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Frameworks are popularly used to reduce implementation complexity and improve productivity. Unfortunately, most frameworks are quite complex and not well documented. Hence, correctly and effectively programming with Framework is still a great challenge. One of the significant obstacles for us to smoothly use Framework is the complicated attribute value configuration of XML files. To overcome these difficulties, we present XMLValue to automatically recommend XML attribute values using association rules and NLP techniques. Experimental results show that our tool is efficient and effective for mining reusable configuration snippets, and has significantly shorten development time for framework based programming, and is general enough to support a variety of frameworks, and has real time performance for code assistance.

Printing good-sized complicated practical report forms is one puzzle in application system with B/S architecture. In order to solve this problem, performing data exchange using XML to come true printing is explored. Windows Form in the framework of .NET is embedded in FrontPage. By self-programming, XML document is analyzed and client-side printing is controlled. Fundamental technique on implementing printing application system report forms with B/S architecture based on XML document is introduced in detail.

Nowadays, the performance and security are always hot research topics in different data fusion systems. In this paper, a more efficient and secure heterogeneous data fusion system has been proposed and implemented. Firstly, based on the global data pattern, which is referred to the concept of view in database, the heterogeneous data is transformed into Extensible Markup Language(XML) documents which are regarded as intermediate data conversion format. Secondly, these XML documents are organized as binary trees and stored in trifurcate chain-table, combined with the XML document tree node encoding. Then the appropriate node attributes are selected as index entries with the security level information, all of these makes up the innovative and dynamic index file with security labels, which is the basis of data querying, fusing and showing. Finally, the system is verified by experiments, and results show that the system can feasibly fuse the heterogeneous data correctly and guarantee the safety of the system.

XML is a standard format for data exchange overinternet. Also huge amount of information is tagged and storedin XML format. Processing XML data has its difficulties due tothe schema centric and semi-structured nature of the majorportion of existing XML data. The data embeded tree stucturemakes it more complicated to process. XML processing usingRDBMS systems and Native XML databases like BaseX, eXist-DBhas its own limitations. Native XML databases are not suitablefor distributed processing. So they just have to bound withsingle systems resources, which are not enough for big dataprocessing. Graph databases and Graph database technologies areemmerging in the recent past. They are also suitable to process bigdata due to the extension of parallel processing features in graphdata processors. Modeling XML data as a graph and processingit with graph processors are benaficial in many contests. In thispaper the graph modleing, storage and processing possibilities ofXML data are analysed. The major graph database Neo4j andthe GraphX graph processor extension embeded with ApacheSpark distributed in-memory processing system are utilized forquerying XML data.

This paper proposes an XML representation of octgrid completely. Octgrid is a data structure based on octal grid graphs for heterogeneous rectangular dissections. This model is represented by a list structure called H3-Code. The file format of H3-Code is a plain text file that consists of a plurality of space separated field. Therefore we introduced the XML representation called H14-Code.

Agile software development methodology is an iterative and incremental method in making interactions more important than process and tools. The method also emphasizes more on developing software rather than making a comprehensive documentation. Therefore, web developers like to adapt agile software development methodology in their web development. The reason is because the methodology delivers web application faster than the traditional software development methodology. As advantages of this method, web application is developed in a short time. Although these make huge benefits, the most important thing in software development life cycle has been ignored. That is, documentation process in capturing requirements and design. Therefore, this paper presents a tool named XML_DocTracker for generating the software requirements specification (SRS) from XML schema as well as addressing the versioning problems during generating the SRS. XML_DocTracker is implemented based on the framework for transformation rules from XML Schema. The framework also addresses the versioning factor using traceability for detecting the document changes. Based on the framework, XML_DocTracker is developed and the tool is able to generate the SRS from the XML schema as well as able to detect document changes in SRS due to traceability factor that is embedded inside the tool. The tool can be used for software community who want to generate the SRS from the source codes if the SRS did not exist for that particular software. This paper contribution is detecting new type of element evolution in SRS when new XML schema version is introduced.

