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1.
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
2.
Query languages for XML such as XPath or XQuery support Boolean retrieval: a query result is a (possibly restructured) subset of XML elements or entire documents that satisfy the search conditions of the query. This search paradigm works for highly schematic XML data collections such as electronic catalogs. However, for searching information in open environments such as the Web or intranets of large corporations, ranked retrieval is more appropriate: a query result is a ranked list of XML elements in descending order of (estimated) relevance. Web search engines, which are based on the ranked retrieval paradigm, do, however, not consider the additional information and rich annotations provided by the structure of XML documents and their element names.This article presents the XXL search engine that supports relevance ranking on XML data. XXL is particularly geared for path queries with wildcards that can span multiple XML collections and contain both exact-match as well as semantic-similarity search conditions. In addition, ontological information and suitable index structures are used to improve the search efficiency and effectiveness. XXL is fully implemented as a suite of Java classes and servlets. Experiments in the context of the INEX benchmark demonstrate the efficiency of the XXL search engine and underline its effectiveness for ranked retrieval. 相似文献
3.
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
4.
《Library & information science research》2005,27(2):249-263
The problem of language in Web searching has been discussed primarily in the area of cross-language information retrieval (CLIR). However, much CLIR research centers on investigation of the effectiveness of automatic translation techniques. The case study reported here explored bilingual user behaviors, perceptions, and preferences with respect to the capability of the Web as a multilingual information resource. Twenty-eight bilingual academic users from Myongji University in Korea were recruited for the study. Findings show that the subjects did not use Web search engines as multilingual tools. For search queries, they selected a language that represents their information need most accurately depending on the types of information task rather than choosing their first language. Subjects expressed concerns about the accuracy of machine translation of scholarly terminologies and preferred to have user control over multilingual Web searches. 相似文献
5.
中文搜索引擎检索语言研究 总被引：1，自引：0，他引：1
中文搜索引擎在很大程度上满了用户检索中文网络信息资源的要求，但也存在检索效果不够理想等问题，本文人检索语言的角度对现有中文搜索引擎进行分析，指出将检索语言的原理与方法应用于中文搜索引擎，必然极大地提高搜索引擎的检索效率。 相似文献
6.
[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。 相似文献
7.
Multilingual information retrieval is generally understood to mean the retrieval of relevant information in multiple target
languages in response to a user query in a single source language. In a multilingual federated search environment, different
information sources contain documents in different languages. A general search strategy in multilingual federated search environments
is to translate the user query to each language of the information sources and run a monolingual search in each information
source. It is then necessary to obtain a single ranked document list by merging the individual ranked lists from the information
sources that are in different languages. This is known as the results merging problem for multilingual information retrieval.
Previous research has shown that the simple approach of normalizing source-specific document scores is not effective. On the
other side, a more effective merging method was proposed to download and translate all retrieved documents into the source
language and generate the final ranked list by running a monolingual search in the search client. The latter method is more
effective but is associated with a large amount of online communication and computation costs. This paper proposes an effective
and efficient approach for the results merging task of multilingual ranked lists. Particularly, it downloads only a small
number of documents from the individual ranked lists of each user query to calculate comparable document scores by utilizing
both the query-based translation method and the document-based translation method. Then, query-specific and source-specific
transformation models can be trained for individual ranked lists by using the information of these downloaded documents. These
transformation models are used to estimate comparable document scores for all retrieved documents and thus the documents can
be sorted into a final ranked list. This merging approach is efficient as only a subset of the retrieved documents are downloaded
and translated online. Furthermore, an extensive set of experiments on the Cross-Language Evaluation Forum (CLEF) () data has demonstrated the effectiveness of the query-specific and source-specific results merging algorithm against other
alternatives. The new research in this paper proposes different variants of the query-specific and source-specific results
merging algorithm with different transformation models. This paper also provides thorough experimental results as well as
detailed analysis. All of the work substantially extends the preliminary research in (Si and Callan, in: Peters (ed.) Results
of the cross-language evaluation forum-CLEF 2005, 2005).
相似文献
| Hao YuanEmail: |
8.
9.
丁一 《现代图书情报技术》2005,21(6):26-29
Web 信息检索（Information Retrieval）技术研究是应用文本检索研究的成果，它结合Web图论的思想，研究Web上的信息检索，是行之有效的Web知识发现的途径。传统HITS方法所获得的信息精确度相当低，而PageRank作为一通用的搜索方法，不能够应用于特定主题的信息获取。在充分分析了PageRank、HITS等现有算法和Web文档的相似度计算方法的基础上，提出了Web上查询特定主题相关信息发现的RG-HITS算法。它结合了Web超链接、网页知识表示的信息相关度以及HITS方法来搜索Web上特定主题的相关知识。 相似文献
10.
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. 相似文献
11.
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
12.
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
13.
复合型Web信息检索系统 总被引：5，自引：0，他引：5
本文首先分析了常见的三种搜索引擎 :基于内容分析的搜索引擎、基于超链分析的搜索引擎、基于反馈分析的搜索引擎的弊端 ,提出了一种能够集三种搜索引擎优点于一身的复合型Web信息检索系统 ,并详细阐述了该系统的实现方法 相似文献
14.
