基于内容的智能网络多媒体信息过滤检索

The paper discusses the construction of a content-based intelligent system that performs multimedia information filtering and retrieving on the Internet. The system disassembles the multimedia information into different media objects and describes them with vectors for content-based retrieval. In the user study module, the system uses the BP neural network to clarify the user interests for intelligent filtering and retrieving.     

情报检索语言的词汇控制问题

本文在情报检索语言和自然语言原理、交流方式等简要比较的基础上,对情报检索中词汇控制的必要性,词汇控制的内容,原则以及词汇控制对检索效率的影响,进行了探讨。     

光盘数据库检索方式的新发展

The main changes in the three commonly-used CD-ROM retrieval systems are introduced,including the enhancement of the window functions,the change of the field index function in SP software and the new saving and reusing functions of ProQuest for its retrieval strategies.     

中文网络目录分类体系的优化

本文根据现有中文网络目录分类体系的经验,借鉴传统分类法,提出了中文网络目录分类体系的优化方案,并建立了一个包含一级类目和二级类目的统一的分类体系.     

Parsimonious translation models for information retrieval

In the KL divergence framework, the extended language modeling approach has a critical problem of estimating a query model, which is the probabilistic model that encodes the user’s information need. For query expansion in initial retrieval, the translation model had been proposed to involve term co-occurrence statistics. However, the translation model was difficult to apply, because the term co-occurrence statistics must be constructed in the offline time. Especially in a large collection, constructing such a large matrix of term co-occurrences statistics prohibitively increases time and space complexity. In addition, reliable retrieval performance cannot be guaranteed because the translation model may comprise noisy non-topical terms in documents. To resolve these problems, this paper investigates an effective method to construct co-occurrence statistics and eliminate noisy terms by employing a parsimonious translation model. The parsimonious translation model is a compact version of a translation model that can reduce the number of terms containing non-zero probabilities by eliminating non-topical terms in documents. Through experimentation on seven different test collections, we show that the query model estimated from the parsimonious translation model significantly outperforms not only the baseline language modeling, but also the non-parsimonious models.     

An empirical study of query expansion and cluster-based retrieval in language modeling approach

The term mismatch problem in information retrieval is a critical problem, and several techniques have been developed, such as query expansion, cluster-based retrieval and dimensionality reduction to resolve this issue. Of these techniques, this paper performs an empirical study on query expansion and cluster-based retrieval. We examine the effect of using parsimony in query expansion and the effect of clustering algorithms in cluster-based retrieval. In addition, query expansion and cluster-based retrieval are compared, and their combinations are evaluated in terms of retrieval performance by performing experimentations on seven test collections of NTCIR and TREC.     

Query expansion with terms selected using lexical cohesion analysis of documents

We present new methods of query expansion using terms that form lexical cohesive links between the contexts of distinct query terms in documents (i.e., words surrounding the query terms in text). The link-forming terms (link-terms) and short snippets of text surrounding them are evaluated in both interactive and automatic query expansion (QE). We explore the effectiveness of snippets in providing context in interactive query expansion, compare query expansion from snippets vs. whole documents, and query expansion following snippet selection vs. full document relevance judgements. The evaluation, conducted on the HARD track data of TREC 2005, suggests that there are considerable advantages in using link-terms and their surrounding short text snippets in QE compared to terms selected from full-texts of documents.     

因特网信息检索模式及其优化设想

本文论述了因特网环境下基于超文本的浏览模式和基于搜索引擎的检索模式两种信息检索模式的产生、原理和缺陷。并根据其现存问题及网络资源自身的特点,着重就建立专业性的网络资源指引库、受控语言的引入和使用、“智能代理”的应用、跟踪记录检索路径和内容提示以及使用语义——文献双层数据结构五点优化设想进行了简要分析。     

信息技术与数字图书馆建设的探索

数字图书馆具有信息资源数字化、信息组织非线性化、结构复杂化、信息传递网络化、服务方式多样化等特点。随着信息技术的飞速发展,如何通过信息技术手段,将图书馆内部的档案、资料、图书等内容进行数字化的管理与利用势在必行。     

信息素质理念下体育文献检索课改革

通过对现行体育文献检索课的教学体系、教材内容进行调整,紧密结合体育专业的特点,增加新知识、新技能的传授,突出实践环节。在此基础上转变教学模式,依托专业特点开展课程群建设,形成多层次的教学体系,才能发挥体育文献检索课的作用。