collection; the type of search (exhaustive, existence or sample); and, the determinacy of document representation. Collectively, these factors can be used to provide a useful framework for, or taxonomy of, document retrieval, and highlight some of the fundamental issues facing the design and development of commercial document retrieval systems. This is the first of a series of three articles. Part II (D.C. Blair, The challenge of commercial document retrieval. Part II. A strategy for document searching based on identifiable document partitions, Information Processing and Management, 2001b, this issue) will discuss the implications of this framework for search strategy, and Part III (D.C. Blair, Some thoughts on the reported results of Text REtrieval Conference (TREC), Information Processing and Management, 2002, forthcoming) will consider the importance of the TREC results for our understanding of operating information retrieval systems.     

Query modification based on relevance back-propagation in an ad hoc environment

It is well-known that relevance feedback is a method significant in improving the effectiveness of information retrieval systems. Improving effectiveness is important since these information retrieval systems must gain access to large document collections distributed over different distant sites. As a consequence, efforts to retrieve relevant documents have become significantly greater. Relevance feedback can be viewed as an aid to the information retrieval task. In this paper, a relevance feedback strategy is presented. The strategy is based on back-propagation of the relevance of retrieved documents using an algorithm developed in a neural approach. This paper describes a neural information retrieval model and emphasizes the results obtained with the associated relevance back-propagation algorithm in three different environments: manual ad hoc, automatic ad hoc and mixed ad hoc strategy (automatic plus manual ad hoc).     

视频检索的用户策略

用户策略研究是检索领域需要考虑的重要问题之一。在这篇论文中,笔者首先介绍了国外研究视频检索系统用户策略的一个实验。然后,笔者将该实验得到的一些结论与一般的检索系统相比较。最后,笔者指出了视频检索系统设计应该注意的一些问题。     

On selection and combining of relevance indicators

Identifying and representing the content of a document was, and still is, one of the main concerns of information retrieval systems. Representation of content is not dependent of the search strategy and other elements of information retrieval systems (IRS) but rather has some relationship with them.In the conventional IRS, each document in the file is characterized by one or more index terms which supposedly describe its content. Those terms are assigned from the natural language or from a pre-prepared list (Thesaurus). Over the years, other means of representing content were suggested. Also, attempts were made to combine several of them assuming independence.This paper discusses the attributes of the items in the data-base and their qualities. It seems that there is no single one which has all the desired qualities.If the attributes are not totally independent neither highly correlated then combining them in a certain way may increase effectiveness. The justification for this comes from the users' information seeking behavior—users are using index terms, author's names, citations, and other attributes in their searches.A model to accomodate the above hypothesis is formulated and the small experiment performed indicates that the hypothesis may be true, and this way of combining might improve effectiveness.     

综合运用VIP、CNKI、万方数据系统功能提高课题检索效率

基于科技文献检索的信息发现与信息检索,探讨VIP、CNKI、万方数据知识服务平台系统功能在课题检索中的应用。在信息发现方面,综合运用各数据库系统功能寻找检索概念的同义词、课题相关的分类号和所属学科类别、抽象检索概念的相关词、课题相关的研究机构和研究者。在信息检索方面,根据各系统的功能特点不同,制定相应的课题检索策略——主题     

基于WEB的信息检索多媒体CAI课件的优化设计

本文介绍了基于Web的信息检索多媒体CAI课件的实质，在分析信息检索多媒体CAI课件利弊的基础上，探讨了基于Web的信息检索多媒体CAI课件优化设计应遵循的原则及开发的一般策略。     

便于快速入门的检索策略模式

文章针对3个较适合于国内信息检索课教学的检索策略模式,采用案例分析的方式进行论述,归纳了检索策略优化的多种方法。目的是通过消化吸收,取其精华,为我所用,以便供信息检索课教学参考,促进大学生信息获取技能和创新能力的提高。     

引文检索策略的探讨

引文检索是一种比较复杂的信息检索,在具体的引文检索中,如何制定优良的检索策略是一个关系到能否获得满意检索结果的核心问题。本文就引文检索的实际工作中所触及到的一些常见的典型问题提出了若干探讨性的意见。     

应用性本科信息检索课教学改革的构想

应用性本科院校培养的是技术型、实用型人才。因而应用性本科院校信息检索课的教学内容和课程重点，应协调好理论与实战、检索与利用、中文信息与外文信息的关系。增加信息服务系统介绍、加强阅读指导、改革教材等几个方面进行改革。     

Specifics of information retrieval for young users: A survey

In this paper, we present the state of the art in the field of information retrieval that is relevant for understanding how to design information retrieval systems for children. We describe basic theories of human development to explain the specifics of young users, i.e., their cognitive skills, fine motor skills, knowledge, memory and emotional states in so far as they differ from those of adults. We derive the implications these differences have on the design of information retrieval systems for children. Furthermore, we summarize the main findings about children’s search behavior from multiple user studies. These findings are important to understand children’s information needs, their search strategies and usage of information retrieval systems. We also identify several weaknesses of previous user studies about children’s information-seeking behavior. Guided by the findings of these user studies, we describe challenges for the design of information retrieval systems for young users. We give an overview of algorithms and user interface concepts. We also describe existing information retrieval systems for children, in specific web search engines and digital libraries. We conclude with a discussion of open issues and directions for further research. The survey provided in this paper is important both for designers of information retrieval systems for young users as well as for researchers who start working in this field.     