XML documents have both structural and semantic information, bringing data integration and deep utilization based on XML more precise description and versatile expression. But in the meanwhile traditional NLP and DM methods can't be applied directly. Feature dimension reduction and general similarity of XML based on tensor analysis are discussed. Considering the correlation between XML's structure and content, a tensor based model for describing XML documents and an MMI method to XML's dimension reduction is presented. Since structure and content are not independent with each other, a tensor based algorithm to calculate general similarity from a non-linear angle is designed to show their relationships and effects to its performance.

The Xevolver framework is a code transformation framework for supporting evolutional modifications of high performance computing codes. This paper introduces a set of software modules that facilitates administrative tasks about multiple code transformations on multiple source codes. We call this set of software modules the xevdriver, because it drives transformations using Xevolver framework. First, xevdriver provides an abstract view of temporary files. Parsing and unparsing between Fortran and XML are done automatically, and the user do not have to keep track of temporary file names during a series of applications of code transformations. Second, xevdriver also provides an abstract view of combinations of transformations. Xevdriver provides a script language, in which users can define combinations of code transformations as procedures. Third, the logging functions and a log-viewer are provided in accordance with the above abstractions. Users can check how the source codes are transformed on the log-viewer from the high level abstractions of code transformation procedures, and can inspect the intermediate results down into an arbitrary level of concreteness of the implementations of transformations. Our toolset will help development, management and applications of complex code transformations based on Xevolver framework.

XML has been evolved from being used for data representation to a structured document format. It has also grown in size from several bytes of small number of files to giga-or terabytes of size with millions of files. XML databases have been developed to efficiently store XML documents with XQuery as querying language from XML documents. However, they have difficulties in dealing with huge number of files and larger space, while most of XML database systems are implemented as centralized systems. Therefore, we explore possibilities to utilize distributed and parallel computing architecture in order to improve its performance. This paper describes directions and simple attempts to take advantage of distributed and parallel computing architecture by extending XQuery processor facilities. Attempts is carried out in an emerging native XML database (BaseX [1]).

Today, we're seeing strong demand real-time information, with a rapid expansion of mobile learning (m-learning). We also see that there are many educational resources on the Internet. The learning objects (LOs) are designed as a way to reuse these resources. Some of these LOs are built for fixed devices, which hinders their use on mobile devices. A LO is an area that is open to research that has a lot of potential in the creation, adaptation and production of learning content. The language of the Semantic Web using XML technology and ontology are increasingly used in electronic publishing documents while completely separating content from presentation. Creating a new LO with the semantic web is complex and raises difficulties because the available authoring tools that require a general knowledge of XML syntax and its related technologies. In this article, we describe an original approach to generate automatically from ontologies in the field of education, a type of content (XML Schema) for the semantic creating a SQL language LO in a native format XML, which may be subsequently adapted to the display of the mobile devices.

Many challenges confront developers in the field of web engineering. Platform independence as well as the inclusion of domain experts in all phases of the development process are two examples of the most challenging aspects encountered in developing web applications. This paper1 proposes a solution, based on XML technologies, to these two problems.

The requirements of data exchange, with XML as the main format, use structural-centric and object-centric data binding frameworks. Through analysis of the current data binding framework, we present a data-centric XML binding framework in order to establish interfaces between relational databases and XML files. This framework solves the problems of generating large amounts of temporary Java code or producing complex XML schema files. The functions of marshalling and unmarshalling meditate the conversion between relational databases and XML files. In this model, objects and files are completely decoupled. Therefore, it implements a non-invasive from of data binding.

Massive XML (Extensible Markup Language) data are available on the web. XML data labeling schemes have been suggested for structural query processing of massive XML data. Notable schemes include interval- based, prefix-based, and prime number-based labeling schemes. Of these, the prime number labeling scheme has the advantage of query processing by simple arithmetic operations. However, a parallel algorithm for this scheme does not exist. The requirement that all parents' labels have to be multiplied to obtain the label of a node makes it difficult to label XML data in a parallel fashion. To address the issue, in this paper, we propose a cluster-based technique wherein all parent nodes for a node are aggregated to compute its label by two-step MapReduce jobs. Our experiments on real-world XML datasets showed the advantages over a single machine-based system.

