共查询到19条相似文献，搜索用时 262 毫秒
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智能情报检索与NLP 总被引：5，自引：1，他引：5
本文论述了智能情报检索、自然语言的内涵、特点，分析了国内外智能情报检索的研究状况，针对智能情报检索系统中自然语言的标引和检索及建立未来更为便捷的智能情报检索系统提出几点建议。 相似文献
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基于用户反馈与协同过滤的情报检索系统的建立 总被引：1，自引：0，他引：1
为达到简化情报检索系统中用户与系统之间的交互接口,使传统情报检索系统从“面向情报机构”和“面向检索专家”向“面向最终用户”方向转变的目的,提出引入用户反馈与协同过滤技术到情报检索系统中,并改进的情报检索系统模型,阐述基于此模型的情报检索系统的工作过程,针对该模型的协同过滤部分实现一原型系统。 相似文献
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用户认知观视野中的情报检索 总被引：4，自引：0，他引：4
回溯了情报检索的历程及研究的重点线路，分析了传统的情报检索及情报检索系统存在的一些难题。针对这些问题，指出了应从用户认知观角度来探索情报检索研究，说明了用户认知观的研究对情报检索理论带来的影响，并从用户认知观的角度对情报检索系统的开发提出了一些设想。 相似文献
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网络(联机)环境中情报检索语言的几个问题 总被引：14，自引：0，他引：14
网络环境下,情报检索系统的变革对情报检索语言提出许多新课题,本文就情报检索语言的电子化和联机显示,网络环境中情报检索语言的兼容,规范语言与自然语言结合应用以及超文本信息系统与情报检索语盲保证的问题进行了探讨。 相似文献
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情报检索进化之路--从情报检索的易用性谈起 总被引：3，自引：0，他引：3
文章从情报检索系统的易用性角度出发，分析以规范语言为媒介的传统情报检索对用户的局限性，及其只着重文献表征的系统不完善性，指出智能情报检索系统是用户与系统交流的系统，二者的互补将造就和谐的情报检索系统。 相似文献
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情报检索研究的认知观与情报检索语言的发展趋势 总被引：4，自引：1，他引：3
阐述了情报检索研究的范式转变:从系统观到认知观。并论述了认知观在情报检索各要素间交互作用的反映,以及情报检索语言的发展趋势。 相似文献
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Probabilistic topic models are unsupervised generative models which model document content as a two-step generation process, that is, documents are observed as mixtures of latent concepts or topics, while topics are probability distributions over vocabulary words. Recently, a significant research effort has been invested into transferring the probabilistic topic modeling concept from monolingual to multilingual settings. Novel topic models have been designed to work with parallel and comparable texts. We define multilingual probabilistic topic modeling (MuPTM) and present the first full overview of the current research, methodology, advantages and limitations in MuPTM. As a representative example, we choose a natural extension of the omnipresent LDA model to multilingual settings called bilingual LDA (BiLDA). We provide a thorough overview of this representative multilingual model from its high-level modeling assumptions down to its mathematical foundations. We demonstrate how to use the data representation by means of output sets of (i) per-topic word distributions and (ii) per-document topic distributions coming from a multilingual probabilistic topic model in various real-life cross-lingual tasks involving different languages, without any external language pair dependent translation resource: (1) cross-lingual event-centered news clustering, (2) cross-lingual document classification, (3) cross-lingual semantic similarity, and (4) cross-lingual information retrieval. We also briefly review several other applications present in the relevant literature, and introduce and illustrate two related modeling concepts: topic smoothing and topic pruning. In summary, this article encompasses the current research in multilingual probabilistic topic modeling. By presenting a series of potential applications, we reveal the importance of the language-independent and language pair independent data representations by means of MuPTM. We provide clear directions for future research in the field by providing a systematic overview of how to link and transfer aspect knowledge across corpora written in different languages via the shared space of latent cross-lingual topics, that is, how to effectively employ learned per-topic word distributions and per-document topic distributions of any multilingual probabilistic topic model in various cross-lingual applications. 相似文献
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《Information processing & management》2005,41(3):433-455
This paper reviews state-of-the-art techniques and methods for enhancing effectiveness of cross-language information retrieval (CLIR). The following research issues are covered: (1) matching strategies and translation techniques, (2) methods for solving the problem of translation ambiguity, (3) formal models for CLIR such as application of the language model, (4) the pivot language approach, (5) methods for searching multilingual document collection, (6) techniques for combining multiple language resources, etc. 相似文献
