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1.
Research on cross-language information retrieval (CLIR) has typically been restricted to settings using binary relevance assessments.
In this paper, we present evaluation results for dictionary-based CLIR using graded relevance assessments in a best match
retrieval environment. A text database containing newspaper articles and a related set of 35 search topics were used in the
tests. First, monolingual baseline queries were automatically formed from the topics. Secondly, source language topics (in
English, German, and Swedish) were automatically translated into the target language (Finnish), using structured target queries.
The effectiveness of the translated queries was compared to that of the monolingual queries. Thirdly, pseudo-relevance feedback
was used to expand the original target queries. CLIR performance was evaluated using three relevance thresholds: stringent,
regular, and liberal. When regular or liberal threshold was used, a reasonable performance was achieved. Using stringent threshold,
equally high performance could not be achieved. On all the relevance thresholds the performance of the translated queries
was successfully raised by pseudo-relevance feedback based query expansion. However, the performance of the stringent threshold
in relation to the other thresholds could not be raised by this method. 相似文献
2.
This study develops regression models for predicting the performance of cross-language information retrieval (CLIR). The model assumes that CLIR performance can be explained by two factors: (1) the ease of search inherent in each query and (2) the translation quality in the process of CLIR systems. As operational variables, monolingual information retrieval (IR) performance is used for measuring the ease of search, and the well-known evaluation metric BLEU is used to measure the translation quality. This study also proposes an alternative metric, weighted average for matched unigrams (WAMU), which is tailored to gauging translation quality for special IR purposes. The data for regression analysis are obtained from a retrieval experiment of English-to-Italian bilingual searches using the CLEF 2003 test collection. The CLIR and monolingual IR performances are measured by average precision score. The result shows that the proposed regression model can explain about 60% of the variation in CLIR performance, and WAMU has more predictive power than BLEU. A back translation method for applying the regression model to operational CLIR systems in real situations is discussed. 相似文献
3.
Dictionary-Based Cross-Language Information Retrieval: Problems, Methods, and Research Findings 总被引：3，自引：1，他引：2
Ari Pirkola Turid Hedlund Heikki Keskustalo Kalervo Järvelin 《Information Retrieval》2001,4(3-4):209-230
This paper reviews literature on dictionary-based cross-language information retrieval (CLIR) and presents CLIR research done at the University of Tampere (UTA). The main problems associated with dictionary-based CLIR, as well as appropriate methods to deal with the problems are discussed. We will present the structured query model by Pirkola and report findings for four different language pairs concerning the effectiveness of query structuring. The architecture of our automatic query translation and construction system is presented. 相似文献
4.
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. 相似文献
5.
Fernando Martínez-Santiago L. Alfonso Ureña-López Maite Martín-Valdivia 《Information Retrieval》2006,9(1):71-93
A usual strategy to implement CLIR (Cross-Language Information Retrieval) systems is the so-called query translation approach.
The user query is translated for each language present in the multilingual collection in order to compute an independent monolingual
information retrieval process per language. Thus, this approach divides documents according to language. In this way, we obtain
as many different collections as languages. After searching in these corpora and obtaining a result list per language, we
must merge them in order to provide a single list of retrieved articles.
In this paper, we propose an approach to obtain a single list of relevant documents for CLIR systems driven by query translation.
This approach, which we call 2-step RSV (RSV: Retrieval Status Value), is based on the re-indexing of the retrieval documents
according to the query vocabulary, and it performs noticeably better than traditional methods.
The proposed method requires query vocabulary alignment: given a word for a given query, we must know the translation or translations
to the other languages. Because this is not always possible, we have researched on a mixed model. This mixed model is applied
in order to deal with queries with partial word-level alignment. The results prove that even in this scenario, 2-step RSV
performs better than traditional merging methods. 相似文献
6.
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
7.
