A study of untrained models for multimodal information retrieval

Operational multimodal information retrieval systems have to deal with increasingly complex document collections and queries that are composed of a large set of textual and non-textual modalities such as ratings, prices, timestamps, geographical coordinates, etc. The resulting combinatorial explosion of modality combinations makes it intractable to treat each modality individually and to obtain suitable training data. As a consequence, instead of finding and training new models for each individual modality or combination of modalities, it is crucial to establish unified models, and fuse their outputs in a robust way. Since the most popular weighting schemes for textual retrieval have in the past generalized well to many retrieval tasks, we demonstrate how they can be adapted to be used with non-textual modalities, which is a first step towards finding such a unified model. We demonstrate that the popular weighting scheme BM25 is suitable to be used for multimodal IR systems and analyze the underlying assumptions of the BM25 formula with respect to merging modalities under the so-called raw-score merging hypothesis, which requires no training. We establish a multimodal baseline for two multimodal test collections, show how modalities differ with respect to their contribution to relevance and the difficulty of treating modalities with overlapping information. Our experiments demonstrate that our multimodal baseline with no training achieves a significantly higher retrieval effectiveness than using just the textual modality for the social book search 2016 collection and lies in the range of a trained multimodal approach using the optimal linear combination of the modality scores.     

信息检索中"相关性"的探究

本文从“相关性”的动态、多维的内涵出发,探讨了“相关性”的影响因素,即信息源、检索系统、用户、时间与环境,最后得出了“相关性”对建立信息检索系统的一些启示。     

On information retrieval metrics designed for evaluation with incomplete relevance assessments

Modern information retrieval (IR) test collections have grown in size, but the available manpower for relevance assessments has more or less remained constant. Hence, how to reliably evaluate and compare IR systems using incomplete relevance data, where many documents exist that were never examined by the relevance assessors, is receiving a lot of attention. This article compares the robustness of IR metrics to incomplete relevance assessments, using four different sets of graded-relevance test collections with submitted runs—the TREC 2003 and 2004 robust track data and the NTCIR-6 Japanese and Chinese IR data from the crosslingual task. Following previous work, we artificially reduce the original relevance data to simulate IR evaluation environments with extremely incomplete relevance data. We then investigate the effect of this reduction on discriminative power, which we define as the proportion of system pairs with a statistically significant difference for a given probability of Type I Error, and on Kendall’s rank correlation, which reflects the overall resemblance of two system rankings according to two different metrics or two different relevance data sets. According to these experiments, Q′, nDCG′ and AP′ proposed by Sakai are superior to bpref proposed by Buckley and Voorhees and to Rank-Biased Precision proposed by Moffat and Zobel. We also point out some weaknesses of bpref and Rank-Biased Precision by examining their formal definitions.

Extended structural relevance framework: a framework for evaluating structured document retrieval

A structured document retrieval (SDR) system aims to minimize the effort users spend to locate relevant information by retrieving parts of documents. To evaluate the range of SDR tasks, from element to passage to tree retrieval, numerous task-specific measures have been proposed. This has resulted in SDR evaluation measures that cannot easily be compared with respect to each other and across tasks. In previous work, we defined the SDR task of tree retrieval where passage and element are special cases. In this paper, we look in greater detail into tree retrieval to identify the main components of SDR evaluation: relevance, navigation, and redundancy. Our goal is to evaluate SDR within a single probabilistic framework based on these components. This framework, called Extended Structural Relevance (ESR), calculates user expected gain in relevant information depending on whether it is seen via hits (relevant results retrieved), unseen via misses (relevant results not retrieved), or possibly seen via near-misses (relevant results accessed via navigation). We use these expectations as parameters to formulate evaluation measures for tree retrieval. We then demonstrate how existing task-specific measures, if viewed as tree retrieval, can be formulated, computed and compared using our framework. Finally, we experimentally validate ESR across a range of SDR tasks.     

定题或立项检索的英文医学检索工具选择

对比分析了PubMed,BIOSISPreviews,EMBASE．corn3个数据库的收录情况、检索结果、关注度,为医学科研定题或立项检索时合理选择英文医学检索工具提供依据,提高外文文献的查全率。     

Low-cost evaluation techniques for information retrieval systems: A review

For a system-based information retrieval evaluation, test collection model still remains as a costly task. Producing relevance judgments is an expensive, time consuming task which has to be performed by human assessors. It is not viable to assess the relevancy of every single document in a corpus against each topic for a large collection. In an experimental-based environment, partial judgment on the basis of a pooling method is created to substitute a complete assessment of documents for relevancy. Due to the increasing number of documents, topics, and retrieval systems, the need to perform low-cost evaluations while obtaining reliable results is essential. Researchers are seeking techniques to reduce the costs of experimental IR evaluation process by the means of reducing the number of relevance judgments to be performed or even eliminating them while still obtaining reliable results. In this paper, various state-of-the-art approaches in performing low-cost retrieval evaluation are discussed under each of the following categories; selecting the best sets of documents to be judged; calculating evaluation measures, both, robust to incomplete judgments; statistical inference of evaluation metrics; inference of judgments on relevance, query selection; techniques to test the reliability of the evaluation and reusability of the constructed collections; and other alternative methods to pooling. This paper is intended to link the reader to the corpus of ‘must read’ papers in the area of low-cost evaluation of IR systems.     