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A challenge for sentence categorization and novelty mining is to detect not only when text is relevant to the user’s information need, but also when it contains something new which the user has not seen before. It involves two tasks that need to be solved. The first is identifying relevant sentences (categorization) and the second is identifying new information from those relevant sentences (novelty mining). Many previous studies of relevant sentence retrieval and novelty mining have been conducted on the English language, but few papers have addressed the problem of multilingual sentence categorization and novelty mining. This is an important issue in global business environments, where mining knowledge from text in a single language is not sufficient. In this paper, we perform the first task by categorizing Malay and Chinese sentences, then comparing their performances with that of English. Thereafter, we conduct novelty mining to identify the sentences with new information. Experimental results on TREC 2004 Novelty Track data show similar categorization performance on Malay and English sentences, which greatly outperform Chinese. In the second task, it is observed that we can achieve similar novelty mining results for all three languages, which indicates that our algorithm is suitable for novelty mining of multilingual sentences. In addition, after benchmarking our results with novelty mining without categorization, it is learnt that categorization is necessary for the successful performance of novelty mining. 相似文献
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This paper proposes a learning approach for the merging process in multilingual information retrieval (MLIR). To conduct the learning approach, we present a number of features that may influence the MLIR merging process. These features are mainly extracted from three levels: query, document, and translation. After the feature extraction, we then use the FRank ranking algorithm to construct a merge model. To the best of our knowledge, this practice is the first attempt to use a learning-based ranking algorithm to construct a merge model for MLIR merging. In our experiments, three test collections for the task of crosslingual information retrieval (CLIR) in NTCIR3, 4, and 5 are employed to assess the performance of our proposed method. Moreover, several merging methods are also carried out for a comparison, including traditional merging methods, the 2-step merging strategy, and the merging method based on logistic regression. The experimental results show that our proposed method can significantly improve merging quality on two different types of datasets. In addition to the effectiveness, through the merge model generated by FRank, our method can further identify key factors that influence the merging process. This information might provide us more insight and understanding into MLIR merging. 相似文献
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【Purpose/significance】Exploring the combination principles and operational laws of the cross-language informa⁃
tion service system of multilingual digital library, formulating a cross-language information service plan that can adapt to
various needs based on idea of hierarchical management, aims to improving the degree of scientificization and standardiza⁃
tion of multilingual digital libraries in China.【Method/process】Based on idea of multilingual information channel, the real⁃
ization principle of cross-language information service in digital library is analyzed, a cross-language service matrix from
dimensions of granularity and precision on cross-language mapping is formulated. Referenced by the theory of hierarchy of
needs, cross-languages services are classified into five levels ranked from low to high. Finally, a hierarchical cross-lan⁃
guage information services model in digital library is established.【Result/conclusion】The cross-language information ser⁃
vices in digital library are classified into five levels as well as two groups. They are initial service level, improved service
level, basic service level, expansive service level and value-added level, as well as the groups of public service and profes⁃
sional services. Every level and group have different characteristics and should be provided by different strategies. 相似文献
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基于引文的信息检索可视化相关系统比较分析 总被引：1，自引：0，他引：1
分析了基于引文的信息检索系统、可视化系统及检索可视化系统三类系统的评价标准,从14个方面对6个典型系统进行深入地比较分析,找出现有的基于引文的信息检索可视化系统存在的一些不足,为国内从事相关研究的同行提供参考. 相似文献
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LexisNexis网上信息检索系统 总被引：3，自引：0，他引：3
作为目前世界上最著名、最权威的网上信息检索系统，特别是法律信息检索系统，LexisNexis无论是在信息收集的广度和深度上，还是在数据加工的规范程度和检索功能的灵活多样上，无论是在数据更新的周期上，还是在使用的方便程度上都深受世界各地用户喜爱与信赖。深入学习和掌握该系统的使用方法将对社会各界人士特别是法律界人士从事信息检索与分析，进行学术研究提供有益帮助。本文对LexisNexis系统比较有特色的功能和检索特点进行了介绍，希望能对读者了解和学习使用该系统提供帮助。 相似文献