In this paper, we study different applications of cross-language latent topic models trained on comparable corpora. The first focus lies on the task of cross-language information retrieval (CLIR). The Bilingual Latent Dirichlet allocation model (BiLDA) allows us to create an interlingual, language-independent representation of both queries and documents. We construct several BiLDA-based document models for CLIR, where no additional translation resources are used. The second focus lies on the methods for extracting translation candidates and semantically related words using only per-topic word distributions of the cross-language latent topic model. As the main contribution, we combine the two former steps, blending the evidences from the per-document topic distributions and the per-topic word distributions of the topic model with the knowledge from the extracted lexicon. We design and evaluate the novel evidence-rich statistical model for CLIR, and prove that such a model, which combines various (only internal) evidences, obtains the best scores for experiments performed on the standard test collections of the CLEF 2001–2003 campaigns. We confirm these findings in an alternative evaluation, where we automatically generate queries and perform the known-item search on a test subset of Wikipedia articles. The main importance of this work lies in the fact that we train translation resources from comparable document-aligned corpora and provide novel CLIR statistical models that exhaustively exploit as many cross-lingual clues as possible in the quest for better CLIR results, without use of any additional external resources such as parallel corpora or machine-readable dictionaries. 相似文献
8.
面对日益膨胀的多语种信息资源,跨语言信息检索已成为实现全球知识存取和共享的关键技术手段。构建一个实用型的跨语言检索查询翻译接口,可方便地嵌入任意的信息检索平台,扩展现有信息检索平台的多语言信息处理能力。该查询翻译接口采用基于最长短语、查询分类和概率词典等多种翻译消歧策略,并从查询翻译的准确性和接口的运行效率两个角度对构建的查询翻译接口进行评测,实验结果验证所采用方法具有可行性。 相似文献
9.
M. á. García-Cumbreras F. Martínez-Santiago L. A. Ure?a-López 《Information Retrieval》2012,15(5):413-432
Given a user question, the goal of a Question Answering (QA) system is to retrieve answers rather than full documents or even best-matching passages, as most Information Retrieval systems currently do. In this paper, we present BRUJA, a QA system for the management of multilingual collections. BRUJ rkstions (English, Spanish and French). The BRUJA architecture is not formed with three monolingual QA systems but instead uses English as Interlingua to make usual QA tasks such as question classifications and answer extractions. In addition, BRUJA uses Cross Language Information Retrieval (CLIR) techniques to retrieve relevant documents from a multilingual collection. On the one hand, we have more documents to find answers from but on the other hand, we are introducing noise into the system because of translations to the Interlingua (English) and the CLIR module. The question is whether the difficulty of managing three languages is worth it or whether a monolingual QA system delivers better results. We report on in-depth experimentation and demonstrate that our multilingual QA system gets better results than its monolingual counterpart whenever it uses good translation resources and, especially, CLIR techniques that are state-of-the-art. 相似文献
10.
Turid Hedlund Eija Airio Heikki Keskustalo Raija Lehtokangas Ari Pirkola Kalervo Järvelin 《Information Retrieval》2004,7(1-2):99-119
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. 相似文献
11.
Cross-language information retrieval (CLIR) has so far been studied with the assumption that some rich linguistic resources such as bilingual dictionaries or parallel corpora are available. But creation of such high quality resources is labor-intensive and they are not always at hand. In this paper we investigate the feasibility of using only comparable corpora for CLIR, without relying on other linguistic resources. Comparable corpora are text documents in different languages that cover similar topics and are often naturally attainable (e.g., news articles published in different languages at the same time period). We adapt an existing cross-lingual word association mining method and incorporate it into a language modeling approach to cross-language retrieval. We investigate different strategies for estimating the target query language models. Our evaluation results on the TREC Arabic–English cross-lingual data show that the proposed method is effective for the CLIR task, demonstrating that it is feasible to perform cross-lingual information retrieval with just comparable corpora. 相似文献
12.
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
13.
隐含语义检索及其应用 总被引：5，自引：1，他引：4
隐含语义检索(Latent Semantic Indexing, LSI) 是一种基于概念的文献检索方式。它区别于传统的基于用户查询条件与文档的单词匹配的文献检索方法, 根据文档与查询条件在语义上的关联而向用户提交查询结果。本文介绍了隐含语义检索在文献检索中的一种实现方法, 为文献检索提供了一种新的途径。 相似文献
14.
