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Journal articles on the topic 'XML Retrieval'

Author: Grafiati

Published: 9 March 2023

Last updated: 31 July 2025

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1

Lalmas, Mounia. "XML Retrieval." Synthesis Lectures on Information Concepts, Retrieval, and Services 1, no. 1 (2009): 1–111. http://dx.doi.org/10.2200/s00203ed1v01y200907icr007.

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Pehcevski, Jovan, James A. Thom, and Anne-Marie Vercoustre. "Hybrid XML Retrieval: Combining Information Retrieval and a Native XML Database." Information Retrieval 8, no. 4 (2005): 571–600. http://dx.doi.org/10.1007/s10791-005-0748-1.

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Liu, Peng Fei, Yan Hua Chen, Wen Jie Xie, and Qiao Yi Hu. "XML Retrieval with Results Clustering on Android." Advanced Materials Research 756-759 (September 2013): 1300–1303. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.1300.

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XML receives widely interests in data exchanging and information management on both traditional desktop computing platforms and rising mobile computing platforms. However, traditional XML retrieval does not work on mobile devices due to the mobile platforms limitations and diversities. Considering that XML retrieval on mobile devices will become increasingly popular, in this article, we have paid attention to the design and implementation of XML retrieval and results clustering model on the android platform, building on jaxen and dom4j, the XML parser and retrieval engine; furthermore, the K-m

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Carmel, David, Yoelle Maarek, and Aya Soffer. "XML and information retrieval." ACM SIGIR Forum 34, no. 1 (2000): 31–36. http://dx.doi.org/10.1145/373593.373624.

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Carmel, David, Yoelle Maarek, and Aya Soffer. "XML and information retrieval." ACM SIGMOD Record 30, no. 1 (2001): 62–65. http://dx.doi.org/10.1145/373626.373705.

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Yu, Hong, Xiao Lei Huang, Zhi Ling Wei, and Chen Xia Yang. "Study on XML Retrieval Results Classification." Applied Mechanics and Materials 263-266 (December 2012): 1773–77. http://dx.doi.org/10.4028/www.scientific.net/amm.263-266.1773.

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Mining (classify or clustering) retrieval results to serve relevance feedback mechanism of search engine is an important solution to improve effectiveness of retrieval. Unlike plain text documents, since the XML documents are semi-structured data, for XML retrieval results classification, consider exploiting structure features of XML documents, such as tag paths and edges etc. We propose to use Support Vector Machine (SVM) classifier to classify XML retrieval results exploiting both their content and structure features. We implemented the classification method on XML retrieval results based on

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Xia, Yao Wen, and Ji Li Xie. "The Research of XML Keyword Retrieval Algorithms Based on MapReduce." Applied Mechanics and Materials 556-562 (May 2014): 3347–49. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.3347.

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In this paper, from the perspective of XML data management, first in the HDFS store large amount of data and XML data based on XML data query rewrite the traditional framework of MapReduce process, the design of large amount of data XML data set keywords retrieval algorithm, contain XML data classification and coding, index and search a four parts, solve the large amount of data of the XML document keywords retrieval problem. Then the design and implementation based on MapReduce of large amount of data XML keyword query system.

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Beamer, Ashley, and Mark Gillick. "ScotlandsPlaces XML: bespoke XML or XML mapping?" Program 44, no. 1 (2010): 13–27. http://dx.doi.org/10.1108/00330331011019654.

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PurposeThe purpose of this paper is to investigate web services (in the form of parameterised URLs), specifically in the context of the ScotlandsPlaces project. This involves cross‐domain querying, data retrieval and display via the development of a bespoke XML standard rather than existing XML formats and mapping between them.Design/methodology/approachIn looking at the different heritage domain datasets as well as the metadata formats used for storage and data exchange, the ScotlandsPlaces XML format is revealed as the most appropriate for this type of project. The nature of the project itse

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MA, MATTHEW Y., JINHONG K. GUO, and PATRICK S. P. WANG. "FROM PIXELS TO TRUE XML STRUCTURES IN DIGITAL DOCUMENT IMAGES." International Journal of Pattern Recognition and Artificial Intelligence 18, no. 06 (2004): 1057–69. http://dx.doi.org/10.1142/s0218001404003575.

