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1.
Due to the heavy use of gene synonyms in biomedical text, people have tried many query expansion techniques using synonyms in order to improve performance in biomedical information retrieval. However, mixed results have been reported. The main challenge is that it is not trivial to assign appropriate weights to the added gene synonyms in the expanded query; under-weighting of synonyms would not bring much benefit, while overweighting some unreliable synonyms can hurt performance significantly. So far, there has been no systematic evaluation of various synonym query expansion strategies for biomedical text. In this work, we propose two different strategies to extend a standard language modeling approach for gene synonym query expansion and conduct a systematic evaluation of these methods on all the available TREC biomedical text collections for ad hoc document retrieval. Our experiment results show that synonym expansion can significantly improve the retrieval accuracy. However, different query types require different synonym expansion methods, and appropriate weighting of gene names and synonym terms is critical for improving performance.
Chengxiang ZhaiEmail:
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2.
Applying Machine Learning to Text Segmentation for Information Retrieval   总被引:2,自引:0,他引:2  
We propose a self-supervised word segmentation technique for text segmentation in Chinese information retrieval. This method combines the advantages of traditional dictionary based, character based and mutual information based approaches, while overcoming many of their shortcomings. Experiments on TREC data show this method is promising. Our method is completely language independent and unsupervised, which provides a promising avenue for constructing accurate multi-lingual or cross-lingual information retrieval systems that are flexible and adaptive. We find that although the segmentation accuracy of self-supervised segmentation is not as high as some other segmentation methods, it is enough to give good retrieval performance. It is commonly believed that word segmentation accuracy is monotonically related to retrieval performance in Chinese information retrieval. However, for Chinese, we find that the relationship between segmentation and retrieval performance is in fact nonmonotonic; that is, at around 70% word segmentation accuracy an over-segmentation phenomenon begins to occur which leads to a reduction in information retrieval performance. We demonstrate this effect by presenting an empirical investigation of information retrieval on Chinese TREC data, using a wide variety of word segmentation algorithms with word segmentation accuracies ranging from 44% to 95%, including 70% word segmentation accuracy from our self-supervised word-segmentation approach. It appears that the main reason for the drop in retrieval performance is that correct compounds and collocations are preserved by accurate segmenters, while they are broken up by less accurate (but reasonable) segmenters, to a surprising advantage. This suggests that words themselves might be too broad a notion to conveniently capture the general semantic meaning of Chinese text. Our research suggests machine learning techniques can play an important role in building adaptable information retrieval systems and different evaluation standards for word segmentation should be given to different applications.  相似文献   

3.
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   

4.
Information retrieval systems operating on free text face difficulties when word forms used in the query and documents do not match. The usual solution is the use of a “stemming component” that reduces related word forms to a common stem. Extensive studies of such components exist for English, but considerably less is known for other languages. Previously, it has been claimed that stemming is essential for highly declensional languages. We report on our experiments on stemming for German, where an additional issue is the handling of compounds, which are formed by concatenating several words. The major contribution of our work that goes beyond its focus on German lies in the investigation of a complete spectrum of approaches, ranging from language-independent to elaborate linguistic methods. The main findings are that stemming is beneficial even when using a simple approach, and that carefully designed decompounding, the splitting of compound words, remarkably boosts performance. All findings are based on a thorough analysis using a large reliable test collection.  相似文献   

5.
The present research studies the impact of decompounding and two different word normalization methods, stemming and lemmatization, on monolingual and bilingual retrieval. The languages in the monolingual runs are English, Finnish, German and Swedish. The source language of the bilingual runs is English, and the target languages are Finnish, German and Swedish. In the monolingual runs, retrieval in a lemmatized compound index gives almost as good results as retrieval in a decompounded index, but in the bilingual runs differences are found: retrieval in a lemmatized decompounded index performs better than retrieval in a lemmatized compound index. The reason for the poorer performance of indexes without decompounding in bilingual retrieval is the difference between the source language and target languages: phrases are used in English, while compounds are used instead of phrases in Finnish, German and Swedish. No remarkable performance differences could be found between stemming and lemmatization.  相似文献   

6.
为解决各引文数据库的检索方法、检索结果展示方式不一、引文著录不规范等问题,解放军医学图书馆采用 NET 框架作为系统的开发平台,采用 C/S 结构模式,在生物医学引文数据库的基础上构建生物医学文献引文集成检索整合平台,实现了统一平台一站式检索、自动去重、自动分组和便捷输出规范的引文报告等个性化功能,提高了生物医学文献查引效率。  相似文献   

