共查询到17条相似文献，搜索用时 98 毫秒
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INEX是当今信息检索领域最重要的国际评测会议之一.文章通过对INEX 2004年至2010年检索评价项目数量、项目类型、项目任务、测试集的变化,以及对IST 2007年至2010年所关注项目,参与INEX评测的机构的分析,了解XML检索领域的发展方向与趋势,以促进我国科研团队在XML语言检索评价领域更加深入的探索和发展. 相似文献
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INEX与TREC是检索领域的两大检索系统评价平台,在检索技术发展迅速的今天依然保持强大生命力,在当今检索技术评价领域起着十分重要的作用。本篇文章通过对INEX与TREC的研究目标以及平台的构成要素包括三个方面:测试集、检索问题的构造、相关性评估的比较,找出INEX相对于TREC评测平台的创新及不同点,以便更加深入和全面地了解INEX的评测方法。 相似文献
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基于域加权词频法的XML文档级检索实现与评价 总被引：1，自引：0，他引：1
利用BM25F模型,通过实验,在INEX 04数据集的基础上,实现了对多个域(元素)词频进行加权的XML文档级检索。XML文档结构的确蕴含了一定的语义信息。利用这些语义信息,可以提高检索性能。表2。图1。参考文献16。 相似文献
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随着社交网络的兴起和发展,互联网上出现了大量与商品有关的社会信息。如何利用这些社会信息结合商品元数据进行检索和推荐是信息检索领域中一个热门的研究问题。本文以社会图书检索为例,提出了一种通用的信息检索方法来解决这一问题。首先,通过分析原始图书数据集和图书的用户标签、用户评分和流行度等社会信息,从图书中提取不同的社会特征构建特征矩阵;然后分别计算图书在各种社会特征上的相似度,并使用不同的策略对搜索引擎返回的排序结果进行重排序;最后使用学习排序的方法进行重排结果融合,得到最终的图书检索结果。在实验中,使用该检索方法在INEX Social Book Search 2015和2016数据集上分别进行了训练和测试。结果表明,相比现有的技术,该检索方法能够有效提升图书检索的效果。 相似文献
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本文采用比较的研究方法,对中西媒体会议新闻报道进行了对比分析。研究发现：西方媒体会议新闻报道所采取的新闻本位的报道观念、受众视角较之我国媒体对应的会议本位、会议主办者视角和严肃性．更符合会议新闻报道规律,值得学习与借鉴。 相似文献
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鹿瑜忠 《中国广播电视学刊》1992,(2)
中国广播电视学会各专业研究委员会负责人会议于3月20日在京召开。会议就研究委员会如何贯彻学会第二届理事会议精神,落实《关于专业研究委员会暂行管理办法》进行了讨论。会议由学会秘书长孙以森主持,常务副会长郝平南、何光,常务理事李振水讲了 相似文献
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北京、上海、广州都提出要建立区域的“会议中心”；“会议经济”也成为经济研究人员的案头之题，而报纸尤其是机关报，却在为“会议新闻”头痛。 笔者参加的各种会议多了，对“会议新闻”的抱怨听多了，也着手作了些研究，才发现这原来不是一个小题目。本文陈述了近期的研究结果。 一、理一理“会议”的概念 “会议新闻多了，所以报纸一版不好看”； “要改变现在的状况，必须改变会议新闻的写法，作到‘跳出会议写会议’”； …… 这样论断与评价我们听得多了，它们传达着同样的信息：对新闻来说，会议不是什么… 相似文献
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随着我国科学技术日新月异的发展,各学术团体和研究机构为了进行有效的学术交流,都要举行各种类型的学术会议(以下简称会议)。会议文献是会议的产物,具有很高的情报价值。在发达国家,会议文献的开发利用已具有很高的水平。相比之下,我国的会议文献开发利用工作还很落后。因此,有必要对怎样充分开发、有效利用我国会议文献这一问题进行研究。 相似文献
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This special issue contains articles describing XML retrieval approaches developed and evaluated during the second year of INEX, the evaluation initiative for XML retrieval. 相似文献
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TIJAH: Embracing IR Methods in XML Databases 总被引：1，自引：0，他引：1
This paper discusses our participation in INEX (the Initiative for the Evaluation of XML Retrieval) using the TIJAH XML-IR system. TIJAHs system design follows a standard layered database architecture, carefully separating the conceptual, logical and physical levels. At the conceptual level, we classify the INEX XPath-based query expressions into three different query patterns. For each pattern, we present its mapping into a query execution strategy. The logical layer exploits score region algebra (SRA) as the basis for query processing. We discuss the region operators used to select and manipulate XML document components. The logical algebra expressions are mapped into efficient relational algebra expressions over a physical representation of the XML document collection using the pre-post numbering scheme. The paper concludes with an analysis of experiments performed with the INEX test collection. 相似文献
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In this paper we evaluate the application of data fusion or meta-search methods, combining different algorithms and XML elements, to content-oriented retrieval of XML structured data. The primary approach is the combination of a probabilistic methods using Logistic regression and the Okapi BM-25 algorithm for estimation of document relevance or XML element relevance, in conjunction with Boolean approaches for some query elements. In the evaluation we use the INEX XML test collection to examine the relative performance of individual algorithms and elements and compare these to the performance of the data fusion approaches. 相似文献
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Jovan Pehcevski James A. Thom Anne-Marie Vercoustre Vladimir Naumovski 《Information Retrieval》2010,13(5):568-600
Entity ranking has recently emerged as a research field that aims at retrieving entities as answers to a query. Unlike entity
extraction where the goal is to tag names of entities in documents, entity ranking is primarily focused on returning a ranked
list of relevant entity names for the query. Many approaches to entity ranking have been proposed, and most of them were evaluated