Many systems use XML as a standardized information transfer between different components. The possibility to describe the data structure through definition documents enables both sender and receiver to validate information sent and received. However, the XML format requires relatively much bandwidth for a transfer via a network. This feature leads to a very high network load in case of applications with a huge amount of data to be transferred. The developed SIEM-like system from the SIMU project (www.simu-project.de) is based on the IF-MAP protocol and therefore uses the XML-based SOAP to represent and transfer data. To reduce network load, a technique was developed during the SIMU project, which allows a lossless transformation between XML and the relatively new specification called CBOR (RFC-7049). Thus, mobile terminals may be connected to such systems with high performance and low bandwidth usage.

The volume of XML data is tremendous in many areas, especially in data logging and scientific areas. XPath query is the core operation of XML process. It is a challenge to query massive XML data stored in a distributed manner. In this paper, we present an efficient distributed XPath query processing using MapReduce, which simultaneously processes queries for a massive volume of XML data. We first use virtual nodes to split the large scale XML data file into filesplits to the distributed storage system. Then we present the distributed XPath query algorithm to compute different fragments of the document tree in parallel using the MapReduce framework. Furthermore, in order to handle the large XML data efficiently, we build the partitional index and use random access mechanism to perform the query. The experimentation shows that our approach is efficient and scalable on this issue.

This paper presents a detailed analysis of various XML parsing techniques available for efficient memory utilization in embedded system. In addition, we propose iXML a novel XML parsing approach for embedded system based on the inline method. The novel iXML parser can be utilized for known as well as unknown type of XML documents. The approach identifies first the structure of the XML document and subsequently identifies the attributes of the tokens. The identified tokens are then checked for its validity and well formedness. Evaluation experiments clearly indicate that the proposed approach produces superior performance in terms of processing time. The proposed method is then compared with Xerces-DOM and EXDOM and it shows a significant improvement in terms of time and can handle larger data files.

Providing efficient encoding approaches for mining XML query patterns is crucial, as many applications use XML to share data in their disciplines over the Internet. These encoded XML query patterns can be used to design an index mechanism or cached and thus enhance XML query performance. Several XML query pattern mining algorithms have been proposed to record user queries in the system and thus discover the frequent XML query patterns. By using the frequent XML query patterns, the query performance of XML data is improved. However, to find out the frequent XML query patterns from big XML data over the Internet, these existing algorithms are time-consuming and thus are not suitable. MapReduce is a software framework for writing parallel programs and can be used to enhance the performance to encode XML query patterns. In this paper, MapReduce-based algorithms to parallel encode XML queries, report experimental results of the prototype implementation on Hadoop system, and a popular implementation of MapReduce framework are proposed.

In the face of development trend that a single XML document data volume is increasingly big, involved a core problem of XML data query technology is how to effectively solve result that meet certain query semantic, and label used by corresponding document tree based on XML document is the key factor of affecting the query efficiency. This paper, all experimental processing is completed through MapReduce framework, and prefix flow label is taken as object of study. Xwei is proposed in allusion to the problems that redundancy of existing prefix flow label, the length is increased constantly with the increase of the depth of the document tree, specific location cannot be intuitively determined in the document tree, and then, query algorithm efficiency designed by prefix flow label is not high. By means of experiments in the distributed cluster and by contrasting Dewey and ED, the efficiency of Labeling with Xwei is improved by 10% at least, and the query efficiency of Xwei based on the certain query semantics is improved by 33%–75%.

Twig pattern query is the core operation of XML process, which directly affects the efficiency of XML data query. It is a challenge to manipulate massive XML data, especially on distributed cluster, such as how to effectively ensure the completeness and correctness of the query results, and minimize communication costs between the various machines. In this paper, we present TwigStack-MR, which simultaneously processes several twig pattern queries for a massive volume of XML data based on MapReduce framework. We first split the large scale XML data file into file-splits as input to the distributed storage system. Then we present the distributed twig algorithm, processing different subtrees of the document tree in parallel. Finally we use the MapReduce framework, full characteristics of distributed environments, to process twig query efficiently. The experimental results show that our approach is efficient and scalable on this issue.