This work reviews information retrieval systems developed at ITC-irst which were evaluated through several tracks of CLEF, during the last three years. The presentation tries to follow the progress made over time in developing new statistical models first for monolingual information retrieval, then for cross-language information retrieval. Besides describing the underlying theory, performance of monolingual and bilingual information retrieval models are reported, respectively, on Italian monolingual tracks and Italian-English bilingual tracks of CLEF. Monolingual systems by ITC-irst performed consistently well in all the official evaluations, while the bilingual system ranked in CLEF 2002 just behind competitors using commercial machine translation engines. However, by experimentally comparing our statistical topic translation model against a state-of-the-art commercial system, no statistically significant difference in retrieval performance could be measured on a larger set of queries. 相似文献
15.
Prior-art search in patent retrieval is concerned with finding all existing patents relevant to a patent application. Since patents often appear in different languages, cross-language information retrieval (CLIR) is an essential component of effective patent search. In recent years machine translation (MT) has become the dominant approach to translation in CLIR. Standard MT systems focus on generating proper translations that are morphologically and syntactically correct. Development of effective MT systems of this type requires large training resources and high computational power for training and translation. This is an important issue for patent CLIR where queries are typically very long sometimes taking the form of a full patent application, meaning that query translation using MT systems can be very slow. However, in contrast to MT, the focus for information retrieval (IR) is on the conceptual meaning of the search words regardless of their surface form, or the linguistic structure of the output. Thus much of the complexity of MT is not required for effective CLIR. We present an adapted MT technique specifically designed for CLIR. In this method IR text pre-processing in the form of stop word removal and stemming are applied to the MT training corpus prior to the training phase. Applying this step leads to a significant decrease in the MT computational and training resources requirements. Experimental application of the new approach to the cross language patent retrieval task from CLEF-IP 2010 shows that the new technique to be up to 23 times faster than standard MT for query translations, while maintaining IR effectiveness statistically indistinguishable from standard MT when large training resources are used. Furthermore the new method is significantly better than standard MT when only limited translation training resources are available, which can be a significant issue for translation in specialized domains. The new MT technique also enables patent document translation in a practical amount of time with a resulting significant improvement in the retrieval effectiveness. 相似文献
16.
汉英词典作为沟通中文与英语两种不同语言的桥梁,是中国与世界交流的工具。在信息时代飞速发展的今天,双语词典的自动构建技术在机器翻译和跨语言检索领域起着重要的作用,本文对双语词典的自动构建方法和其中的关键技术进行了比较全面的分析和总结,并提出一种从汉英平行语料库中抽取双语词语,自动构建双语词典的方法,在实现汉英句子级对齐后,对双语语料分别进行分词和词性标注处理,通过抽取汉英词语单元并计算其关联概率来实现汉英的词语对齐,最终生成双语词典。该方法在对真实语料的双语词典构建实验中取得了较好的结果,词对齐效果优于传统的IBM模型方法。 相似文献
17.
18.
认为多语言信息存取（MLIA）是数字图书馆面临的一个重要问题,而跨语言信息搜索（CLIR）则是MLIA的主要应用,CLIR中以用户为中心的研究相比以技术为中心的研究少但正日益受到重视。目前CLIR中的用户需求、用户行为、用户体验或用户满意度等的定性或定量研究已发展为交互式跨语言信息搜索即interactive CLIR（iCLIR）。从系统的角度对国内外主要的iCLIR研究进行对比,揭示其用户交互技术策略,分析其翻译消歧、查询优化等核心技术,预测未来iCLIR的发展趋势。 相似文献
19.
20.
本体在跨语言信息检索中的应用机制研究 总被引：3，自引：1，他引：2
解释多语本体的含义,指出其在不同语言中所对应的领域知识,分析多语本体在查询扩展、语义标注、基于概念索引3方面对改善跨语言信息检索的作用,并通过介绍EuroWorldNet和Cindor系统的多语本体概念的对应方法,探讨本体应用于跨语言信息检索最关键的多语本体库的映射方法,认为采用中间语言作为概念表示、并通过词典翻译对照与不同语种的词汇建立链接关系是多语本体映射的一种良好方法。 相似文献