Multilingual retrieval (querying of multiple document collections each in a different language) can be achieved by combining several individual techniques which enhance retrieval: machine translation to cross the language barrier, relevance feedback to add words to the initial query, decompounding for languages with complex term structure, and data fusion to combine monolingual retrieval results from different languages. Using the CLEF 2001 and CLEF 2002 topics and document collections, this paper evaluates these techniques within the context of a monolingual document ranking formula based upon logistic regression. Each individual technique yields improved performance over runs which do not utilize that technique. Moreover the techniques are complementary, in that combining the best techniques outperforms individual technique performance. An approximate but fast document translation using bilingual wordlists created from machine translation systems is presented and evaluated. The fast document translation is as effective as query translation in multilingual retrieval. Furthermore, when fast document translation is combined with query translation in multilingual retrieval, the performance is significantly better than that of query translation or fast document translation. 相似文献
15.
Armin Hust 《Informatik - Forschung und Entwicklung》2005,19(4):224-238
Information Retrieval Systeme haben in den letzten Jahren nur geringe Verbesserungen in der Retrieval Performance erzielt.
Wir arbeiten an neuen Ans?tzen, dem sogenannten Collaborativen Information Retrieval (CIR), die das Potential haben, starke
Verbesserungen zu erreichen. CIR ist die Methode, mit der durch Ausnutzen von Informationen aus früheren Anfragen die Retrieval
Peformance für die aktuelle Anfrage verbessert wird. Wir haben ein eingeschr?nktes Szenario, in dem nur alte Anfragen und
dazu relevante Antwortdokumente zur Verfügung stehen. Neue Ans?tze für Methoden der Query Expansion führen unter diesen Bedingungen
zu Verbesserungen der Retrieval Performance .
The accuracy of ad-hoc document retrieval systems has reached a stable plateau in the last few years. We are working on so-called
collaborative information retrieval (CIR) systems which have the potential to overcome the current limits. We define CIR as
a task, where an information retrieval (IR) system uses information gathered from previous search processes from one or several
users to improve retrieval performance for the current user searching for information. We focus on a restricted setting in
CIR in which only old queries and correct answer documents to these queries are available for improving a new query. For this
restricted setting we propose new approaches for query expansion procedures. We show how CIR methods can improve overall IR
performance.
CR Subject Classification H.3.3 相似文献
16.
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
17.
The collective feedback of the users of an Information Retrieval (IR) system has been shown to provide semantic information
that, while hard to extract using standard IR techniques, can be useful in Web mining tasks. In the last few years, several
approaches have been proposed to process the logs stored by Internet Service Providers (ISP), Intranet proxies or Web search
engines. However, the solutions proposed in the literature only partially represent the information available in the Web logs.
In this paper, we propose to use a richer data structure, which is able to preserve most of the information available in the
Web logs. This data structure consists of three groups of entities: users, documents and queries, which are connected in a
network of relations. Query refinements correspond to separate transitions between the corresponding query nodes in the graph,
while users are linked to the queries they have issued and to the documents they have selected. The classical query/document
transitions, which connect a query to the documents selected by the users’ in the returned result page, are also considered.
The resulting data structure is a complete representation of the collective search activity performed by the users of a search
engine or of an Intranet. The experimental results show that this more powerful representation can be successfully used in
several Web mining tasks like discovering semantically relevant query suggestions and Web page categorization by topic. 相似文献
18.
Query suggestion, which enables the user to revise a query with a single click, has become one of the most fundamental features of Web search engines. However, it has not been clear what circumstances cause the user to turn to query suggestion. In order to investigate when and how the user uses query suggestion, we analyzed three kinds of data sets obtained from a major commercial Web search engine, comprising approximately 126 million unique queries, 876 million query suggestions and 306 million action patterns of users. Our analysis shows that query suggestions are often used (1) when the original query is a rare query, (2) when the original query is a single-term query, (3) when query suggestions are unambiguous, (4) when query suggestions are generalizations or error corrections of the original query, and (5) after the user has clicked on several URLs in the first search result page. Our results suggest that search engines should provide better assistance especially when rare or single-term queries are input, and that they should dynamically provide query suggestions according to the searcher’s current state. 相似文献
19.
基于中文自然语言理解的知识检索模型 总被引：6，自引：0，他引：6
基于中文自然语言理解的知识检索模型的设计思路是:通过对用户提问及Web文档信息进行语义层次的自然语言处理,构建概念和概念网络,针对用户真实查询需求与概念网络及其映射的源文档进行推理匹配,然后对检索结果进行排序处理,提交给用户。图2。参考文献5。 相似文献
20.
AbstractThis article reports on the results of an exploratory user-centered study that examined how technological advancements in natural language processing (NLP) such as the availability of multilingual information access (MLIA) tools impact the information searching behavior of bi/multilingual academic users. Thirty-one bi/multilingual students participated in a controlled lab-based user experiment in which they carried out two assigned tasks each on Google and WorldCat for a total of four tasks, and then completed a post experiment questionnaire. The captures from the experiment showed 86.7% of the participants using multilingual information access tools. Further analyses of the captures also showed that participants were more likely to use MLIA tools when the instructions for the task were stated in their native language. An independent samples t-test revealed that participants spent less time on their searches when they used MLIA tools. The study revealed considerable diversity in the information searching behavior of the participants, even within the same pair of languages, and even for the same user. Diversity was noted for instance, on which tasks MLIA tools were used and in how these tools were used. User-centered designed, personalized multilingual information retrieval (PMLIR) models could hold promise for best representing the information searching behavior of bi/multilingual users. 相似文献