共查询到20条相似文献，搜索用时 22 毫秒
1.
Multimodal biomedical image indexing and retrieval using descriptive text and global feature mapping
Matthew S. Simpson Dina Demner-Fushman Sameer K. Antani George R. Thoma 《Information Retrieval》2014,17(3):229-264
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
2.
The application of relevance feedback techniques has been shown to improve retrieval performance for a number of information retrieval tasks. This paper explores incremental relevance feedback for ad hoc Japanese text retrieval; examining, separately and in combination, the utility of term reweighting and query expansion using a probabilistic retrieval model. Retrieval performance is evaluated in terms of standard precision-recall measures, and also using number-to-view graphs. Experimental results, on the standard BMIR-J2 Japanese language retrieval collection, show that both term reweighting and query expansion improve retrieval performance. This is reflected in improvements in both precision and recall, but also a reduction in the average number of documents which must be viewed to find a selected number of relevant items. In particular, using a simple simulation of user searching, incremental application of relevance information is shown to lead to progressively improved retrieval performance and an overall reduction in the number of documents that a user must view to find relevant ones. 相似文献
3.
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
4.
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
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6.
特征词抽取和相关性融合的伪相关反馈查询扩展 总被引：2，自引：0，他引：2
针对现有信息检索系统中存在的词不匹配问题,提出一种基于特征词抽取和相关性融合的伪相关反馈查询扩展算法以及新的扩展词权重计算方法。该算法从前列n篇初检局部文档中抽取与原查询相关的特征词,根据特征词在初检文档集中出现的频度以及与原查询的相关度,将特征词确定为最终的扩展词实现查询扩展。实验结果表明,该方法有效,并能提高和改善信息检索性能。 相似文献
7.
The application of word sense disambiguation (WSD) techniques to information retrieval (IR) has yet to provide convincing retrieval results. Major obstacles to effective WSD in IR include coverage and granularity problems of word sense inventories, sparsity of document context, and limited information provided by short queries. In this paper, to alleviate these issues, we propose the construction of latent context models for terms using latent Dirichlet allocation. We propose building one latent context per word, using a well principled representation of local context based on word features. In particular, context words are weighted using a decaying function according to their distance to the target word, which is learnt from data in an unsupervised manner. The resulting latent features are used to discriminate word contexts, so as to constrict query’s semantic scope. Consistent and substantial improvements, including on difficult queries, are observed on TREC test collections, and the techniques combines well with blind relevance feedback. Compared to traditional topic modeling, WSD and positional indexing techniques, the proposed retrieval model is more effective and scales well on large-scale collections. 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
10.
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
11.
Information Retrieval from Documents: A Survey 总被引：4，自引：0，他引：4
Given the phenomenal growth in the variety and quantity of data available to users through electronic media, there is a great demand for efficient and effective ways to organize and search through all this information. Besides speech, our principal means of communication is through visual media, and in particular, through documents. In this paper, we provide an update on Doermann's comprehensive survey (1998) of research results in the broad area of document-based information retrieval. The scope of this survey is also somewhat broader, and there is a greater emphasis on relating document image analysis methods to conventional IR methods.Documents are available in a wide variety of formats. Technical papers are often available as ASCII files of clean, correct, text. Other documents may only be available as hardcopies. These documents have to be scanned and stored as images so that they may be processed by a computer. The textual content of these documents may also be extracted and recognized using OCR methods. Our survey covers the broad spectrum of methods that are required to handle different formats like text and images. The core of the paper focuses on methods that manipulate document images directly, and perform various information processing tasks such as retrieval, categorization, and summarization, without attempting to completely recognize the textual content of the document. We start, however, with a brief overview of traditional IR techniques that operate on clean text. We also discuss research dealing with text that is generated by running OCR on document images. Finally, we also briefly touch on the related problem of content-based image retrieval. 相似文献
12.
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
13.
采用提问式融合与相关反馈方法的结合,对现有的TopN文献选取策略研究和分析,提出利用相关度系数选取数量可变的TopN文献进行扩展查询的提问融合算法,即基于可变N反馈的提问融合算法。通过实验对固定N和可变N算法进行对比分析,结果显示可变N反馈在一定程度上可以改进检索性能。 相似文献
14.