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XML has been widely used as metadata for image retrieval. As a standard, it makes it easier to index and retrieve information across different platforms. However, how to automatically convert an image into XML format remains a challenge. In this paper, a system for generating structured document in XML from digitally captured document images is presented. The system is aimed at providing an easy to use tool for average users without requiring depth of knowledge in the document processing areas. Further, a XML/XSL generator is developed to accurately represent a document in a XML structure, yet

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Chen, Jiang Xin, and Li Yong Wan. "A Novel XML Document Retrieval Method." Advanced Materials Research 981 (July 2014): 167–70. http://dx.doi.org/10.4028/www.scientific.net/amr.981.167.

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XML is a new standard for data representation and exchange, which has been widely used on the Internet. XML retrieval has caused more and more researchers concern. How to improve the retrieval efficiency has become an important study field, this paper proposes the retrieval method based on keyword weight and structure extension, which can get the middle retrieval results in accordance with calculating the keyword weight, and further to retrieval by implementing structural extension of middle retrieval results, then can get the final query results. The experiment results show that the retrieval

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Schweiger, R., J. Dudeck, and S. Hoelzer. "Representation of Practice Guidelines with XML – Modeling with XML Schema." Methods of Information in Medicine 41, no. 04 (2002): 305–12. http://dx.doi.org/10.1055/s-0038-1634387.

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Summary Objectives: Data and information in medicine are mainly represented in slightly structured or even unstructured, narrative text documents. It is nearly impossible to detect and handle relationships between data elements within narrative documents or to retrieve parts of documents that contain specific information. But information access and retrieval are essential to serve the delivery and application of evidence-based medicine. Methods: The eXtensible Markup Language (XML) provides a standard means to explicitly describe a document‘s structure and to identify meaningful elements insid

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Blanke, Tobias. "Theoretical evaluation of XML retrieval." ACM SIGIR Forum 46, no. 1 (2012): 82–83. http://dx.doi.org/10.1145/2215676.2215689.

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Blanke, Tobias, and Mounia Lalmas. "Specificity aboutness in XML retrieval." Information Retrieval 14, no. 1 (2010): 68–88. http://dx.doi.org/10.1007/s10791-010-9144-6.

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Arvola, Paavo, Jaana Kekäläinen, and Marko Junkkari. "Contextualization models for XML retrieval." Information Processing & Management 47, no. 5 (2011): 762–76. http://dx.doi.org/10.1016/j.ipm.2011.02.006.

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Chiu, Yu Bin, Huei Huang Chen, Chu Yen Liu, Shih Chih Chen, and Chung Wen Hung. "Efficient Storage and Retrieval of XML Documents Using XQuery." Advanced Materials Research 779-780 (September 2013): 1685–88. http://dx.doi.org/10.4028/www.scientific.net/amr.779-780.1685.

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XML has already been the standard of data interchange on the Internet. Nowadays, a large amount of data is represented in XML format. However, most of the critical data in businesses are still stored in relational database management systems. It is difficult to query XML databases because of its textual format. This research intends to tackle this problem, and we proposed a system to manage XML documents that could be queried by the query language XQuery. XML documents are stored in relational format and the XQuery expressions are translated into appropriate SQL queries. The results of the SQL

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Song, Ling, Qian Gi Lv, and Xiao Bing Tang. "Semantic Search for XML Documents." Applied Mechanics and Materials 48-49 (February 2011): 1028–31. http://dx.doi.org/10.4028/www.scientific.net/amm.48-49.1028.

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With the continuous growth in the XML data, the ability to search in massive collections of XML data becomes important. In this paper, we present efficient techniques that are able to employ bloom-filtering to decrease computation complexity that is used to filter irrelevant XML paths. After filtering, a kind of semantic measure is used to compute similarity between the query and the relevant XML documents, which is used to rank retrieval results. Experiment results show that the retrieval prototype system based on bloom-filtering runs faster than ever under the almost same average precise.