At present, each department in large enterprises has already setup a large number of databases on Internet. But these databases lack the information sharing each other, forming the detached island of information; therefore enterprise data integration becomes more and more important. This paper presents a data integration and exchange framework under distributed heterogeneous environment based on web services and XML. The detailed functions of the framework are described. The methods are totally implemented in the data integration platform of the housing fund for eliminating isolated information islands.

Web users tend to focus their attention on stream data rather than on archival one. In an XML stream environment, data arrive continuously, which means that queries must be evaluated for producing results on the fly. Thus, it is crucial to count on algorithms that efficiently evaluate multiple queries, usually expressed in terms of keywords, over several XML streams. However, there are few algorithms that evaluate this kind of query. One of them is MKStream, which is the current state-of-the-art algorithm for processing keyword-based queries over XML streams. In order to improve scalability, in this paper we introduce PMKStream (Parallel MKStream), which is a parallel version of MKStream. Like MKStream, PMKStream evaluates multiple keyword queries by using multiple parsing stacks. However, it parallelizes them on a multicore platform, thus reducing response time by up to 57%. A comprehensive set of experiments, using distinct datasets, evaluates its performance and shows that PMKStream is a much more efficient alternative for supporting keyword-based search over XML streams.

Keyword search in XML and relational databases (RDB) has gained popularity as it provides a user-friendly way to explore structured data. Existing works on XML and RDB keyword search only rely on the structures of XML/RDB data and/or schemas, and this causes serious problems of returning incomplete answers, meaningless answers and overwhelming answers. In this paper, we identify the problems of existing keyword search methods and point out that the main reason of these problems is due to the unawareness of the Object-Relationship-Attribute (ORA) semantics in XML/RDB. We exploit the ORA semantics in XML and RDB, and capture these semantics by constructing the Object tree for XML, and the Object-Relationship-Mixed (ORM) data graph for RDB, respectively. Based on the Object tree and the ORM data graph, we propose an ORA-Semantics based keyword search in XML and RDB. Our semantic approach can avoid the problems of existing methods and improves the completeness and correctness of keyword search. In addition, we extend the keyword query language to include keywords that match the metadata, i.e., the names of tags in XML and the names of relations and attributes in RDB. These keywords reduce the ambiguities of queries and enable us to infer user' search intention more precisely. Finally, we incorporate aggregate functions and GROUPBY into keyword queries to retrieve statistical information from XML and RDB.

The high cost of education and the increased number of adult students increased the demand for online degrees. In the current online education model, the school specifies the courses required to obtain a degree. For each course, the instructor specifies the course elements including teaching method and assessments. But research in education has long proved that different students have different capabilities and constraints. Most institutions provide the same courses. A student should be able to select the course that best matches his capabilities and constraints as long as it satisfies the required course outcomes. To achieve this goal, we propose the use of SOA. We introduce an extended service-oriented architecture and an extended service definition. This paper also presents two XML languages. The first, enables course providers to specify courses that have been defined using our extended service. The second enables course requesters to specify their requirements and constraints.

eXtensible Markup Language (XML) is one of the standard data representation nowadays. It can be used in various applications as its flexibility and easy to use so the need to summarize XML document become increasingly an important topic to save time and cost. For these reasons, there are more interest for developing tools for summarizing XML Documents. This paper surveys different approaches for summarizing XML documents regarding to both its structure and content.

In this paper, we are presenting a semi-automatic framework for annotating multi-lingual handwritten texts document images. There is a significant need for a structure that can annotate the coordinate segmentation information of the text present in a handwritten document image to provide a platform for OCR algorithm evaluation. In this paper, we describe an XML based four level annotations of handwritten text image that contain the ground-truth information of script text image in Unicode format. In order to collect the huge amount of data for linguistic researchers, structure provide a way to store and annotate at different four levels: Image, Lines, Words and Characters which aids for benchmarking of various OCRs. Structure would be best source for compilation of an annotated handwritten corpora in systematic and scientific way by storing a labelling(markup) information of image script texts in a Unicode and an XML file format that encapsulates the bounding box pixel information of each level in a collaborative manner. The structure provides useful results based on the annotation for various quantitative and statistical corpus approaches to linguistic analysis.

