XML Documents Research Articles

Structural Information Retrieval in XML Documents: A Graph-based Approach

Although retrieval engines are becoming more and more functional and efficient, they still have the drawback of not being able to locate the relevant documentary granularity, which results in ignoring the structural aspect. In the context of XML document, Information Retrieval Systems allow to return the user’s documentary granules. Several studies have used graphs to represent XML documents. However, in the scope of this research, the semi-structured document’s structure and that of a user’s query can be seen as arborescences composed of a hierarchy of nested elements. By using graph theory, by calculating the structural proximity and especially the intersection between these two arborescences. The article presents a model for structural information retrieval based on graphs. A collection of multimedia documents are randomly extracted from INEX (Initiative for the Evaluation of XML Retrieval) 2010 to validate the approach. The first results shows the interest of such an approach.

XAPP: An Implementation of SAX-Based Method for Mapping XML Document to and from a Relational Database

Extensible Markup Language (XML) is the standard medium for data exchange among businesses over the Internet, hence the need for effective management. However, since XML was not designed for storage and retrieval, its management has become an open research area in the database community. Existing mapping techniques for XML-to-relational database adopt either the structural mapping or the model mapping. Though numerous mapping approaches have been developed, mapping and reconstruction time had been problematic, especially when the document size is large and can hardly fit into main memory. In this research, an application codenamed XAPP, a new lightweight application that adopts a novel model mapping approach was developed using Simple API for XML (SAX) parser. XAPP accepts a document with or without Document Type Definition (DTD). It implements two algorithms: one maps XML data to a relational database and improves mapping time, and the other reconstructs an XML document from a relational database to improve reconstruction time and minimise memory usage. The performance of XAPP was analysed and compared with the Document Object Model (DOM) algorithm. XAPP proves to perform significantly better than the DOM-based algorithm in terms of mapping and reconstruction time, and memory efficiency. The correctness of XAPP was also verified.

Программное извлечение данных из word-документов на основе ситуационно-ориентированного подхода

The article discusses the use of situation-oriented approach to software processing word-documents. The documents under consideration are prepared by the user in the environment of the Microsoft Word processor or its analogs and are used in the future as data sources. The openness of the Office Open XML and Open Document Format made it possible to apply the concept of virtual documents mapped to ZIP archives for programmatic access to XML components of word documents in a situational environment. The importance of developing preliminary agreements regarding the placement of information in the document for subsequent search and retrieval, for example, using pre-prepared templates, is substantiated. For the DOCX and ODT formats, the article discusses the use of key phrases, bookmarks, content controls, custom XML components to organize the extraction of entered data. For each option, tree-like models of access to the extracted data, as well as the corresponding XPath expressions, are built. It is noted that the use of one or another option depends on the functionality and limitations of the word processor and is characterized by varying complexity of developing a blank template, entering data by the user and programming data extraction. The applied solution is based on entering metadata into the article using content controls placed in a stub template and bound to elements of a custom XML component. The developed hierarchical situational model of HSM provides extraction of an XML component, loading it into a DOM object and XSLT transformations to obtain the resulting data: an error report and JavaScript code for subsequent use of the extracted metadata.

Research on Ocean Government Data Extraction and Clustering Based on XML Document Similarity Technology

Yao, B.; Wang, L., and Liu, S., 2019. Research on ocean government data extraction and clustering based on XML document similarity technology. In: Li, L.; Wan, X., and Huang, X. (eds.), Recent Developments in Practices and Research on Coastal Regions: Transportation, Environment and Economy. Journal of Coastal Research, Special Issue No. 98, pp. 259–262. Coconut Creek (Florida), ISSN 0749-0208.In component clustering, a recursive algorithm for computing the similarity between components based on extensible markup language (XML) description is proposed, which can effectively measure the structure and semantic information contained in the XML description document. The document similarity matrix is constructed. The high-dimensional samples are mapped to the two-dimensional plane by a genetic algorithm, and the k-means algorithm is used to cluster to obtain the global optimal component clustering. Finally, experiments are carried out on the component library test model. The experimental results show that the component clustering algorithm based on XML similarity is feasible and effective in component query practice.