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Hong, Seong-Yong, and Sung-Joon Lee. "An Intelligent Web Digital Image Metadata Service Platform for Social Curation Commerce Environment." Modelling and Simulation in Engineering 2015 (2015): 1–10. http://dx.doi.org/10.1155/2015/651428.

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Information management includes multimedia data management, knowledge management, collaboration, and agents, all of which are supporting technologies for XML. XML technologies have an impact on multimedia databases as well as collaborative technologies and knowledge management. That is, e-commerce documents are encoded in XML and are gaining much popularity for business-to-business or business-to-consumer transactions. Recently, the internet sites, such as e-commerce sites and shopping mall sites, deal with a lot of image and multimedia information. This paper proposes an intelligent web digit

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Ahn, Byeongtae. "A Study on Image Search System using Semantics Based on Smartphone." International Journal of Engineering and Advanced Technology 10, no. 5 (2021): 381–85. http://dx.doi.org/10.35940/ijeat.e2841.0610521.

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Image semantic retrieval has been a crux to bridge "semantic gap" between the simple visual features and the abundant semantics delivered by a image. Effective image retrieval using semantics is one of the major challenges in image retrieval. We suggest a semantic retrieval and clustering method of image using image annotation user interface. And also design and implement a image semantic search management system that facilitates image management and semantic retrieval, which fully relies on the MPEG-7 standard as information base, and using a native XML database, which is Berkeley DB XML

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Byeongtae, Ahn. "A Study on Image Search System using Semantics Based on Smartphone." International Journal of Engineering and Advanced Technology (IJEAT) 10, no. 5 (2021): 381–85. https://doi.org/10.35940/ijeat.E2841.0610521.

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Image semantic retrieval has been a crux to bridge "semantic gap" between the simple visual features and the abundant semantics delivered by a image. Effective image retrieval using semantics is one of the major challenges in image retrieval. We suggest a semantic retrieval and clustering method of image using image annotation user interface. And also design and implement a image semantic search management system that facilitates image management and semantic retrieval, which fully relies on the MPEG-7 standard as information base, and using a native XML database, which is Berkeley D

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WANG, JASON T. L., JIANGHUI LIU, and JUNHAN WANG. "XML CLUSTERING AND RETRIEVAL THROUGH PRINCIPAL COMPONENT ANALYSIS." International Journal on Artificial Intelligence Tools 14, no. 04 (2005): 683–99. http://dx.doi.org/10.1142/s0218213005002326.

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XML is increasingly important in data exchange and information management. A great deal of efforts have been spent in developing efficient techniques for storing, querying, indexing and accessing XML documents. In this paper we propose a new approach to clustering XML data. In contrast to previous work, which focused on documents defined by different DTDs, the proposed method works for documents with the same DTD. Our approach is to extract features from documents, modeled by ordered labeled trees, and transform the documents to vectors in a high-dimensional Euclidean space based on the occurr

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Yang, Lin Hui, Xin Ye Li, and Shao Hua Sun. "Research on the Technology of XML Faceted Search Based on User’s Cognitive." Advanced Materials Research 684 (April 2013): 588–91. http://dx.doi.org/10.4028/www.scientific.net/amr.684.588.

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In information retrieval, the user cognitive factors on the search process and results have the significant influence. First of all, the user cognitive factors are reasonably acquired and expressed, and then the technology of XML is applied to faceted recommend. Finally, according to the XML key technical characteristics that in the result shows, different cognitive styles and space ability have different display format. To effectively improve the XML retrieval efficiency and customer satisfaction, the methods not only have the certain reference value, and also have important practical signifi

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22

Yao, Quan Zhu, Bing Tian, and Wang Yun He. "XML Keyword Search Algorithm Based on Level-Traverse Encoding." Applied Mechanics and Materials 263-266 (December 2012): 1553–58. http://dx.doi.org/10.4028/www.scientific.net/amm.263-266.1553.

