网上隐性信息及其检索策略

本文分析了网上隐性信息的概念及成因，提出了隐性信息的检索策略。     

如何有效地利用互联网上的标准数据库

根据所收录标准文献的学科范围，将互联网上的标准数据库分为综合型标准库和专业型标准库，并列举出这两类标准库的几个典型实例，对其基本情况和检索系统进行比较分析，同时提出在互联网上有效地检索标准文献的具体方法、步骤及应注意的事项。     

ILASⅡ连续出版物管理子系统的检索策略

本文以ILASⅡ连续出版物管理子系统为例,探讨条件检索和批检索的特点,分析检索途径和检索键值的选择,提出实用的检索策略。关于工作集和光笔的应用亦有心得。     

知识管理对图书馆虚拟参考咨询服务的理论阐释

本文探讨以知识管理的研究视角对图书馆虚拟参考咨询服务进行理论阐释与实践引导。认为图书馆的虚拟参考咨询服务应做到：加强对显性知识的序化组织与展示，重视用户自助服务；采取善待电话咨询、完善Web表单咨询、配合Chat咨询的思路，深化图书馆虚拟参考咨询服务；重视人本管理，实现馆员与用户之间隐性知识资源的充分开发与交互；强化参考咨询软件的知识库功能，以及与馆藏资源检索无缝整合的功能，实现隐性知识与显性知识的互动转换；发扬知识联盟与知识共享的图书馆传统，走合作虚拟参考咨询之路。     

CJN及电子期刊检索与应用

中国期刊网是集我国自然科学、工程技术、人文社会科学核心期刊和专业特色期刊为一体的大型全文检索系统，具有学科覆盖面宽、编辑合理、信息更新快、全文数据全息化处理等特点。检索系统吸收了结构化数据库检索的特点，采用了传统和智能化相结合的多入口、多检索点方案。具有强大的检索功能。探讨了CJN的特点及其检索方法和技巧。     

在有限信息集上的智能检索接口的实现方法*

探讨了有限信息集和智能检索的特点, 并对智能检索中常用的技术和适用这些技术的信息表达方法, 结合所开发的项目进行了介绍。这些技术是交叉树索引、分解匹配综合。一般信息管理系统都只使用有限信息集, 为之开发较友好的具有智能的人机接口是可行的。这也是当今信息系统发展的主流。因此, 本文探讨的问题具有一定的普遍意义。     

白沙能源股份有限公司电力分公司

悠悠耒水傍春枝，白沙电力竟光明。白沙能源股份有限公司电力分公司其前身系白沙矿务局机电厂，是一家集发供电、机械加工制造、建筑与安装、印刷等于一体的国有综合型企业，     

网络隐性信息探微

本文从网上隐性信息的概念入手，简要分析其形成原因，井着重从检索的角度提出了八条策略，并通过应用实例作了相关分析。     

隐性采访与记者的角色冲突

隐性采访，按照笔者的理解，是记者隐去职业身份而进行的一种采访方式，即以非记者身份进行的采访，基于这一定义，加上对于近年来大量隐性采访案例的分析，笔者发现，记者在隐性采访中存在着较为普遍的角色冲突现象，下面，试对隐性采访中记者角色冲突的表现与规避方法进行一番探讨。     

试论图书馆隐性知识管理

隐性知识管理是知识管理的主要内容，是一种以高度个人化和难以规范化的隐性知识为对象的知识管理。本文论述了图书馆内存在的隐性知识，探讨了隐性知识管理的内涵及内容，并阐述了对图书馆内存在的隐性知识进行管理的必要性和方法。     

New Approaches to Spoken Document Retrieval

This paper presents four novel techniques for open-vocabulary spoken document retrieval: a method to detect slots that possibly contain a query feature; a method to estimate occurrence probabilities; a technique that we call collection-wide probability re-estimation and a weighting scheme which takes advantage of the fact that long query features are detected more reliably. These four techniques have been evaluated using the TREC-6 spoken document retrieval test collection to determine the improvements in retrieval effectiveness with respect to a baseline retrieval method. Results show that the retrieval effectiveness can be improved considerably despite the large number of speech recognition errors.     

Retrieval quality vs. effectiveness of specificity-oriented search in XML collections

Content-only queries in hierarchically structured documents should retrieve the most specific document nodes which are exhaustive to the information need. For this problem, we investigate two methods of augmentation, which both yield high retrieval quality. As retrieval effectiveness, we consider the ratio of retrieval quality and response time; thus, fast approximations to the 'correct' retrieval result may yield higher effectiveness. We present a classification scheme for algorithms addressing this issue, and adopt known algorithms from standard document retrieval for XML retrieval. As a new strategy, we propose incremental-interruptible retrieval, which allows for instant presentation of the top ranking documents. We develop a new algorithm implementing this strategy and evaluate the different methods with the INEX collection.     