on the INEX Wikipedia test collection. In this paper, we describe a system we developed for ranking Wikipedia entities in
answer to a query. The entity ranking approach implemented in our system utilises the known categories, the link structure
of Wikipedia, as well as the link co-occurrences with the entity examples (when provided) to retrieve relevant entities as
answers to the query. We also extend our entity ranking approach by utilising the knowledge of predicted classes of topic
difficulty. To predict the topic difficulty, we generate a classifier that uses features extracted from an INEX topic definition
to classify the topic into an experimentally pre-determined class. This knowledge is then utilised to dynamically set the
optimal values for the retrieval parameters of our entity ranking system. Our experiments demonstrate that the use of categories
and the link structure of Wikipedia can significantly improve entity ranking effectiveness, and that topic difficulty prediction
is a promising approach that could also be exploited to further improve the entity ranking performance. 相似文献
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Content-only queries in hierarchically structured documents should retrieve the most specific document nodes which are exhaustive
to the information need. For this problem, we investigate two methods of augmentation, which both yield high retrieval quality.
As retrieval effectiveness, we consider the ratio of retrieval quality and response time; thus, fast approximations to the
'correct' retrieval result may yield higher effectiveness. We present a classification scheme for algorithms addressing this
issue, and adopt known algorithms from standard document retrieval for XML retrieval. As a new strategy, we propose incremental-interruptible retrieval, which allows for instant presentation of the top ranking documents. We develop a new algorithm implementing this strategy
and evaluate the different methods with the INEX collection. 相似文献
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This paper investigates the impact of three approaches to XML retrieval: using Zettair, a full-text information retrieval system; using eXist, a native XML database; and using a hybrid system that takes full article answers from Zettair and uses eXist to extract elements from those articles. For the content-only topics, we undertake a preliminary analysis of the INEX 2003 relevance assessments in order to identify the types of highly relevant document components. Further analysis identifies two complementary sub-cases of relevance assessments (General and Specific) and two categories of topics (Broad and Narrow). We develop a novel retrieval module that for a content-only topic utilises the information from the resulting answer list of a native XML database and dynamically determines the preferable units of retrieval, which we call Coherent Retrieval Elements. The results of our experiments show that—when each of the three systems is evaluated against different retrieval scenarios (such as different cases of relevance assessments, different topic categories and different choices of evaluation metrics)—the XML retrieval systems exhibit varying behaviour and the best performance can be reached for different values of the retrieval parameters. In the case of INEX 2003 relevance assessments for the content-only topics, our newly developed hybrid XML retrieval system is substantially more effective than either Zettair or eXist, and yields a robust and a very effective XML retrieval. 相似文献
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Most recent document standards like XML rely on structured representations. On the other hand, current information retrieval systems have been developed for flat document representations and cannot be easily extended to cope with more complex document types. The design of such systems is still an open problem. We present a new model for structured document retrieval which allows computing scores of document parts. This model is based on Bayesian networks whose conditional probabilities are learnt from a labelled collection of structured documents—which is composed of documents, queries and their associated assessments. Training these models is a complex machine learning task and is not standard. This is the focus of the paper: we propose here to train the structured Bayesian Network model using a cross-entropy training criterion. Results are presented on the INEX corpus of XML documents. 相似文献