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For XML documents, existing keyword retrieval methods encode each node with Dewey encoding, comparing Dewey encodings part by part is necessary in LCA computation. When the depth of XML is large, lots of LCA computations will affect the performance of keyword search. In this paper we propose a novel labeling method called Level-TRaverse (LTR) encoding, combine with the definition of the result set based on Exclusive Lowest Common Ancestor (ELCA),design a query Bottom-Up Level Algorithm(BULA).The experiments demonstrate this method improves the efficiency and the veracity of XML keyword retriev

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Lalmas, Mounia, and Anastasios Tombros. "Evaluating XML retrieval effectiveness at INEX." ACM SIGIR Forum 41, no. 1 (2007): 40–57. http://dx.doi.org/10.1145/1273221.1273225.

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24

Luoma, Olli. "Relevance measures for XML information retrieval." International Journal of Web and Grid Services 3, no. 2 (2007): 170. http://dx.doi.org/10.1504/ijwgs.2007.014073.

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25

de Campos, Luis M., Juan M. Fernandez-Luna, Juan F. Huete, and Eduardo Vicente-Lopez. "Using Personalization to Improve XML Retrieval." IEEE Transactions on Knowledge and Data Engineering 26, no. 5 (2014): 1280–92. http://dx.doi.org/10.1109/tkde.2013.75.

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26

Roko, Abubakar, Shyamala Doraisamy, Azreen Azman, and Azrul Hazri Jantan. "Named Entity Based Ranking with Term Proximity for XML Retrieval." International Journal of Information Retrieval Research 8, no. 2 (2018): 57–77. http://dx.doi.org/10.4018/ijirr.2018040104.

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In this article, an indexing scheme that includes the named entity category for each indexed term is proposed. Based on this, two methods are proposed, one to infer the semantics of an XML element based on its data content, called the confidence value of the element, and the second method computes the proximity scores of the query terms. The confidence value of an element is obtained based on the probability of a named entity category in the data content of the underlying XML element. The proximity score of the query terms measures the proximity and ordering of the query term within an XML ele

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SRINIVASA, K. G., S. SHARATH, K. R. VENUGOPAL, and M. PATNAIK. "SAGAXSEARCH: AN XML INFORMATION RETRIEVAL MECHANISM USING SELF ADAPTIVE GENETIC ALGORITHMS." International Journal of Computational Intelligence and Applications 05, no. 04 (2005): 471–93. http://dx.doi.org/10.1142/s1469026805001738.

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The XML technology, with its self-describing and extensible tags, is significantly contributing to the next generation semantic web. The present search techniques used for HTML and text documents are not efficient when retrieving relevant XML documents. In this paper, Self Adaptive Genetic Algorithms are presented to learn about the tags, which are useful in indexing. The indices and relationship strength metric are used to extract fast and accurate semantically related elements in the XML documents. The Experiments are conducted on the DataBase systems and Logic Programming (DBLP) XML corpus

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Krücken, Peter, Wolf Mueller, Kerstin Denecke, and Stefan Kropf. "Structuring Legacy Pathology Reports by openEHR Archetypes to Enable Semantic Querying." Methods of Information in Medicine 56, no. 03 (2017): 230–37. http://dx.doi.org/10.3414/me16-01-0073.

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SummaryBackground: Clinical information is often stored as free text, e.g. in discharge summaries or pathology reports. These documents are semi-structured using section headers, numbered lists, items and classification strings. However, it is still challenging to retrieve relevant documents since keyword searches applied on complete unstructured documents result in many false positive retrieval results.Objectives: We are concentrating on the processing of pathology reports as an example for unstructured clinical documents. The objective is to transform reports semi- automatically into an info

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Yusof, Mohd Kamir. "Efficiency of JSON for Data Retrieval in Big Data." Indonesian Journal of Electrical Engineering and Computer Science 7, no. 1 (2017): 250. http://dx.doi.org/10.11591/ijeecs.v7.i1.pp250-262.

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Big data is the latest industry buzzword to describe large volume of structured and unstructured data that can be difficult to process and analyze. Most of organization looking for the best approach to manage and analyze the large volume of data especially in making a decision. XML is chosen by many organization because of powerful approach during retrieval and storage processes. However, XML approach, the execution time for retrieving large volume of data are still considerably inefficient due to several factors. In this contribution, two databases approaches namely Extensible Markup Language

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Fu, Da Jie. "Comparative Research of Two XML Document Storage Modes Based on Relational Database." Applied Mechanics and Materials 263-266 (December 2012): 1360–63. http://dx.doi.org/10.4028/www.scientific.net/amm.263-266.1360.