Exploiting Manual Indexing to Improve Collection Selection and Retrieval Effectiveness

Vocabulary incompatibilities arise when the terms used to index a document collection are largely unknown, or at least not well-known to the users who eventually search the collection. No matter how comprehensive or well-structured the indexing vocabulary, it is of little use if it is not used effectively in query formulation. This paper demonstrates that techniques for mapping user queries into the controlled indexing vocabulary have the potential to radically improve document retrieval performance. We also show how the use of controlled indexing vocabulary can be employed to achieve performance gains for collection selection. Finally, we demonstrate the potential benefit of combining these two techniques in an interactive retrieval environment. Given a user query, our evaluation approach simulates the human user's choice of terms for query augmentation given a list of controlled vocabulary terms suggested by a system. This strategy lets us evaluate interactive strategies without the need for human subjects.     

基于概念空间方法的信息检索技术研究

为了解决词汇差异问题,词表构造在信息检索系统中有着重要意义。概念空间方法是利用计算机自动构造概念语义网络(词表)并以此为基础进行概念检索的一种方法。由词语作为语义网络的节点,词语之间的关联权重以一个给定文档集合中词语的共现率来计算,其大小代表它们之间的相似性。检索时系统采用人工智能方法激活与检索入口词相关的术语或概念,为用户提供交互式的检索用语建议。方法的具体步骤包括文档和对象列表收集、对象过滤和自动标引、共现分析和联想检索四个阶段。这种方法多用于英文检索系统,但对我国的信息检索系统也有重要的借鉴意义。     

On Collection Size and Retrieval Effectiveness

The relationship between collection size and retrieval effectiveness is particularly important in the context of Web search. We investigate it first analytically and then experimentally, using samples and subsets of test collections. Different retrieval systems vary in how the score assigned to an individual document in a sample collection relates to the score it receives in the full collection; we identify four cases.We apply signal detection (SD) theory to retrieval from samples, taking into account the four cases and using a variety of shapes for relevant and irrelevant distributions. We note that the SD model subsumes several earlier hypotheses about the causes of the decreased precision in samples. We also discuss other models which contribute to an understanding of the phenomenon, particularly relating to the effects of discreteness. Different models provide complementary insights.Extensive use is made of test data, some from official submissions to the TREC-6 VLC track and some new, to illustrate the effects and test hypotheses. We empirically confirm predictions, based on SD theory, that P@n should decline when moving to a sample collection and that average precision and R-precision should remain constant. SD theory suggests the use of recall-fallout plots as operating characteristic (OC) curves. We plot OC curves of this type for a real retrieval system and query set and show that curves for sample collections are similar but not identical to the curve for the full collection.     

问答式信息检索查询优化技术研究

问答式信息检索是新一代搜索引擎,它接收自然语言描述的问题,在文档集合中搜索并返回问题的精确答案.问答式信息检索中,检索模块性能的提高将直接影响问题回答系统的整体性能.本文研究系统中的查询优化技术,包括两种策略:基于模式知识库的查询优化;挖掘Web语义蕴含信息,构建查询扩展资源.本文利用TREC提供的问题集与答案集(TREC8-TREC13)做实验来测试查询优化方法的性能,实验结果表明,相对于传统的查询生成,本文采用的查询优化技术在检索精度上取得了提高,t-test结果证明,系统性能提高统计显著.     

An Evaluation of Automatically Constructed Hypertexts for Information Retrieval

This paper assesses the retrieval effectiveness of automatically constructed inter-document hypertext links in Information Retrieval (IR). The objectives of the experiments described are to obtain evidence concerning the usefulness of querying and browsing automatically constructed IR hypertexts. Links are built by using IR techniques, as these enable rapid, automatic production of hypertexts from a document collection for accessing the collection itself. These tests are carried out in a laboratory environment and through simulation of link browsing. Results of experiments show that browsing has little impact on the retrieval of relevant documents if used in place of querying or relevance feedback methods, though may be practical if used in combination with them.     

Combining Multiple Strategies for Effective Monolingual and Cross-Language Retrieval

This paper describes and evaluates different retrieval strategies that are useful for search operations on document collections written in various European languages, namely French, Italian, Spanish and German. We also suggest and evaluate different query translation schemes based on freely available translation resources. In order to cross language barriers, we propose a combined query translation approach that has resulted in interesting retrieval effectiveness. Finally, we suggest a collection merging strategy based on logistic regression that tends to perform better than other merging approaches.     

A Bayesian Framework for XML Information Retrieval: Searching and Learning with the INEX Collection

Most recent document standards like XML rely on structured representations. On the other hand, current information retrieval systems have been developed for flat document representations and cannot be easily extended to cope with more complex document types. The design of such systems is still an open problem. We present a new model for structured document retrieval which allows computing scores of document parts. This model is based on Bayesian networks whose conditional probabilities are learnt from a labelled collection of structured documents—which is composed of documents, queries and their associated assessments. Training these models is a complex machine learning task and is not standard. This is the focus of the paper: we propose here to train the structured Bayesian Network model using a cross-entropy training criterion. Results are presented on the INEX corpus of XML documents.     

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对当前情报界“情报检索”与“文献检索”的相互关系、有关“情报检索”类型的几种常见的观点进行了分析，认为情报检索与文献检索实质上是相同的。