The Effects of Conjunction, Facet Structure, and Dictionary Combinations in Concept-Based Cross-Language Retrieval

The paper studies concept-based cross-language information retrieval (CLIR). The document collection was a subset of the TREC collection. The test requests were formed from TREC's health related topics. As translation dictionaries the study used a general dictionary and a domain-specific (=medical) dictionary. The effects of translation method, conjunction, and facet order on the effectiveness of concept-based cross-language queries were studied, and concept-based structuring of cross-language queries was compared to mechanical structuring based on the output of dictionaries. The performance of translated Finnish queries against English documents was compared to the performance of original English queries against the English documents, and the performance of different CLIR query types was compared with one another. No major difference was found between concept-based and mechanical structuring. The best translation method was a simultaneous look-up in the medical dictionary and the general dictionary, in which case cross-language queries performed as well as the original English queries. The results showed that especially at high exhaustivity (the number of mutually restrictive concepts in a request) levels cross-language queries perform well in relation to monolingual queries. This suggests that conjunction disambiguates cross-language queries. An extensive study was made of the relative importance of the concepts of requests. On the basis of the classification data of request concepts it was shown how the order of facets in a query affects cross-language as well as monolingual queries.     

Using Statistical Term Similarity for Sense Disambiguation in Cross-Language Information Retrieval

With the increasing availability of machine-readable bilingual dictionaries, dictionary-based automatic query translation has become a viable approach to Cross-Language Information Retrieval (CLIR). In this approach, resolving term ambiguity is a crucial step. We propose a sense disambiguation technique based on a term-similarity measure for selecting the right translation sense of a query term. In addition, we apply a query expansion technique which is also based on the term similarity measure to improve the effectiveness of the translation queries. The results of our Indonesian to English and English to Indonesian CLIR experiments demonstrate the effectiveness of the sense disambiguation technique. As for the query expansion technique, it is shown to be effective as long as the term ambiguity in the queries has been resolved. In the effort to solve the term ambiguity problem, we discovered that differences in the pattern of word-formation between the two languages render query translations from one language to the other difficult.     

基于多语言本体的中英跨语言信息检索模型及实现

[目的/意义] 构建一个基于多语言本体的跨语言信息检索模型,有助于用户通过该模型使用自己熟悉的语言来获取不同语种的信息资源。[方法/过程] 通过本体设计及检索模型功能模块设计建立一个基于数字出版领域本体的中英跨语言信息检索模型,并利用Java语言及Lucene搜索引擎架构对该模型进行编程实现。[结果/结论] 多语言领域本体具有明确、形式化、共享、概念化、结构清晰等特征,可以作为语义层应用于跨语言信息检索系统之中,实现信息资源的语义表达。经测试,本文构建的模型能够较好地实现分词、查询扩展和语义关联等功能,促进跨语言信息检索向语义层次发展。     

跨语言信息检索探究

认为网络语言和用户语言的多样化使跨语言信息检索成为一个重要的研究领域,该领域所采用的技术主要包括基于机器翻译的方法、基于机读双语词典的方法、基于主题词表的方法以及基于平行语料库的方法。跨语言信息检索的实现除以技术为基础外,还需要查询扩展技术的辅助。     

跨语言信息检索理论与应用研究

随着互联网的全球化发展趋势，跨语言信息检索日益成为信息检索领域中的重要课题，跨语言检索可用一种提问语言检索出用另一种语言书写的信息。文章主要对跨语言信息检索理论应用研究进行了探讨，并对其在专业领域数据库中的应用提出一种思路。     

一种新的跨语言商品信息检索方法在图书搜索中的应用*

分析跨语言信息检索的基本模式和翻译消歧关键技术,采用基于词语对共现率和词语间距加权计算的方法,对查询式翻译进行消歧优化,在此基础上构建跨语言商品信息检索系统并应用于图书商品搜索,实验结果证明翻译质量和检索效果得到提高。     

跨语言信息检索进展研究

根据研究对象的变迁,国外关于跨语言信息检索的历程主要分为三个阶段。跨语言信息检索目前的主要解决方法是在单语言信息检索系统上增加一个语言转换机制。解决查询条件与查询文档集间的语言障碍有五种不同的技术路线。跨语言信息检索主要研究热点有翻译歧义研究、翻译资源构建、专有名词识别与音译研究等五个领域。     

实用型跨语言检索查询翻译接口性能改进研究

针对某网站在线运行的基于词典的查询翻译接口,对接口中实现的3种比较常用的查询翻译消歧算法进行改进,利用性能测试工具Loadrunner对改进前后的查询翻译接口的运行效率进行对比分析,最后总结影响基于词典的查询翻译的运行效率的3个主要因素。     

英汉交互式跨语言检索系统设计与实现

针对跨语言信息检索的查询翻译歧义性问题,采用交互式系统开发设计方法,对基于相关反馈的跨语言信息检索技术进行研究和分析,提出一个英汉交互式跨语言信息检索系统,实现用户辅助查询翻译、多级用户相关性判断,以及翻译优化与查询扩展等相关反馈功能,结果明显提高了检索效果。     

Dictionary-Based Cross-Language Information Retrieval: Learning Experiences from CLEF 2000–2002

In this study the basic framework and performance analysis results are presented for the three year long development process of the dictionary-based UTACLIR system. The tests expand from bilingual CLIR for three language pairs Swedish, Finnish and German to English, to six language pairs, from English to French, German, Spanish, Italian, Dutch and Finnish, and from bilingual to multilingual. In addition, transitive translation tests are reported. The development process of the UTACLIR query translation system will be regarded from the point of view of a learning process. The contribution of the individual components, the effectiveness of compound handling, proper name matching and structuring of queries are analyzed. The results and the fault analysis have been valuable in the development process. Overall the results indicate that the process is robust and can be extended to other languages. The individual effects of the different components are in general positive. However, performance also depends on the topic set and the number of compounds and proper names in the topic, and to some extent on the source and target language. The dictionaries used affect the performance significantly.     