Conventional approaches to XML clustering by content and structure are generally affected by a limitation due to the adoption of the bag-of-word model for the representation of their textual contents. This choice may lead to consider structure-constrained textual items of separate XML documents as related, even though the actual meaning of such items in their respective contexts is different. To overcome such a limitation, we propose XML clustering by structure-constrained phrases. The latter is a previously unexplored method relying on the more accurate bag-of-phrase model of the XML textual content, with which to better preserve the meaning of the structure-constrained content items for improved clustering effectiveness. In order to conduct an in-depth and systematic study of the effectiveness of the proposed method, we develop a parameter-free prototypical approach to XML partitioning, which projects the XML documents into a space of XML features representing fixed-length sequences of adjacent textual items in the context of root-to-leaf paths. Feature selection without any tunable threshold is used to choose a subset of the XML features on the basis of their relevance to clustering, which is assessed through a new scoring scheme. A comparative experimentation on real-world benchmark XML corpora reveals a higher effectiveness than several state-of-the-art competitors.

Treebanks are essential resources for both data-driven approaches to natural language processing (NLP) and empirical linguistic researches. Developing these resources is time- and cost-consuming and requires specialized expertise. Therefore, they should be designed to be reused for different purposes. Currently, there are several dependency treebanks for some languages which are annotated in CoNLL format. For some languages, such as Persian, they are the few available linguistic resources. These treebanks are more suitable for the input of data-driven parsers, and querying linguistic data in them is not easy. In recent years, XML has been widely used for formatting treebanks, and there are various tools available for querying and annotating a linguistic croups in this format. In this paper, we present a tool for converting a dependency treebank in CoNLL format to an appropriate XML format. We designed the XML scheme to be particularly suitable for writing linguistic queries in XQuery syntax.

The vast amounts of data generated in near real-time due to prolific use of sensors, pervasive usage of mobile Internet, and popularity of social media platforms, necessitates the efficient dissemination of the semi-structured streaming data to the consuming applications. Towards this end, we introduce the subscriber-centric XML filtering approach for seamless and efficient XML stream replication/distribution mechanism. The subscriber-centric filtering architecture can be configured to support different topologies in order to support efficient message filtering for a large number of concurrent subscribers. It allows selective filtering on the various nodes that improves efficiency and provides applications with data on a need-to-know basis. Moreover, it supports inter-operability and allows semi-structured streams generated from multiple sources to be filtered. Our XML filtering network consists of decoupled data producers, message transformation agents and XML brokers that can be deployed in conventional data centers as well as in the public cloud environment. We provide detailed performance results of processing filtering queries in several use case scenarios with varying XML message loads and number of nodes involved in the replication/dissemination process. Our results indicate that the subscriber-centric XML filtering architecture is a viable approach for disseminating semi-structured data streams to the various consuming applications.

Facing tremendous volume of semi-structured XML and non-structured free text, network information retrieval is one of the most research hotspots in dealing with these data more efficiently, precisely and uniformly. Many traditional IR methods ignore text semantics and their labeling result has usually only one level, lacking of context expression as well, therefore structure extraction from free text and its conversion to XML format are studied, with a CRF based algorithm SIECRF provided. Experiment results are analyzed, showing its efficiency to extracting text structure and has a good application future.

International audience; This paper briefly describes and evaluates XSDF, a new XML Semantic Disambiguation Framework, taking as input: an XML document and a general purpose semantic network, and then producing as output a semantically augmented XML tree made of unambiguous semantic concepts. Experiments demonstrate the effectiveness of XSDF in comparison with alternative methods.

Controlled vocabularies such as terminologies and ontologies are regarded as a solution to the achievement of semantic interoperability across healthcare applications. This is yet to be attained. The semantics of current healthcare applications are directly in the source code and database structure and therefore cannot be readily shared. The multilevel model-driven approach is a method to produce semantically interoperable healthcare applications by providing sharable concept models. At this point, the methodology is proven, but implementations are still required. This study presents the fundamentals of knowledge modeling of controlled vocabularies for a XML-based multilevel model specification. The term subset 'Tuberculosis' of the 10th Revision of the International Classification of Diseases (ICD-10) is modeled as constraints to the XML Schema that defines the Reference Model. The Brazilian Mortality and Hospital Information Systems provided sample data for demonstration. The demonstration of the semantic validation of the XML data instances that include the ICD-10 'Tuberculosis' term set, converted to the multilevel model generated, is presented.