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XML has become one of the general data exchange formats in the current Web application programs, with a wide range of applications in e-commerce, e-books, mobile communications and other fields. XML data storage technology is the key technology for XML applications, and an effective XML data storage, retrieval and management mechanism is a strong driving force for the development of XML. At present, XML data storage technology is generally divided into two categories, which are storage technologies based on a file system and based on a database. In this paper, the technical characteristics of

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Hwang, Jeong Hee, and Keun Ho Ryu. "Structure-based Clustering for XML Document Retrieval." KIPS Transactions:PartD 11D, no. 7 (2004): 1357–66. http://dx.doi.org/10.3745/kipstd.2004.11d.7.1357.

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Wichaiwong, Tanakorn. "An Exponentiation Method for XML Element Retrieval." Scientific World Journal 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/404518.

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XML document is now widely used for modelling and storing structured documents. The structure is very rich and carries important information about contents and their relationships, for example, e-Commerce. XML data-centric collections require query terms allowing users to specify constraints on the document structure; mapping structure queries and assigning the weight are significant for the set of possibly relevant documents with respect to structural conditions. In this paper, we present an extension to the MEXIR search system that supports the combination of structural and content queries i

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Pardede, Eric, J. Rahayu, Ramanpreet Aujla, and David Taniar. "SQL/XML Hierarchical Query Performance Analysis in an XML-Enabled Database System." JUCS - Journal of Universal Computer Science 15, no. (10) (2009): 2058–77. https://doi.org/10.3217/jucs-015-10-2058.

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The increase utilization of XML structure for data representation, exchange, and integration has strengthened the need for an efficient storage and retrieval of XML data. Currently, there are two major streams of XML data repositories. The first stream is the Native XML database systems which are built solely to store and manipulate XML data, and equipped with the standard XML query language known as XPath and XQuery. The second stream is the XML-Enabled database systems which are generally existing traditional database systems enhanced with XML storage capabilities. The SQL/XML standard for X

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Jiang, Haifeng, and Chang Wan. "Realization of Dynamic Interface and High Performance Data Retrieval." Computer and Information Science 10, no. 4 (2017): 16. http://dx.doi.org/10.5539/cis.v10n4p16.

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This paper introduces a method to realize dynamic interface, and designs a database storage model based on XML field technology to realize convenient data storage, any combination condition retrieval function and how to improve the retrieval speed in this kind of storage model. Usually a business system needs to provide information entry and retrieval functions, software designers have to design the appropriate entry items, input interface and retrieval functions for each business system and spend too much time on the repetitive works. And later engineers have to maintain the changing needs of

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35

Zhang, Tao, Qiu Hong Wang, and Jiang Han. "Research on Intelligent Fault Diagnosis System Based on Numerical Turning Machine." Applied Mechanics and Materials 192 (July 2012): 397–400. http://dx.doi.org/10.4028/www.scientific.net/amm.192.397.

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According to the problem of NC Turning Machine fault diagnosis,this paper use frame as express of fault case,through XML case of storage and retrieval,which can realize the intelligent fault diagnosis reasoning Based on CBR. The redevelopment data stored of the fault cases in the XML neutral document,while XML doucument has the advantage of small data quantity and strong universal make it exchange and transmission easily. provided a new way of data exchange and information integration.

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Samadi, Nafisse, and Sri Devi Ravana (Corresponding Author). "XML CLUSTERING FRAMEWORK BASED ON DOCUMENT CONTENT AND STRUCTURE IN A HETEROGENEOUS DIGITAL LIBRARY." Malaysian Journal of Computer Science 36, no. 2 (2023): 124–47. http://dx.doi.org/10.22452/mjcs.vol36no2.2.