Relevance feedback is an effective technique for improving search accuracy in interactive information retrieval. In this paper, we study an interesting optimization problem in interactive feedback that aims at optimizing the tradeoff between presenting search results with the highest immediate utility to a user (but not necessarily most useful for collecting feedback information) and presenting search results with the best potential for collecting useful feedback information (but not necessarily the most useful documents from a user’s perspective). Optimizing such an exploration–exploitation tradeoff is key to the optimization of the overall utility of relevance feedback to a user in the entire session of relevance feedback. We formally frame this tradeoff as a problem of optimizing the diversification of search results since relevance judgments on more diversified results have been shown to be more useful for relevance feedback. We propose a machine learning approach to adaptively optimizing the diversification of search results for each query so as to optimize the overall utility in an entire session. Experiment results on three representative retrieval test collections show that the proposed learning approach can effectively optimize the exploration–exploitation tradeoff and outperforms the traditional relevance feedback approach which only does exploitation without exploration. 相似文献
15.
A known-item search is a particular information retrieval task in which the system is asked to find a single target document in a large document set. The TREC-5 confusion track used a set of 49 known-item tasks to study the impact of data corruption on retrieval system performance. Two corrupted versions of a 55,600 document corpus whose true content was known were created by applying OCR techniques to page images. The first version of the corpus used the page images as scanned, resulting in an estimated character error rate of approximately 5%. The second version used page images that had been down-sampled, resulting in an estimated character error rate of approximately 20%. The true text and each of the corrupted versions were then searched using the same set of 49 questions. In general, retrieval methods that attempted a probabilistic reconstruction of the original clean text fared better than methods that simply accepted corrupted versions of the query text. 相似文献
16.
提出一种结合全局分析和局部分析从单篇文档中抽取查询信息的算法。利用全局分析提取用户的查询兴趣，通过局部分析消除查询词的歧义性。实验结果表明，该方法能较全面反映用户查询的上下文信息，提高查询的相关度。 相似文献
17.
信息检索系统中的用户相关反馈机制 总被引：3，自引：0，他引：3
陈定权 《现代图书情报技术》2002,18(4):33-35
从理论上论述了向量空间模型和概率模型是如何通过相关反馈机制来提高检索性能，还讨论了在不同模型中，相关反馈是如何实现查询式扩展和检索词权值调整的。 相似文献
18.
Information Retrieval with a Hybrid Automatic Query Expansion and Data Fusion Procedure 总被引：1，自引：0，他引：1
We propose a hybrid information retrieval (IR) procedure that builds on two well-known IR approaches: data fusion and query expansion via relevance feedback. This IR procedure is designed to exploit the strengths of data fusion and relevance feedback and to avoid some weaknesses of these approaches. We show that our IR procedure is built on postulates that can be justified analytically and empirically. Additionally, we offer an empirical investigation of the procedure, showing that it is superior to relevance feedback on some dimensions and comparable on other dimensions. The empirical investigation also verifies the conditions under which the use of our IR procedure could be beneficial. 相似文献
19.
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.
相似文献
| Chengxiang ZhaiEmail: |
20.
Luca Soldaini Andrew Yates Elad Yom-Tov Ophir Frieder Nazli Goharian 《Information Retrieval》2016,19(1-2):149-173
The majority of Internet users search for medical information online; however, many do not have an adequate medical vocabulary. Users might have difficulties finding the most authoritative and useful information because they are unfamiliar with the appropriate medical expressions describing their condition; consequently, they are unable to adequately satisfy their information need. We investigate the utility of bridging the gap between layperson and expert vocabularies; our approach adds the most appropriate expert expression to queries submitted by users, a task we call query clarification. We evaluated the impact of query clarification. Using three different synonym mappings and conducting two task-based retrieval studies, users were asked to answer medically-related questions using interleaved results from a major search engine. Our results show that the proposed system was preferred by users and helped them answer medical concerns correctly more often, with up to a 7 % increase in correct answers over an unmodified query. Finally, we introduce a supervised classifier to select the most appropriate synonym mapping for each query, which further increased the fraction of correct answers (12 %). 相似文献