XML is a widely adopted technology in various domains ranging from web services to messaging systems, databases grid and scientific computing. However the processing of XML documents is an expensive operation that can degrade performance and limits the adoption of XML for specific applications. As different applications incorporating XML have come to the fore it becomes imperative to conduct a comprehensive study of the issues involved in design of parser. Hence optimizing parser performance has become a research hotspot. This paper focuses on a detailed study of the optimization parameters and design and implementation of a novel parser NXParse while optimizing for character streams, in-place parsing, string transformation control-flow, data structures and recurrent structures. Our empirical analysis shows that the NXParse gives a better parsing performance.

Electronic Data Processing used automated methods for processing commercial data. There is big amount of work on discovering duplicates in relational data; merely elite findings concentrate on duplication in additional multifaceted hierarchical structures Electronic information is one of the key factors in several business operations, applications, and determinations, at the same time as an outcome, guarantee its superiority is necessary. Duplicate finding a little assignment because of the actuality that duplicates are not accurately equivalent, frequently because of the errors in the information. Accordingly, many data processing techniques never apply widespread assessment algorithms which identify precise duplicates. As an alternative, evaluate all objective representations, by means of a probably compound identical approach, to identifying that the object is real world or not. Duplicate detection is applicable in data clean-up and data incorporation applications and which considered comprehensively for relational data or XML document. This paper will provide the person who reads with the groundwork for research in Efficient and Effective Duplicate Detection in Hierarchical Data or XML data.

This paper solves the problem of the excessive memory footprint and the slow speed of parsing when using the DOM method to parse the XML data. As we know the current XML parsing technology is the key of XML research field and now there are a lot of XML parsers, their works plays a significant role in promoting XML parsing, but failed to achieve a good balance in the analysis of both time and memory usage. We propose a hash function based on the XML parser, for evaluating the memory consumption. We have demonstrated the text part of delay spread in terms of the time consumption, using a hash function. Our testing results show that, compared with the traditional method, the memory footprint reduced by 5% and the analytical efficiency increased by 3%.

The increasing amount of available XML documents collections has led to the emergence of new challenges in information retrieval field. Therefore, multiple sources of evidence were used to retrieve XML elements at different levels of granularity. XML information retrieval combines textual and structural information to perform different information retrieval tasks. In this paper, we propose a new approach exploiting link evidence to re-rank XML retrieval results. Our approach, based on fuzzy logic concepts, combines both content and link evidence for all retrieved XML elements. The combination process generates a new ranked list from the initial returned list. Experiment based on INEX 2007 Wikipedia collection showed improvement of the interpolated precision values.

Software-as-a-service (SaaS) is becoming more important as a software delivery and service model. However, multi-tenancy, which promises to provide a high degree of resource sharing among a large number of tenants (customers or organizations), can significantly complicate SaaS development, deployment, and management due to potential explosion of co-existing tenant-specific variations. Manually configuring those tenant-specific variations for multi-tenant SaaS systems cannot satisfy scalability and flexibility. In this paper, we propose a novel approach in support of multi-tenant SaaS systems using feature modeling and XML filtering techniques. Feature modeling is used to capture functional, non-functional requirements and constraints. The features of a cloud system and tenant-specific requirements are encoded with XPath feature representations and XML document, respectively. We adopt Yfilter, an established XML filtering technique, and tailor it to match cloud configurations that satisfy tenant-specific requirements and constraints. The experimental results demonstrate that our approach can automatically and correctly identify cloud system configurations that match tenant-specific requirements. In addition, the execution time in our approach is only a small fraction compared to the existing approaches (e.g., Fama) and the configuration space is also smaller.