7.
基于词向量扩展的学术资源语义检索技术   总被引:1,自引:0,他引:1  
[目的/意义] 尝试以统计的方法为指导思想,探究基于词向量扩展的语义检索技术来提升学术资源的语义检索能力。[方法/过程] 利用自然语言处理、文本挖掘技术,对采集来的学术资源(主要是学术论文)元数据进行预处理,结合word2vec词向量生成工具和elasticsearch全文检索引擎搭建语义检索系统,对学术资源进行语义检索的探索研究。[结果/结论] 本文提出的方法能够有效提升学术信息的检索效果,一定程度上实现学术资源的语义检索,并为后续语义检索的进一步研究提供借鉴。  相似文献   

8.
In this paper, which treats Swedish full text retrieval, the problem of morphological variation of query terms in the document database is studied. The Swedish CLEF 2003 test collection was used, and the effects of combination of indexing strategies with query terms on retrieval effectiveness were studied. Four of the seven tested combinations involved indexing strategies that used normalization, a form of conflation. All of these four combinations employed compound splitting, both during indexing and at query phase. SWETWOL, a morphological analyzer for the Swedish language, was used for normalization and compound splitting. A fifth combination used stemming, while a sixth attempted to group related terms by right hand truncation of query terms. The truncation was performed by a search expert. These six combinations were compared to each other and to a baseline combination, where no attempt was made to counteract the problem of morphological variation of query terms in the document database. Both the truncation combination, the four combinations based on normalization and the stemming combination outperformed the baseline. Truncation had the best performance. The main conclusion of the paper is that truncation, normalization and stemming enhanced retrieval effectiveness in comparison to the baseline. Further, normalization and stemming were not far below truncation.  相似文献   

9.
董慧  余传明  姜赢  杨宁  徐国虎  张华 《情报学报》2006,25(4):451-461
语义信息提取是一项较新的技术,本文讨论语义信息提取的定义、原理和思路,并以国共两党关系历史为领域背景,详细分析语义信息提取的过程,即对于待处理的自然语言文字,将其进行分段和分句;针对拆分出的句子,进行分词和词性标注;在词性标注的基础上选择适当动词作为句子的语义谓词;判断该谓词是否属于语义谓词列表;再根据语义谓词来获取相关的语义实体,同时对于指示代词进行消解;最后对时间和地点维进行提取,并更新语义提取背景。本文还对开发过程中所用到的数据结构、关键算法进行了分析。  相似文献   

10.
运用非结构化信息挖掘,对网络评论情感进行分析是一个非常重要的方法。本文基于Web客户评论情感文本,在情感文本预处理过程中使用四种不同的停用词表,采用两种不同的特征选择方法,选用著名的TF-IDF权重计算方法,使用基于RBF核函数的支持向量机方法的分类器实现了对携程网上采集的4000个酒店客户评论情感文本的分类研究。通过实验,分析了不同特征选择方和停用词表的使用对客户评论文本情感分类的影响,提出了基于情感文本分类的有效的停用词表。  相似文献   

11.
The Cross-Language Evaluation Forum has encouraged research in text retrieval methods for numerous European languages and has developed durable test suites that allow language-specific techniques to be investigated and compared. The labor associated with crafting a retrieval system that takes advantage of sophisticated linguistic methods is daunting. We examine whether language-neutral methods can achieve accuracy comparable to language-specific methods with less concomitant software complexity. Using the CLEF 2002 test set we demonstrate empirically how overlapping character n-gram tokenization can provide retrieval accuracy that rivals the best current language-specific approaches for European languages. We show that n = 4 is a good choice for those languages, and document the increased storage and time requirements of the technique. We report on the benefits of and challenges posed by n-grams, and explain peculiarities attendant to bilingual retrieval. Our findings demonstrate clearly that accuracy using n-gram indexing rivals or exceeds accuracy using unnormalized words, for both monolingual and bilingual retrieval.  相似文献   

