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1.
Query languages for XML such as XPath or XQuery support Boolean retrieval: a query result is a (possibly restructured) subset of XML elements or entire documents that satisfy the search conditions of the query. This search paradigm works for highly schematic XML data collections such as electronic catalogs. However, for searching information in open environments such as the Web or intranets of large corporations, ranked retrieval is more appropriate: a query result is a ranked list of XML elements in descending order of (estimated) relevance. Web search engines, which are based on the ranked retrieval paradigm, do, however, not consider the additional information and rich annotations provided by the structure of XML documents and their element names.This article presents the XXL search engine that supports relevance ranking on XML data. XXL is particularly geared for path queries with wildcards that can span multiple XML collections and contain both exact-match as well as semantic-similarity search conditions. In addition, ontological information and suitable index structures are used to improve the search efficiency and effectiveness. XXL is fully implemented as a suite of Java classes and servlets. Experiments in the context of the INEX benchmark demonstrate the efficiency of the XXL search engine and underline its effectiveness for ranked retrieval. 相似文献
2.
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
3.
XML retrieval is a departure from standard document retrieval in which each individual XML element, ranging from italicized words or phrases to full blown articles, is a retrievable unit. The distribution of XML element lengths is unlike what we usually observe in standard document collections, prompting us to revisit the issue of document length normalization. We perform a comparative analysis of arbitrary elements versus relevant elements, and show the importance of element length as a parameter for XML retrieval. Within the language modeling framework, we investigate a range of techniques that deal with length either directly or indirectly. We observe a length-bias introduced by the amount of smoothing, and show the importance of extreme length bias for XML retrieval. We also show that simply removing shorter elements from the index (by introducing a cut-off value) does not create an appropriate element length normalization. Even after restricting the minimal size of XML elements occurring in the index, the importance of an extreme explicit length bias remains. 相似文献
4.
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
5.
一种基于Native XML的全文检索引擎 总被引：5，自引：0，他引：5
随着XML的日益流行 ,基于XML的全文检索应用需求也迅速扩大。在这些应用中 ,native XML数据库是发展方向。虽然商业化的native XML数据库已经出现 ,但其全文检索的性能还不尽人意。本文提出一种方法 :在传统的倒排索引的框架下 ,对XML的标记建立索引 ,使得一个全文数据库能够以Native的方式存储、索引、检索和输出XML文档 ,成为一个真正意义上的native XML全文数据库 ,既有传统全文数据库的优越性能 ,又能满足基于na tive XML的应用需求 相似文献
6.
与传统信息检索不同的是XML要实现元素级的检索,其核心是元素级检索模型的构建。而XML文档内上下文元素的相关性、元素之间信息的重复性以及元素大小的不一性等则是构建模型时面临的核心问题。解决办法是:构建基于BM25元素级XML检索模型,构建基于上下文的元素级XML检索模型BM25E,过滤重复元素,进行可检索元素的选择和太小元素的处理。表1。图1。参考文献19。 相似文献
7.
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
8.
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.
相似文献
| Gabriella KazaiEmail: |
9.
图像对象特征值的抽取、存储、转换、显现的实现有多种方法，SIMIIRS系统主要采用了数据库方法和XML方法。文章主要讨论了图像资源的XML描述方法、建立图像信息的XML索引文档，检索XML文档以实现图像信息查询与提供。 相似文献
10.
Over the last three decades, research in Information Retrieval (IR) shows performance improvement when many sources of evidence
are combined to produce a ranking of documents. Most current approaches assess document relevance by computing a single score
which aggregates values of some attributes or criteria. They use analytic aggregation operators which either lead to a loss
of valuable information, e.g., the min or lexicographic operators, or allow very bad scores on some criteria to be compensated
with good ones, e.g., the weighted sum operator. Moreover, all these approaches do not handle imprecision of criterion scores.
In this paper, we propose a multiple criteria framework using a new aggregation mechanism based on decision rules identifying
positive and negative reasons for judging whether a document should get a better ranking than another. The resulting procedure
also handles imprecision in criteria design. Experimental results are reported showing that the suggested method performs
better than standard aggregation operators. 相似文献