Data plays an important role in today's business activities. In order to share information, data is outsourced occasionally, usually in the form of Extensible Markup Language (XML) files which may contain sensitive information only intended for specific audiences. Securing the data is, as a result, of the utmost importance. Several techniques are used for this purpose, with encryption being the most powerful method. The major disadvantage of using encryption is that it reduces the performance of those queries which perform operations on encrypted data. In this paper we propose a technique that significantly improves the performance of range XQuery on encrypted XML data. Results show that the proposed technique is more efficient than the state-of-the-art technique.

This paper presents a REST service composition framework based on functional programming with monads. It is motivated by the acute needs for dynamism and compos ability in concurrent control of large number of REST resources, especially in the areas of Cloud computing, software-defined networking (SDN), and Internet-of-Things/Web-of-Things. Dynamism gives us the ability to write a REST service composition program to invoke REST services whose identifications and operations are unknown at the design time, and compos ability gives us the ability to combine existing programs for different purposes. The key idea of our approach is to treat the primitives of a composition program, including resource identifications, operations, and control structures, as unknown functions and monads that can be dynamically composed from known functions and monads. We present the algebraic operators and rules that govern the compositions and its translation to XML, to combine the modularity and flexibility of functional programming with the portability and extensibility of XML. A prototype composition engine has been implemented and used to compose REST services in the Cloud computing domain. The initial experimental results indicate that the approach is feasible and promising.

Classical XML keyword search based on the Lowest Common Ancestor (LCA) framework requires users to be well versed with data and semantic relationships between the query keywords to extract meaningful response, restricting its applicability. GKS (Generic Keyword Search), on the other hand, allows users to browse and navigate XML data without such constraints. GKS enables discovery of deeper insights (DI) in the XML data, found in the context of the search results. Such insights not only expose patterns hidden in the search results but also help users tune their queries, thus enabling the navigation of complex XML repositories with ease. We further show how, for a search query, different insights can be discovered from the data by varying a single parameter.

This paper presents an object-based method for indexing recursive structured XML data and process branched queries efficiently. The proposed method is called Object-based Twig Query processing for Recursive data (OTQa#x211C;). It is an extended approach of our existing work in [1] in order to handle recursion in XML data. Our motivation of extending OTQ to OTQa#x211C; is to support many applications that require recursive data structure to be fully functional. OTQa#x211C; is proposed to utilize semantics of XML data to efficiently process branched queries on recursive XML data. The experiments and evaluation are presented to cover variant evaluating points and the efficiency of our approach.

Duplicate Detection is critical task of any database of any organization. Duplicates are nothing but the same real time entities or objects are presented in the form of different structure and in the different formats. We can find out the duplicates in relational data, in complex data and hierarchical data like XML. There are lots of works already presented in the past for finding the duplicates in the relational data. But nowadays there is more focus on finding duplicates in the XML data. Because of XML is very popular for data storing and extensively used for data exchange between the organizations. Here we have done an extensive literature survey on this topic and proposed a duplicate detection method that incorporates some of the existing paper's ideas and some of our original ideas. In addition to improving the efficiency and effectiveness, we also checks for its typographical errors when comparing the two XML elements. To test the correctness of Improved network pruning method, we are comparing it with existing duplicate detection system, and giving more focus on how we get higher precision and recall values in the various datasets we would used.

In this paper, we discuss the one-to-multiple matching problem in leaf-clustering based approximate XML join algorithms and propose a path-sequence based discrimination method to solve this problem. In our method, each path sequence from the top node to the matched leaf in the base and target subtree is extracted, and the most similar target subtree for the base one is determined by the pathsequence based subtree similarity degree. We conduct experiments to evaluate our method by using both real bibliography and bioinformatics XML documents. The experimental results show that our method can effectively decrease the occunence rate of one-to-multiple matching for both bibliography and bioinformatics XML data, and hence improve the precision of the leaf-clustering based approximate XML join algorithms.