Evaluating the effectiveness of content-oriented XML retrieval methods

Content-oriented XML retrieval approaches aim at a more focused retrieval strategy: Instead of retrieving whole documents, document components that are exhaustive to the information need while at the same time being as specific as possible should be retrieved. In this article, we show that the evaluation methods developed for standard retrieval must be modified in order to deal with the structure of XML documents. More precisely, the size and overlap of document components must be taken into account. For this purpose, we propose a new effectiveness metric based on the definition of a concept space defined upon the notions of exhaustiveness and specificity of a search result. We compare the results of this new metric by the results obtained with the official metric used in INEX, the evaluation initiative for content-oriented XML retrieval.

医学信息检索对医学文稿编辑加工的作用

介绍医学信息检索相关数据库,探讨医学信息检索在参考文献等编辑加工中的作用.认为医学编辑应掌握关键词、医学信息检索技能,熟悉常用医学数据库的检索,利用医学信息检索提高工作效率及编校质量.     

医学文献检索在医学期刊编辑中的应用

介绍医学文献检索在选题、初审、复审、退修、编辑加工、校对及编制主题词索引等医学期刊编辑各个环节中的应用及价值,认为医学编辑应掌握良好的医学文献检索技能,时时借助文献检索控制编校质量.     

医学信息检索在线考试系统

介绍了首都医科大学的在线考试系统,比较分析了学生的考试成绩,指出了在线考试系统的优点及需改进的问题。     

基于综合特征的图像检索技术的研究

随着计算机网络和多媒体信息的迅猛发展，基于内容的图像检索技术成为研究热点。本文通过介绍了基于颜色、形状、纹理和空间特征的图像检索，阐述了利用单一特征检索的不足，提出和分析了多种综合特征的图像检索技术。     

留学生医学文献检索双语教学探索

从多角度分析了留学生医学文检课双语教学的优势及教学模式,提出了留学生医学文检课应从全英文教学模式向阶梯式双语教学模式转变,并强调了在教学中应注意的几个问题。     

Evaluating the effectiveness of relevance feedback based on a user simulation model: effects of a user scenario on cumulated gain value

We propose a method for performing evaluation of relevance feedback based on simulating real users. The user simulation applies a model defining the user’s relevance threshold to accept individual documents as feedback in a graded relevance environment; user’s patience to browse the initial list of retrieved documents; and his/her effort in providing the feedback. We evaluate the result by using cumulated gain-based evaluation together with freezing all documents seen by the user in order to simulate the point of view of a user who is browsing the documents during the retrieval process. We demonstrate the method by performing a simulation in the laboratory setting and present the “branching” curve sets characteristic for the presented evaluation method. Both the average and topic-by-topic results indicate that if the freezing approach is adopted, giving feedback of mixed quality makes sense for various usage scenarios even though the modeled users prefer finding especially the most relevant documents.     

医学文献检索教学模式创新

从创建信息环境下合理的教学体系、教学模式、教学评价体系及师资队伍的建设4个方面对医学文献检索教学模式的创新进行初步探索。     

医学信息检索双语教材建设

总结了目前医学信息检索双语教材建设的现状,分析了医学信息检索双语教材建设的必要性和可行性,具体阐述了华北煤炭医学院、首都医科大学等国内多所高校联合编写医学信息检索双语教材的实践。     

A review of text and image retrieval approaches for broadcast news video

The effectiveness of a video retrieval system largely depends on the choice of underlying text and image retrieval components. The unique properties of video collections (e.g., multiple sources, noisy features and temporal relations) suggest we examine the performance of these retrieval methods in such a multimodal environment, and identify the relative importance of the underlying retrieval components. In this paper, we review a variety of text/image retrieval approaches as well as their individual components in the context of broadcast news video. Numerous components of text/image retrieval have been discussed in detail, including retrieval models, text sources, temporal expansion methods, query expansion methods, image features, and similarity measures. For each component, we conduct a series of retrieval experiments on TRECVID video collections to identify their advantages and disadvantages. To provide a more complete coverage of video retrieval, we briefly discuss an emerging approach called concept-based video retrieval, and review strategies for combining multiple retrieval outputs.     

循证医学与医学文献检索

对如何获取循证医学资源进行介绍,在论述循证医学和文献检索关系的同时,提出医学文献检索服务及教学应积极参与循证医学实践,从服务的内容、层次、教学的方式、对象、内容等方面进行扩展,以适应现代临床医学发展的新趋势.     

基于任职教育的医学信息检索教学实践

遵照军队任职教育的要求,武警医学院图书馆开展医学信息检索教学时依据武警系统卫生干部的特点确定教学目标,依据卫生干部的需求选定教学内容,将集中培训与个别辅导相结合,在提高干部信息素质的基础上,提高科研论文的写作能力。教学实践证明,这样既增强了卫生干部的发展后劲,又有利于在职卫生干部成为胜任“全岗位”、“全职能”的复合型军事医学人才。