共查询到19条相似文献，搜索用时 171 毫秒
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英汉交互式跨语言检索系统设计与实现 总被引：1，自引：0，他引：1
吴丹 《现代图书情报技术》2009,3(2):89-95
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。 相似文献
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跨语言信息检索进展研究 总被引：7，自引：1，他引：6
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。 相似文献
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许多研究已经探讨了跨语言和多语言信息检索问题,并提出了多种实现方法,特别是针对查询的翻译.但是大多数的方法都将跨语言检索问题看成是两个分开的步骤查询的翻译和单语检索.而对于多语言信息检索,则另外再加上一个结果合成的步骤.在本文中,我们提出一种一体化的检索方法,即将查询的翻译看成是整个检索过程的一部分.使用这种一体化的方法能充分将翻译和检索中的不确定性结合起来,从而达到更好的整体优化,也能将单语言信息检索的方法用于跨语言及多语言信息检索. 相似文献
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跨语言信息检索中的询问翻译方法及其研究进展 总被引：10，自引：0，他引：10
主要介绍了跨语言文本信息检索的三类基本方法：询问翻译、文献翻译和不翻译，并且对目前最常用的询问翻译方法所涉及的一些基本问题及其研究进展进行了阐述，最后总结出跨语言信息检索的现状和动向。 相似文献
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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。 相似文献
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国外跨语言信息检索中的翻译歧义性问题研究综述 总被引：2，自引：0，他引：2
翻译歧义是影响跨语言信息检索效果的主要因素之一。本文论述了跨语言信息检索中翻译歧义性问题产生的原因，并且总结了目前消除这种歧义的方法和技术。 相似文献
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交互式跨语言信息检索是信息检索的一个重要分支。在分析交互式跨语言信息检索过程、评价指标、用户行为进展等理论研究基础上,设计一个让用户参与跨语言信息检索全过程的用户检索实验。实验结果表明:用户检索词主要来自检索主题的标题;用户判断文档相关性的准确率较高;目标语言文档全文、译文摘要、译文全文都是用户认可的判断依据;翻译优化方法以及翻译优化与查询扩展的结合方法在用户交互环境下非常有效;用户对于反馈后的翻译仍然愿意做进一步选择;用户对于与跨语言信息检索系统进行交互是有需求并认可的。用户行为分析有助于指导交互式跨语言信息检索系统的设计与实践。 相似文献
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基于伪相关反馈的跨语言查询扩展 总被引：3，自引：2，他引：1
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. 相似文献
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本体驱动的跨语言信息检索研究 总被引：5，自引：0，他引：5
吴丹 《现代图书情报技术》2006,1(5):22-26
分析跨语言信息检索技术的翻译歧异性问题，指出多语本体的引入可以提高语义排歧的准确性，详细分析两个国外的跨语言信息检索系统，并在此基础上提出一个基于双语本体的中英跨语言信息检索模型及实现方案。 相似文献
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信息检索模型与逻辑理论 总被引：6，自引：0，他引：6
本文从另外一个角度讨论信息检索模型。基于逻辑理论,本文定义了一种查询与知识集的等价关系,从逻辑的角度描述了查询与信息检索系统之间的关系、查询与作为检索结果的文献集之间的关系。 相似文献
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Using Statistical Term Similarity for Sense Disambiguation in Cross-Language Information Retrieval 总被引：2，自引：0，他引：2
Mirna Adriani 《Information Retrieval》2000,2(1):71-82
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. 相似文献
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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. 相似文献
16.
Query structuring and expansion with two-stage term dependence for Japanese web retrieval 总被引：1，自引：1，他引：0
In this paper, we propose a new term dependence model for information retrieval, which is based on a theoretical framework
using Markov random fields. We assume two types of dependencies of terms given in a query: (i) long-range dependencies that
may appear for instance within a passage or a sentence in a target document, and (ii) short-range dependencies that may appear
for instance within a compound word in a target document. Based on this assumption, our two-stage term dependence model captures
both long-range and short-range term dependencies differently, when more than one compound word appear in a query. We also
investigate how query structuring with term dependence can improve the performance of query expansion using a relevance model.
The relevance model is constructed using the retrieval results of the structured query with term dependence to expand the
query. We show that our term dependence model works well, particularly when using query structuring with compound words, through
experiments using a 100-gigabyte test collection of web documents mostly written in Japanese. We also show that the performance
of the relevance model can be significantly improved by using the structured query with our term dependence model.
相似文献
| Koji EguchiEmail: |
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In Information Retrieval, since it is hard to identify users’ information needs, many approaches have been tried to solve
this problem by expanding initial queries and reweighting the terms in the expanded queries using users’ relevance judgments.
Although relevance feedback is most effective when relevance information about retrieved documents is provided by users, it
is not always available. Another solution is to use correlated terms for query expansion. The main problem with this approach
is how to construct the term-term correlations that can be used effectively to improve retrieval performance. In this study,
we try to construct query concepts that denote users’ information needs from a document space, rather than to reformulate initial queries using the term correlations
and/or users’ relevance feedback. To form query concepts, we extract features from each document, and then cluster the features into primitive concepts that are then used to form
query concepts. Experiments are performed on the Associated Press (AP) dataset taken from the TREC collection. The experimental evaluation
shows that our proposed framework called QCM (Query Concept Method) outperforms baseline probabilistic retrieval model on
TREC retrieval. 相似文献
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In this paper we evaluate the application of data fusion or meta-search methods, combining different algorithms and XML elements, to content-oriented retrieval of XML structured data. The primary approach is the combination of a probabilistic methods using Logistic regression and the Okapi BM-25 algorithm for estimation of document relevance or XML element relevance, in conjunction with Boolean approaches for some query elements. In the evaluation we use the INEX XML test collection to examine the relative performance of individual algorithms and elements and compare these to the performance of the data fusion approaches. 相似文献
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TIJAH: Embracing IR Methods in XML Databases 总被引：1，自引：0，他引：1
This paper discusses our participation in INEX (the Initiative for the Evaluation of XML Retrieval) using the TIJAH XML-IR system. TIJAHs system design follows a standard layered database architecture, carefully separating the conceptual, logical and physical levels. At the conceptual level, we classify the INEX XPath-based query expressions into three different query patterns. For each pattern, we present its mapping into a query execution strategy. The logical layer exploits score region algebra (SRA) as the basis for query processing. We discuss the region operators used to select and manipulate XML document components. The logical algebra expressions are mapped into efficient relational algebra expressions over a physical representation of the XML document collection using the pre-post numbering scheme. The paper concludes with an analysis of experiments performed with the INEX test collection. 相似文献