XML is the commonly utilized content specification format for data interchange over the Internet. In Publish/Subscribe model, producer is the source for an XML document and disseminates the XML content to the consumer using a mediator called publisher. Producer labels the XML document and defines access control policies for the consumers. Securely labeled XML document are encrypted and sent to the publisher with consumers access details. Encryption is used to provide confidentiality and integrity for XML content dissemination. Consumer queries the publisher for their accessible content. Here, XML label plays a vital role which locates the XML content uniquely. The objective is to design a secure label that has to identify each XML tag uniquely, should not reveal any additional information about the source XML document. Also, XML label size should be optimal with less label generation time. We proposed a secure and efficient XML labeling scheme called Secure Dewey Coding (SDC) that prevents information leak and assures minimal memory space and time. The implementation results of the proposed XML labeling scheme showed that the XML label size has been reduced to a maximum and an average of 68% and 59% respectively and the generation time also decreased significantly.

This paper proposes an extensible programming framework to separate platform-specific optimizations from application codes. The framework allows programmers to define their own code translation rules for special demands of individual systems, compilers, libraries, and applications. Code translation rules associated with user-defined compiler directives are defined in an external file, and the application code is just annotated by the directives. For code transformations based on the rules, the framework exposes the abstract syntax tree (AST) of an application code as an XML document to expert programmers. Hence, the XML document of an AST can be transformed using any XML-based technologies. Our case studies using real applications demonstrate that the framework is effective to separate platform-specific optimizations from application codes, and to incrementally improve the performance of an existing application without messing up the code.

The usage of XML in maintaining data over the web communications has lead to new ways of exploitation which are dangerous for the data integrity yet can be remediated on the basis of the vulnerability classification. The approach is reserved for the research scope of unchangeable dynamic vulnerabilities with the help of WSDL Enumeration and automation script for detection of the vulnerabilities on analysis of the SOAP Request and Response saved in XML Format with different payloads.

To address the issue of reviewing unstructured document format of academic dissertation, this paper proposes a model method for dissertation format review based on XML format node template tree. This method is to convert the Word document of a dissertation to an xml document and then identify the XML tags to extract the document format features and establish a document format node tree. During a document format review, compare the format node tree of the tested document with that of the standard document to detect the error nodes and comment the format errors. To enhance the comparison efficiency, divide the dissertation document format node tree into a number of sub-trees based on the theme. In the comparison algorithm, compare the theme sub-trees in the standard format template with the theme sub-trees of the tested document in terms of structures, nodes and attributes, so as to identify and record the error format nodes and tag the error in the comment algorithm. The method described in this paper achieves automatic format review and comment insertion for academic dissertation. It is a superior method for its high error detection rate, low false detection rate, and simple yet robust extraction rules.

The need for IT skills assessment and certification is indisputable for both persons and institutions. Thus, the recourse to automatic assessment systems able to answer the strong demand of such assessment or certification is inevitable. In this paper, we propose a new approach to automatically assess IT skills in authentic context. This approach relies on the potential of XML format and its related efficient technologies which allow the extraction of information from XML documents. We divide our assessment approach into two steps. In the first, we transform both Students documents and answers model to an intermediate representation using XML format for which some preprocessing is done. In the second step, we extract from the teacher's correct document the required skills as paths of the tree representation of the XML document. In order to assign a mark we measure similarities between these paths and those of the student document. We have conducted an experimental study to validate our approach. Thus, we have developped a tool based on the proposed approach to automatically assess Word Processing skills using Microsoft Office Word program. The evaluation of our tool is performed on a real exam with one hundred students. The results show the accuracy and the suitability of this solution for assessing IT skills.

Rapid development of XML technology over the World Wide Web has motivated the need for query optimization especially in a dynamic environment. As such, a good XML labeling scheme to ensure fast query processing is crucial. Although many labeling schemes were proposed in the past, only few support structural relationship efficiently. Therefore, in this paper, we propose a novel XML labeling scheme that helps quick determination of structural relationship among XML nodes and supports dynamic updates without relabeling nodes in case of update occurrences.

Big data in XML format poses a challenge to distributed data systems. This paper proposes an open Hive schema approach to XML data placement in Hadoop. Placing XML data in Hive with this generic schema to build column-oriented and OLAP-focused XML data warehouse of heterogeneous content has benefits for data access, maintenance and scalability.