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As textually published information is increasing in digital libraries, efficient retrieval methods are required. Textual documents in a digital library are available in various structures and contents. It is possible to represent these documents with hierarchical levels of granularity when these are organized in XML structure to improve precision by focused retrieval. By this means, contextual elements of each document can be retrieved from a known structure. One solution for retrieving these elements is clustering from a combination of Content and Structural similarities. To achieve this, a n

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Cheol-Joo, Chae, Choi Kiseok, and Choi Kwang-Nam. "The XML based Electronic Document Image Retrieval System." Indian Journal of Science and Technology 8, S9 (2015): 239. http://dx.doi.org/10.17485/ijst/2015/v8is9/68316.

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kumar, K. Naresh, Ch Satyanand Reddy, and N. V. E. S. Murthy. "Fuzzy-Based XML Knowledge Retrieval Methods in Edaphology." International Journal of Intelligent Systems and Applications 8, no. 5 (2016): 55–64. http://dx.doi.org/10.5815/ijisa.2016.05.08.

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CHANG, Hsu-Kuang, King-Chu HUNG, and I.-Chang JOU. "Efficient XML Retrieval Service with Complete Path Representation." IEICE Transactions on Information and Systems E96.D, no. 4 (2013): 906–17. http://dx.doi.org/10.1587/transinf.e96.d.906.

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Baeza-Yates, Ricardo, Norbert Fuhr, and Yoelle Maarek. "Introduction to the special issue on XML retrieval." ACM Transactions on Information Systems 24, no. 4 (2006): 405–6. http://dx.doi.org/10.1145/1185877.1185878.

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Ashoori, Elham. "Using topic shifts in content-oriented XML retrieval." ACM SIGIR Forum 43, no. 1 (2009): 70. http://dx.doi.org/10.1145/1670598.1670614.

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Marrara, Stefania, and Gabriella Pasi. "Fuzzy Approaches to Flexible Querying in XML Retrieval." International Journal of Computational Intelligence Systems 9, sup1 (2016): 95–103. http://dx.doi.org/10.1080/18756891.2016.1180822.

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Piwowarski, Benjamin, Andrew Trotman, and Mounia Lalmas. "Sound and complete relevance assessment for XML retrieval." ACM Transactions on Information Systems 27, no. 1 (2008): 1–37. http://dx.doi.org/10.1145/1416950.1416951.

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Tahraoui, Mohammed Amin, Karen Pinel-Sauvagnat, Cyril Laitang, Mohand Boughanem, Hamamache Kheddouci, and Lei Ning. "A survey on tree matching and XML retrieval." Computer Science Review 8 (May 2013): 1–23. http://dx.doi.org/10.1016/j.cosrev.2013.02.001.

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Larson, Ray R. "A Fusion Approach to XML Structured Document Retrieval." Information Retrieval 8, no. 4 (2005): 601–29. http://dx.doi.org/10.1007/s10791-005-0749-0.

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Kamps, Jaap, Maarten de Rijke, and B�rkur Sigurbj�rnsson. "The Importance of Length Normalization for XML Retrieval." Information Retrieval 8, no. 4 (2005): 631–54. http://dx.doi.org/10.1007/s10791-005-0750-7.

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de Campos, Luis M., Juan M. Fernández-Luna, Juan F. Huete, and Carlos Martín-Dancausa. "Managing structured queries in probabilistic XML retrieval systems." Information Processing & Management 46, no. 5 (2010): 514–32. http://dx.doi.org/10.1016/j.ipm.2009.11.006.

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Bremer, Jan-Marco, and Michael Gertz. "Integrating document and data retrieval based on XML." VLDB Journal 15, no. 1 (2005): 53–83. http://dx.doi.org/10.1007/s00778-004-0150-4.

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Luk, R. W. P., B. K. Y. T'sou, T. B. Y. Lai, O. O. Y. Kwong, F. C. Y. Chik, and L. Y. L. Cheung. "Bilingual legal document retrieval and management using XML." Software: Practice and Experience 33, no. 1 (2002): 41–59. http://dx.doi.org/10.1002/spe.494.

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Ashoori, Elham, Mounia Lalmas, and Theodora Tsikrika. "Examining topic shifts in content-oriented XML retrieval." International Journal on Digital Libraries 8, no. 1 (2007): 39–60. http://dx.doi.org/10.1007/s00799-007-0026-5.

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