12.
The images found within biomedical articles are sources of essential information useful for a variety of tasks. Due to the rapid growth of biomedical knowledge, image retrieval systems are increasingly becoming necessary tools for quickly accessing the most relevant images from the literature for a given information need. Unfortunately, article text can be a poor substitute for image content, limiting the effectiveness of existing text-based retrieval methods. Additionally, the use of visual similarity by content-based retrieval methods as the sole indicator of image relevance is problematic since the importance of an image can depend on its context rather than its appearance. For biomedical image retrieval, multimodal approaches are often desirable. We describe in this work a practical multimodal solution for indexing and retrieving the images contained in biomedical articles. Recognizing the importance of text in determining image relevance, our method combines a predominately text-based image representation with a limited amount of visual information, in the form of quantized content-based visual features, through a process called global feature mapping. The resulting multimodal image surrogates are easily indexed and searched using existing text-based retrieval systems. Our experimental results demonstrate that our multimodal strategy significantly improves upon the retrieval accuracy of existing approaches. In addition, unlike many retrieval methods that utilize content-based visual features, the response time of our approach is negligible, making it suitable for use with large collections.  相似文献   

13.
文本信息检索技术进展和性能评价框架   总被引:6,自引:0,他引:6  
本文介绍TREC 评价信息检索系统的动向及其在推动研制新型检索系统中所起的作用, 并介绍新型检索系统的模式和特征及国外商品化全文文本检索系统性能评测指标。文中探讨了文本信息检索的性质评价标准问题, 并提出一个中文文本信息检索的系统评价框架。  相似文献   

14.
文本检索的潜在语义索引法初探   总被引:5,自引:0,他引:5  
传统的文本检索方式是基于提问集合和文本集合的单纯语词匹配检索,然而这并不能解决检索实践过程中存在的同义和多义问题。文章阐述了文本检索的潜在语义索引法的原理并通过实验来验证潜在语义索引可以用来解决同义和多义问题,完善检索系统的性能。  相似文献   

15.
Significant progress has been made in information retrieval covering text semantic indexing and multilingual analysis. However, developments in Arabic information retrieval did not follow the extraordinary growth of Arabic usage in the Web during the ten last years. In the tasks relating to semantic analysis, it is preferable to directly deal with texts in their original language. Studies on topic models, which provide a good way to automatically deal with semantic embedded in texts, are not complete enough to assess the effectiveness of the approach on Arabic texts. This paper investigates several text stemming methods for Arabic topic modeling. A new lemma-based stemmer is described and applied to newspaper articles. The Latent Dirichlet Allocation model is used to extract latent topics from three Arabic real-world corpora. For supervised classification in the topics space, experiments show an improvement when comparing to classification in the full words space or with root-based stemming approach. In addition, topic modeling with lemma-based stemming allows us to discover interesting subjects in the press articles published during the 2007–2009 period.  相似文献   

16.
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   

17.
中文全文检索技术的研究及实现   总被引:9,自引:0,他引:9  
李梅  王庆林 《情报学报》2003,22(1):10-17
本文设计了一个中文全文检索系统 ,在单汉字全文数据库的基础之上进行了全文检索的算法研究 ,提出了针对特定检索策略的计算公式。同时还对检索结果集的排序问题进行了讨论 ,并采用用户反馈信息量 ,使最后检出的结果在应用中不断得到优化  相似文献   

18.
Although always present in text, word sense ambiguity only recently became regarded as a problem to information retrieval which was potentially solvable. The growth of interest in word senses resulted from new directions taken in disambiguation research. This paper first outlines this research and surveys the resulting efforts in information retrieval. Although the majority of attempts to improve retrieval effectiveness were unsuccessful, much was learnt from the research. Most notably a notion of under what circumstance disambiguation may prove of use to retrieval.  相似文献   

19.
汉语分词技术综述   总被引:2,自引:1,他引:1  
首先介绍了汉语自动分词技术及基于词索引的中文全文检索技术,接着分别从文献自动标引、文摘自动生成、文本自动分类、文本信息过滤、自然语言检索接口和智能检索等方面详细地阐述了汉语自动分词技术在中文全文检索中的应用,并对目前汉语自动分词技术存在的局限性进行了分析,提出了发展思路,最后对汉语自动分词技术在中文全文检索中的应用前景进行了预测。  相似文献   

20.
作者根据多年的教学经验,采用“问题解决”的教学方法,设计由浅到深的“问题串”,引导学生掌握《中国期刊全文数据库》的检索方法,并能根据课题的不同需要,结合《中国期刊全文数据库》的特点,制定良好的检索策略,掌握《中国期刊全文数据库》的检索技巧。  相似文献   

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