情报检索发展的几个前沿问题

本文介绍了现阶段情报检索研究中的几个前沿问题,包括自然语言检索、跨语言检索、智能信息检索、基于语义的图像和视频检索及检索系统评价研究的最新发展情况。语言、智能和语义等问题相互关联,近年来又一同推动着信息检索的发展。检索评价研究也有针对性地引导着情报检索的发展方向。结语部分论述了这些问题在情报检索前沿发展中的本质联系及未来的发展方向。     

Using Corpus-Based Approaches in a System for Multilingual Information Retrieval

We present a system for multilingual information retrieval that allows users to formulate queries in their preferred language and retrieve relevant information from a collection containing documents in multiple languages. The system is based on a process of document level alignments, where documents of different languages are paired according to their similarity. The resulting mapping allows us to produce a multilingual comparable corpus. Such a corpus has multiple interesting applications. It allows us to build a data structure for query translation in cross-language information retrieval (CLIR). Moreover, we also perform pseudo relevance feedback on the alignments to improve our retrieval results. And finally, multiple retrieval runs can be merged into one unified result list. The resulting system is inexpensive, adaptable to domain-specific collections and new languages and has performed very well at the TREC-7 conference CLIR system comparison.     

合作信息查寻与检索的几个问题探析

在信息查寻与检索的全景图谱中探讨合作信息查寻与检索的研究语境,讨论其中英文互译问题,从行为产生、行为实现与行为结果三方面分析其内涵,基于信息检索内在发展需求及外部环境（用户需求与信息技术）分析合作信息查寻与检索研究的起源与发展动力。最后指出研究中应解决的几个核心问题：在用户信息获取谱系中的位置问题、语境功能问题、与传统研究的集成整合问题、机理机制问题、技术方法问题。     

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.     

近几年国内信息检索可视化研究综述

文章首先简要介绍了国外信息检索可视化的研究现状,然后分析了国内近几年信息检索可视化的研究领域,包括理论探讨、技术开发及实际应用等几个方面。接着指出信息检索可视化发展所面临的问题。最后提出了信息检索可视化的未来展望。     

跨语言信息检索中的词语转换方法

讨论跨语言信息检索的相关技术和有关内容，重点讨论跨语言信息检索系统所要解决的问题，并针对其中最常用的一种跨语言信息检索方法，即用户提问转换法中的关键问题--词语转换问题及其实现方法进行讨论。这些方法有基于词典的实现方法、基于索引辞典的实现方法和基于语料库的实现方法。     

查询分类在跨语言检索中的应用研究

文章旨在探讨查询分类技术和跨语言检索技术的关系,前者的应用能否改善后者的系统性能是核心问题。首先提出一种基于查询分类的标准化折扣累积增量评价指标,通过对采用查询分类技术前后信息检索系统的标准化折扣累积增量评价指标的变化进行判断,来检验该评价指标的可用性和有效性。同时,查询分类可以作为降低跨语言检索系统查询翻译的歧义性的技术手段。对大规模查询集随机抽样的查询翻译实验结果表明,本文提出的基于查询分类的查询翻译消歧方法对大部分查询有效,在一些情况下甚至可以直接通过本方法完成查询翻译。结合其他方法进一步消除翻译的歧义性则是下一步的工作内容。     

网上农业信息资源检索工具及检索方法

论文介绍了因特网上具有权威性和实用性的农业信息资源检索工具及其检索方法，为获取网上农业文献信息资源提供了有效途径。     

Towards Universal Text Retrieval: Tipster Text Retrieval Research at New Mexico State University

New Mexico State University's Computing Research Lab has participated in research in all three phases of the US Government's Tipster program. Our work on information retrieval has focused on research and development of multilingual and cross-language approaches to automatic retrieval. The work on automatic systems has been supplemented by additional research into the role of the IR system user in interactive retrieval scenarios: monolingual, multilingual and cross-language. The combined efforts suggest that universal text retrieval, in which a user can find, access and use documents in the face of language differences and information overload, may be possible.     

基于伪相关反馈的跨语言查询扩展

相关反馈是一种重要的查询重构技术,本文分析了两类相关反馈技术,一是按用户是否参与可分为伪相关反馈和交互式相关反馈,二是按作用于查询的方式可分为查询扩展与检索词重新加权.在此基础上,本文重点探讨了将相关反馈技术应用于跨语言信息检索,提出了翻译前查询扩展、翻译后查询扩展、翻译前与翻译后相结合的查询扩展三种方法.最后,本文通过伪相关反馈实验对这三种方法进行了比较,实验结果显示,三种跨语言查询扩展方法都能够有效地提高检索结果的精度,其中翻译后查询扩展方法相对更优越.此外,查询式的长度对不同跨语言查询扩展方法产生着不同程度的影响.