A Narrative Review of Storing and Querying XML Documents Using Relational Database

Extensible Markup Language (XML) has become a common language for data interchange and data representation in the Web. The evolution of the big data environment and the large volume of data which is being represented by XML on the Web increase the challenges in effectively managing such data in terms of storing and querying. Numerous solutions have been introduced to store and query XML data, including the file systems, Object-Oriented Database (OODB), Native XML Database (NXD), and Relational Database (RDB). Previous research attempts indicate that RDB is the most powerful technology for managing XML data to date. Because of the structure variations of XML and RDB, the need to map XML data to an RDB scheme is increased. This growth has prompted numerous researchers and database vendors to propose different approaches to map XML documents to an RDB, translating different types of XPath queries to SQL queries and returning the results to an XML format. This paper aims to comprehensively review most cited and latest mapping approaches and database vendors that use RDB solution to store and query XML documents, in a narrative manner. The advantages and the drawbacks of each approach is discussed, particularly in terms of storing and querying. The paper also provides some insight into managing XML documents using RDB solution in terms of storing and querying and contributes to the XML community.

Optimization Algorithms Study and Implementation on Graph Drawing Based on XML Document

In the process of engineering applications, we often use a large number of vertices and edges to represent the complex system model, but sometimes the model is so complex that it is impossible to draw the graph neatly and beautifully by hand. So how to draw the graph automatically using the computer and how to make the graph visual become an important research topic. Based on the study on the genetic algorithm, SHLA algorithm and FR algorithm, we implement these algorithms by analyzing the pseudo-codes. Especially we focus on the study of the source programming about FR-boost and then implement an improved FR algorithm that selects XML document as the input and output graph files. It can effectively reduce the complexity of algorithm and increase the point-line graph’s visualization.

Exploiting Links to Improve Search in XML Documents

Exploiting Links to Improve Search in XML Documents

CBSL − A Compressed Binary String Labeling Scheme for Dynamic Update of XML Documents

The growing volume of XML documents over the Web has increased the need for an efficient mechanism to facilitate query processing. Many labeling schemes have been introduced to optimize data retrieval and query processing on XML database documents. As it is known, labels hold information about XML tree nodes such as their position, their relationship with other nodes and their order, which helps in query processing. Most of the existing labeling schemes support query processing over static XML documents. However, they need to re-label during dynamic update. In this paper a compressed binary string labeling scheme is proposed which supports dynamic update of XML documents without re-labeling existing nodes. Analytical results show that the proposed labeling scheme takes less label size in comparison with other labeling schemes. Also, an experiment has been conducted to evaluate the label generation time as well as update processing.

Direct Update of XML Documents with Data Values Compressed by Tree Grammars

Direct Update of XML Documents with Data Values Compressed by Tree Grammars

Mapping of XML Document and Relational Database (Using Structural Queries)

Mapping of XML Document and Relational Database (Using Structural Queries)

Investigation of Mining Association Rules on XML Document

Investigation of Mining Association Rules on XML Document

An Efficient prefix based labeling scheme for Dynamic update of XML Documents

The increasing volume of XML documents and the real-world requirement to support the updations has motivated the research community to develop dynamic labelling schemes. Each of the dynamic labelling schemes proposed till date differs in characteristics and has its own advantages and limitations. They may differ in terms of the query supported, their update performance, label size, etc. In this paper, a new prefix based labelling scheme is proposed which is compact, dynamic. And it also facilitates the computation of structural relationships which is the core part of query processing. The proposed scheme can handle both static as well as dynamic XML documents. The experimentation is conducted to evaluate the performance of storage requirement, structural relationship computation and update processing. The result is compared with some of the existing labelling mechanisms.

Evaluating Queries and Updates on Big XML Documents

In this paper we present Andromeda, a system for processing queries and updates on large XML documents. The system is based on the idea of statically and dynamically partitioning the input document, so as to distribute the computing load among the machines of a MapReduce cluster.

Research on the Similarity of Fuzzy XML Documents and Fuzzy DTD

Research on the Similarity of Fuzzy XML Documents and Fuzzy DTD

Relevant XML Documents - Approach Based on Vectors and Weight Calculation of Terms

Relevant XML Documents - Approach Based on Vectors and Weight Calculation of Terms

A Systematic Approach for Changing XML Namespaces in XML Schemas and Managing their Effects on Associated XML Documents under Schema Versioning

A Systematic Approach for Changing XML Namespaces in XML Schemas and Managing their Effects on Associated XML Documents under Schema Versioning