The weighted Condorcet fusion in information retrieval

The Condorcet fusion is a distinctive fusion method and was found useful in information retrieval. Two basic requirements for the Condorcet fusion to improve retrieval effectiveness are: (1) all component systems involved should be more or less equally effective; and (2) each information retrieval system should be developed independently and thus each component result is more or less equally different from the others. These two requirements may not be satisfied in many cases, then weighted Condorcet becomes a good option. However, how to assign weights for the weighted Condorcet has not been investigated.     

基于互联网的海量信息检索系统检索策略模式研究

在检索系统对基于互联网的海量信息进行检索的过程中,检索效率很大程度上取决于检索策略的质量。为提高检索策略的正确性,本文根据信息逻辑检索的基本原理,并参照DIALOG系统,提出了检索需求的主题分析法则,并在此基础上建立了检索策略优化模型。同时,还给出了此模型在操作执行过程中的组配机制。     

基于科技查新案例的文献检索课检索策略教学研究

论述了将科技查新案例引入高校文献检索课教学的必要性,着重探讨了文献检索课检索策略章节如何运用查新案例提高教学效果。结果显示,将大量的科技查新案例引入检索策略教学能调动学生学习积极性．取得较好的教学效果。     

跨语言信息检索初探

随着互联网的发展，网络成为人们获取信息的重要来源，但是语言的藩篱却限制了人们获取信息的自由。跨语言信息检索应运而生。本文将从理论和实践两方面对跨语言信息检索进行论述：理论方面分析了实现跨语言信息检索的方法和策略；实践方面则以Mulinex系统和Google搜索引擎为例，介绍了跨语言信息检索在实际中的应用。     

A logic basis for information retrieval

This paper examines the potential of recent work in artificial intelligence for the development of more effective information retrieval systems. The primary task in this research has been to examine and define the role of an expert system in the domain of bibliographic retrieval. Once such a goal can be described the available knowledge representations and techniques can be evaluated. This paper examines the role of an expert bibliographic retrieval system, examines an artificial intelligence view of information retrieval, and then describes a prototype expert information retrieval system that has been designed and implemented.     

网络信息资源的知识检索研究

本文介绍信息检索到知识检索的发展,比较知识检索与信息检索的区别和联系,提出基于Internet分布式信息资源的两级检索策略,分析知识检索的发展所需要解决的问题。     

A reliable FAQ retrieval system using a query log classification technique based on latent semantic analysis

To obtain high performances, previous works on FAQ retrieval used high-level knowledge bases or handcrafted rules. However, it is a time and effort consuming job to construct these knowledge bases and rules whenever application domains are changed. To overcome this problem, we propose a high-performance FAQ retrieval system only using users’ query logs as knowledge sources. During indexing time, the proposed system efficiently clusters users’ query logs using classification techniques based on latent semantic analysis. During retrieval time, the proposed system smoothes FAQs using the query log clusters. In the experiment, the proposed system outperformed the conventional information retrieval systems in FAQ retrieval. Based on various experiments, we found that the proposed system could alleviate critical lexical disagreement problems in short document retrieval. In addition, we believe that the proposed system is more practical and reliable than the previous FAQ retrieval systems because it uses only data-driven methods without high-level knowledge sources.     

Mathematical model of time-effective information retrieval system based on the theory of fuzzy sets

Search patterns of documents and information requests are their better or worse representatives only, so it is important to carry on examinations on possibilities of designing self-learning information retrieval systems. Another important question is to elaborate such an organization of document search pattern set as to obtain an acceptable response time of the information system to a given information request.A self-learning process of the proposed information system consists in the determination—on a set of document and information request search patterns—of the similarity relation according to L. A. Zadeh.The organization of a set of document search patterns proposed in the paper ensures the limitation of document search pattern set searching process—when retrieving a response to a given information request—to one (or several) subset from previously determined subsets. This makes the information system response time acceptable. The proposed information retrieval strategy is discussed in terms of fuzzy sets.     

Using information gain to improve multi-modal information retrieval systems

Nowadays, access to information requires managing multimedia databases effectively, and so, multi-modal retrieval techniques (particularly images retrieval) have become an active research direction. In the past few years, a lot of content-based image retrieval (CBIR) systems have been developed. However, despite the progress achieved in the CBIR, the retrieval accuracy of current systems is still limited and often worse than only textual information retrieval systems. In this paper, we propose to combine content-based and text-based approaches to multi-modal retrieval in order to achieve better results and overcome the lacks of these techniques when they are taken separately. For this purpose, we use a medical collection that includes both images and non-structured text. We retrieve images from a CBIR system and textual information through a traditional information retrieval system. Then, we combine the results obtained from both systems in order to improve the final performance. Furthermore, we use the information gain (IG) measure to reduce and improve the textual information included in multi-modal information retrieval systems. We have carried out several experiments that combine this reduction technique with a visual and textual information merger. The results obtained are highly promising and show the profit obtained when textual information is managed to improve conventional multi-modal systems.