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当含有敏感信息的XML文档在网络上传输或交换时,需要用户执行受限查询,如何提高查询效率,同时又保证敏感信息的安全一直是安全领域的研究热点。以带访问权限的实例信息树为主体,优先抽取主干信息策略,再反向作用于实例信息树存储特殊节点的压缩方法,为安全且高效的XML关键字查询奠定了基础,而且采用扩展的Dewey编码方式,为安全查询提供了方便。实验结果表明,这种基于压缩策略的安全查询方式减轻了存储负担,提高了查询效率。 相似文献
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为了解决基于LCA(Lower Common Ancestor)的XML关键字查询丢失语义的问题,提出了一种基于“自然语言生成技术(Natural Language Generation,NLG)”的XML关键字查询技术,将NLG的内容规划应用到XML文档,产生针对用户查询的消息语句集,通过对消息语句集的筛选既可以实现基于语义的XML关键字查询,又可以极大地提高查询效率。 相似文献
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Feng Shao Lin Guo Chavdar Botev Anand Bhaskar Muthiah Chettiar Fan Yang Jayavel Shanmugasundaram 《The VLDB Journal The International Journal on Very Large Data Bases》2009,18(2):543-570
Emerging applications such as personalized portals, enterprise search, and web integration systems often require keyword search
over semi-structured views. However, traditional information retrieval techniques are likely to be expensive in this context
because they rely on the assumption that the set of documents being searched is materialized. In this paper, we present a
system architecture and algorithm that can efficiently evaluate keyword search queries over virtual (unmaterialized) XML views. An interesting aspect of our approach is that it exploits indices present on the base data and
thereby avoids materializing large parts of the view that are not relevant to the query results. Another feature of the algorithm
is that by solely using indices, we can still score the results of queries over the virtual view, and the resulting scores
are the same as if the view was materialized. Our performance evaluation using the INEX data set in the Quark (Bhaskar et al. in Quark: an efficient
XQuery full-text implementation. In: SIGMOD, 2006) open-source XML database system indicates that the proposed approach is
scalable and efficient. 相似文献
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基于有效最低公共祖先的XML关键字查询算法 总被引:1,自引:0,他引:1
针对XML文档关键字搜索问题,从元素标签内容等价和元素结构相似性等价两个方面考虑无效的查询结果。介绍了有效最低公共祖先(FLCA)的概念,在此基础上提出紧致的有效最低公共祖先(CFLCA)的概念。根据定义的查询结果集,提出基于等价模式值索引的查询算法(BEPVA)。最后与CVLCA和SLCA进行了比较,结果表明提出的方法在查询质量和查询效率上有较大的提高。 相似文献
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As a large number of corpuses are represented, stored and published in XML format, how to find useful information from XML databases has become an increasingly important issue. Keyword search enables web users to easily access XML data without the need to learn a structured query language or to study complex data schemas. Most existing indexing strategies for XML keyword search are based upon Dewey encoding. In this paper, we proposed a new encoding method called Level Order and Father (LAF) for XML documents. With LAF encoding, we devised a new index structure, called two‐layer LAF inverted index, which can greatly decrease the space complexity compared with Dewey encoding‐based inverted index. Furthermore, with two‐layer LAF inverted index, we proposed a new keyword query algorithm called Algorithm based on Binary Search (ABS) that can quickly find all Smallest Lowest Common Ancestor. We experimentally evaluate two‐layer LAF inverted index and ABS algorithm on four real XML data sets selected from Wikipedia. The experimental results prove the advantages of our index method and querying algorithm. The space consumed by two‐layer LAF index is less than half of that consumed by Dewey inverted index. Moreover, ABS is about one to two orders of magnitude faster than the classic Stack algorithm. Concurrency and Computation: Practice and Experience, 2012.© 2012 Wiley Periodicals, Inc. 相似文献
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In this paper, we study the problem of keyword proximity search in XML documents. We take the disjunctive semantics among the keywords into consideration and find top-k relevant compact connected trees (CCTrees) as the answers of keyword proximity queries. We first introduce the notions of compact lowest common ancestor (CLCA) and maximal CLCA (MCLCA), and then propose compact connected trees and maximal CCTrees (MCCTrees) to efficiently and effectively answer keyword proximity queries. We give the theoretical upper bounds of the numbers of CLCAs, MCLCAs, CCTrees and MCCTrees, respectively. We devise an efficient algorithm to generate all MCCTrees, and propose a ranking mechanism to rank MCCTrees. Our extensive experimental study shows that our method achieves both high efficiency and effectiveness, and outperforms existing state-of-the-art approaches significantly. 相似文献
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With a significant advance in ciphertext searchability, public-key encryption with keyword search (PEKS) guarantees both security and convenience for outsourced keyword search over ciphertexts. In this paper, we establish static index (SI) and dynamic index (DI) for PEKS to make search efficient and secure in the state of the art. Suppose there are senders to generate searchable ciphertexts for keywords. The search complexity of PEKS always is for each query, even if the keyword has been searched for multiple times. It is obviously inefficient for massive searchable ciphertexts. Fortunately, SI and DI help PEKS lowering the burden respectively in two phases: if the queried keyword is the first time to be searched, apply SI to reduce the complexity from to ; otherwise, apply DI to reduce the complexity from to . Because DI is invalid for the first time search on any keyword, SI and DI are simultaneously applied with PEKS to complete our work as the secure hybrid indexed search (SHIS) scheme. Since in practice, our SHIS scheme is significantly more efficient than PEKS as demonstrated by our analysis. In the end, we show the extension of SHIS to multi-receiver applications, which is absent for pure PEKS. 相似文献