Building Semantic Trees from XML Documents

The distributed nature of the Web, as a decentralized system exchanging information between heterogeneous sources, has underlined the need to manage interoperability, i.e., the ability to automatically interpret information in Web documents exchanged between different sources, necessary for efficient information management and search applications. In this context, XML was introduced as a data representation standard that simplifies the tasks of interoperation and integration among heterogeneous data sources, allowing to represent data in (semi-) structured documents consisting of hierarchically nested elements and atomic attributes. However, while XML was shown most effective in exchanging data, i.e., in syntactic interoperability, it has been proven limited when it comes to handling semantics, i.e., semantic interoperability, since it only specifies the syntactic and structural properties of the data without any further semantic meaning. As a result, XML semantic-aware processing has become a motivating challenge in Web data management, requiring dedicated semantic analysis and disambiguation methods to assign well-defined meaning to XML elements and attributes. In this context, most existing approaches: (i) ignore the problem of identifying ambiguous XML elements/nodes, (ii) only partially consider their structural relationships/context, (iii) use syntactic information in processing XML data regardless of the semantics involved, and (iv) are static in adopting fixed disambiguation constraints thus limiting user involvement. In this paper, we provide a new XML Semantic Disambiguation Framework titled XSDF designed to address each of the above limitations, taking as input: an XML document, and then producing as output a semantically augmented XML tree made of unambiguous semantic concepts extracted from a reference machine-readable semantic network. SDF consists of four main modules for: (i) linguistic pre-processing of simple/compound XML node labels and values, (ii) selecting ambiguous XML nodes as targets for disambiguation, (iii) representing target nodes as special sphere neighborhood vectors including all XML structural relationships within a (user-chosen) range, and (iv) running context vectors through a hybrid disambiguation process, combining two approaches: concept-based and context-based disambiguation, allowing the user to tune disambiguation parameters following her needs. Conducted experiments demonstrate the effectiveness and efficiency of our approach in comparison with alternative methods. We also discuss some practical applications of our method, ranging over semantic-aware query rewriting, semantic document clustering and classification, Mobile and Web services search and discovery, as well as blog analysis and event detection in social networks and tweets.

BIM and Thermographic Sensing: Reflecting the As-is Building Condition in Energy Analysis

This paper presents an automated computer vision-based system to update BIM data by leveraging multi-modal visual data collected from existing buildings under inspection. Currently, visual inspections are conducted for building envelopes or mechanical systems, and auditors analyze energy-related contextual information to examine if their performance is maintained as expected by the design. By translating 3D surface thermal profiles into energy performance metrics such as actual R-values at point-level and by mapping such properties to the associated BIM elements using XML Document Object Model (DOM), the proposed method shortens the energy performance modeling gap between the architectural information in the as-designed BIM and the as-is building condition, which improve the reliability of building energy analysis. Several case studies were conducted to experimentally evaluate their impact on BIM-based energy analysis to calculate energy load. The experimental results on existing buildings show that (1) the point-level thermography-based thermal resistance measurement can be automatically matched with the associated BIM elements; and (2) their corresponding thermal properties are automatically updated in gbXML schema. This paper provides practitioners with insight to uncover the fundamentals of how multi-modal visual data can be used to improve the accuracy of building energy modeling for retrofit analysis. Open research challenges and lessons learned from real-world case studies are discussed in detail.

A Comparative Study: Change Detection and Querying Dynamic XML Documents

<span>The efficient management of the dynamic XML documents is a complex area of research. The changes and size of the XML documents throughout its lifetime are limitless. Change detection is an important part of version management to identify difference between successive versions of a document. Document content is continuously evolving. Users wanted to be able to query previous versions, query changes in documents, as well as to retrieve a particular document version efficiently. In this paper we provide comprehensive comparative analysis of various control schemes for change detection and querying dynamic XML documents.</span>

Clustering XML Documents using Structure and Content Based in a Proposal Similarity Function (OverallSimSUX)

Every day more digital data in semi-structured format are available on the World Wide Web, corporate intranets, and other media. Knowledge management using information search and processing is essential in the field of academic writing. This task becomes increasingly complex and defiant, mainly because collections of documents are usually heterogeneous, big, diverse, and dynamic. To resolve these challenges it is essential to improve management of time necessary to process scientific information. In this paper, we propose a new method of automatic clustering of XML documents based on their content and structure, as well as on a new similarity function OverallSimSUX which facilitates capturing the degree of similarity among documents. Evaluation of our proposal by means of experiments with data sets showed better results than those in previous work.