Linear feature-based models for information retrieval     

Donald Metzler  W. Bruce Croft 《Information Retrieval》2007,10(3):257-274

There have been a number of linear, feature-based models proposed by the information retrieval community recently. Although each model is presented differently, they all share a common underlying framework. In this paper, we explore and discuss the theoretical issues of this framework, including a novel look at the parameter space. We then detail supervised training algorithms that directly maximize the evaluation metric under consideration, such as mean average precision. We present results that show training models in this way can lead to significantly better test set performance compared to other training methods that do not directly maximize the metric. Finally, we show that linear feature-based models can consistently and significantly outperform current state of the art retrieval models with the correct choice of features.

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A goodness of fit test approach in information retrieval     

Kostas Fragos  Yannis Maistros 《Information Retrieval》2006,9(3):331-342

In many probabilistic modeling approaches to Information Retrieval we are interested in estimating how well a document model “fits” the user’s information need (query model). On the other hand in statistics, goodness of fit tests are well established techniques for assessing the assumptions about the underlying distribution of a data set. Supposing that the query terms are randomly distributed in the various documents of the collection, we actually want to know whether the occurrences of the query terms are more frequently distributed by chance in a particular document. This can be quantified by the so-called goodness of fit tests. In this paper, we present a new document ranking technique based on Chi-square goodness of fit tests. Given the null hypothesis that there is no association between the query terms q and the document d irrespective of any chance occurrences, we perform a Chi-square goodness of fit test for assessing this hypothesis and calculate the corresponding Chi-square values. Our retrieval formula is based on ranking the documents in the collection according to these calculated Chi-square values. The method was evaluated over the entire test collection of TREC data, on disks 4 and 5, using the topics of TREC-7 and TREC-8 (50 topics each) conferences. It performs well, outperforming steadily the classical OKAPI term frequency weighting formula but below that of KL-Divergence from language modeling approach. Despite this, we believe that the technique is an important non-parametric way of thinking of retrieval, offering the possibility to try simple alternative retrieval formulas within goodness-of-fit statistical tests’ framework, modeling the data in various ways estimating or assigning any arbitrary theoretical distribution in terms.  相似文献   

Ei Compendex Web数据库检索方法及检索效果的研究   总被引：7，自引：0，他引：7  

刘亚茹 《情报科学》2000,18(1):65-67

本文主要介绍Ei Compendex Web数据库的检索方法,并通过实例将其与Ei Compendex光盘数据库的检索效果进行比较．从而找出二者在检索过程中的优缺点。  相似文献   

基于Web的信息服务   总被引：9，自引：0，他引：9  

丁蔚  倪波 《情报科学》2000,18(7):646-650

本文通过Ｉｎｔｅｒｎｅｔ网上信息服务的必要性以及Ｗｅｂ技术的阐述,介绍了国际互联网上基于Ｗｅｂ信息服务的两大技术支柱,即查询引和Ｗｅｂ Ｓｅｒｖｅｒ与数据库的连接技术,展示了Ｗｅｂ信息服务的巨大优越性,指出这一技术将成为今后网上信息服务的基本手段得到蓬勃发展。  相似文献   

文献检索课开设30年的回顾     

葛敬民 《大学图书馆学报》2014,(4):98-102

山东理工大学图书馆开设文献检索课30年,实现了前辈们将文献检索课建成高校三大公共课程之一的愿望。此文重点介绍该校近5年文献检索课的改革举措,包括课程普及和提高两个方面。普及是实现全校范围的授课,提高是达到教育部的共享课标准。作者认为文献检索课的成功在于图书馆教育科研职能被广泛认可,这是图书馆由被动服务向主动服务的重要转折,实践证明此举能够显著提升图书馆在校内的地位。  相似文献   

PubMed与Embase.com检索效果对比分析     

孙艳 《中华医学图书馆杂志》2014,(9):75-77

目的：对比分析Embase.com和PubMed的检索结果,为科研人员推荐最适合的检索工具和提高检索效率。方法：选取8个不同学科的检索词,在PubMed和Embase.com中分别采用主题词检索和带有自动转换功能的基本检索两种途径检索。结果：8个检索词在检索中出现6种不同情况。结论：通过主题词检索,总体来说Embase.com检全率要高于PubMed;带有自动转换功能的基本检索,两个数据库都会出现错误转换,但从转换的原理上看,PubMed的查准率更高。  相似文献   

基于语义WEB服务的WSMO信息检索应用模型及支撑体系研究     

李兵 《黑龙江科技信息》2014,(2):138-139

搭建一个良好的信息检索平台,通过互联网提供对分布式存储信息的知识化组织、智能化访问和服务。提出WSMO信息检索应用的模型,借鉴现有的信息资源检索组织模式、借助本体网络服务模型WSMO,创造性地与精准检索技术相结合,有效地进行信息整序,使用户获取信息不受空间限制,都可以在任何时间、任何地点方便快捷地享用世界上任何一个开放的数字化信息资源。  相似文献   

Lexical and Syntactic knowledge for Information Retrieval     

Antonio Ferrández 《Information processing & management》2011

Traditional Information Retrieval (IR) models assume that the index terms of queries and documents are statistically independent of each other, which is intuitively wrong. This paper proposes the incorporation of the lexical and syntactic knowledge generated by a POS-tagger and a syntactic Chunker into traditional IR similarity measures for including this dependency information between terms. Our proposal is based on theories of discourse structure by means of the segmentation of documents and queries into sentences and entities. Therefore, we measure dependencies between entities instead of between terms. Moreover, we handle discourse references for each entity. It has been evaluated on Spanish and English corpora as well as on Question Answering tasks obtaining significant increases.  相似文献   

Linguistic kernels for answer re-ranking in question answering systems     

Alessandro Moschitti  Silvia Quarteroni 《Information processing & management》2011

Answer selection is the most complex phase of a question answering (QA) system. To solve this task, typical approaches use unsupervised methods such as computing the similarity between query and answer, optionally exploiting advanced syntactic, semantic or logic representations.  相似文献   

基于信息检索及发展趋势的研究     

王晓波 《河南图书馆学刊》2011,31(1):7-9

论述了信息检索的概念、类型、意义、主要方式、原理以及网络信息检索的发展趋势。  相似文献