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Semi‐structured data are commonly represented by labeled flat db‐graphs. In this paper, we study an extension of db‐graph model for representing nested semi‐structured data. This extension allows one to have db‐graphs whose vertex labels are db‐graphs themselves. Bringing the data model closer to the natural presentation of data stored via Web documents is the main motivation behind nesting db‐graphs. The importance of nested db‐graphs is similar to the importance of nested tables in relational model. The main purpose of the paper is to provide a mechanism to query nested semi‐structured data and Web forms in a uniform way. Most of the languages proposed so far have been designed as extensions of SQL with, among others, the advantage to provide a user‐friendly syntax and commercial flavor. The major focus of the paper is on defining a graph query language in a multi‐sorted calculus like style.

eXtensible Markup Language (XML) data are data which are not necessarily constrained by a schema, XML is fast emerging as a standard for data representation and exchange on the world wide web, the ability to intelligently query XML data becomes increasingly important. Some XML graphical query languages for XML data have been proposed but they are either too complex or too limited in the power of expression and in their use. The purpose of this paper is to propose a recursive graphical query language for querying and restructuring XML data (RGQLX). The expressive power of RGQLX is comparable to Fixpoint. RGQLX language is a multi‐sorted graphical language integrating grouping, aggregate functions, nested queries and recursion.

The methodology emphasizes on RGQLX's development which is base of G‐XML data model syntax to express a wide variety of XML queries, ranging from simple selection, to expressive data transformations involving grouping, aggregation and sorting. RGQLX allows users to express recursive visual queries in an elegant manner. RGQLX has an operational semantics based on the annotated XML, which serves to express queries and data trees in form of XML. The paper presents an algorithm to achieve the matching between data and query trees after translating a query tree into annotated XML.

Developed and demonstrated were: a G‐XML model; recursive queries; annotated XML for the semantic operations and a matching algorithm.

The future research work on RGQLX language will be expanding it to include recursive aggregations.

The algorithms/approaches proposed can be easily integrated in any commercial product to enhance the performance of XML query languages.

The proposed work integrates various novel techniques for XML query syntax/semantic into a single language with a suitable matching algorithm. The power of this proposal is in the class of Fixpoint queries.

GraphQL is a new Open API specification that allows clients to send queries and obtain data flexibly according to their needs. However, a high-complexity GraphQL query may lead to an excessive data volume of the query result, which causes problems such as resource overload of the API server. Therefore, this paper aims to address this issue by predicting the response data volume of a GraphQL query statement.

This paper proposes a GraphQL response data volume prediction approach based on Code2Vec and AutoML. First, a GraphQL query statement is transformed into a path collection of an abstract syntax tree based on the idea of Code2Vec, and then the query is aggregated into a vector with the fixed length. Finally, the response result data volume is predicted by a fully connected neural network. To further improve the prediction accuracy, the prediction results of embedded features are combined with the field features and summary features of the query statement to predict the final response data volume by the AutoML model.

Experiments on two public GraphQL API data sets, GitHub and Yelp, show that the accuracy of the proposed approach is 15.85% and 50.31% higher than existing GraphQL response volume prediction approaches based on machine learning techniques, respectively.

This paper proposes an approach that combines Code2Vec and AutoML for GraphQL query response data volume prediction with higher accuracy.

With the rapid spread of smartphones and tablets, it is becoming necessary for web developers to create responsive web pages which are visually appealing on devices of various sizes. However, building responsive UIs is a very challenging task, requiring deep knowledge of HTML and CSS. This paper aims to propose an approach to generate responsive web pages using SuperSQL, which is an extension of SQL that can format data retrieved from a database into various kinds of structured documents.

By incorporating the methodology of bootstrap, a grid-based framework for front-end development, the authors have made it possible to create responsive web pages from simple SuperSQL queries. In addition, by utilizing SuperSQL’s unique feature that can describe the structure of the output web page, the authors have proposed and implemented a mechanism to automatically optimize the web content’s size and position.

In the evaluation, the authors created some actual web applications with and without the use of SuperSQL and compared the code amount (number of lines). As a result, when using the proposed system, the amount of code was reduced to about 1/5. The authors also compared the layout generated by the proposed automatic layout generation mechanism with the responsive layout that was generated manually. As a result, the automatic layout generation mechanism created the same layout as the manually created layout 74.8 per cent of the time, and the user satisfaction level turned out to be 85.8 per cent.

The way to generate a responsive HTML by using a single SuperSQL query, and the mechanism for automatic responsive layout generation.

This paper discusses some particularly desirable features of the user‐computer dialogue involved in query formulation in an on‐line information retrieval system. The methods used in the Culham RIOT II system, designed to give on‐line access to a data base of 25, 000–50, 000 references, are described. To facilitate query formulation a matrix technique is employed and the most recent titles may be displayed while the query statement is under construction and before a full search is requested.

The rapid development of Extensible Markup Language (XML) from a mere data exchange format to a universal syntax for encoding domain specific information increases the need of new query languages specifically visualized to address the characteristics of XML. Such languages should be able not only to extract information from XML documents, but also to apply powerful restructuring operators, based on a well‐defined semantics. Moreover, XML queries should be natural to write and understand, as also end‐users are expected to access the large XML information bases supporting their businesses. The purpose of this paper is to propose a new graphical query language for XML (GQLX) for querying and restructuring XML data.

The methodology emphasizes on GQLX's development, which is based on G‐XML data model syntax to express a wide variety of XML queries, ranging from simple selection to expressive data transformations involving grouping, aggregation and sorting. GQLX has an operational semantics based on the annotated XML, which serves to express queries and data trees in the form of XML. The paper also presents an algorithm to achieve the matching between data and query trees after translating them into annotated XML.

Developed and demonstrated were: a G‐XML syntax; annotated XML for the semantic operations and a matching algorithm.

The future research work on this language lies in expanding it to include recursion and nested queries.

The algorithms/approaches proposed can be implemented to enhance the performance of the XML query language.

The proposed work integrates various novel techniques for XML query syntax/semantic into a single language with a suitable matching algorithm.

Estimating the sizes of query results and intermediate results is crucial to many aspects of query processing. All database systems rely on the use of cardinality estimates to choose the cheapest execution plan. In principle, the problem of cardinality estimation is more complicated in the Extensible Markup Language (XML) domain than the relational domain. The purpose of this paper is to present a novel framework for estimating the cardinality of XQuery expressions as well as their sub‐expressions. Additionally, this paper proposes a novel XQuery cardinality estimation benchmark. The main aim of this benchmark is to establish the basis of comparison between the different estimation approaches in the XQuery domain.

As a major innovation, the paper exploits the relational algebraic infrastructure to provide accurate estimation in the context of XML and XQuery domains. In the proposed framework, XQuery expressions are translated into an equivalent relational algebraic plans and then using a well defined set of inference rules and a set of special properties of the algebraic plan, this framework is able to provide high‐accurate estimation for XQuery expressions.

This paper is believed to be the first which provides a uniform framework to estimate the cardinality of more powerful XML querying capabilities using XQuery expressions as well as their sub‐expressions. It exploits the relational algebraic infrastructure to provide accurate estimation in the context of XML and XQuery domains. Moreover, the proposed framework can act as a meta‐model through its ability to incorporate different summarized XML structures and different histogram techniques which allows the model designers to achieve their targets by focusing their effort on designing or selecting the adequate techniques for them. In addition, this paper proposes benchmark for XQuery cardinality estimation systems. The proposed benchmark distinguishes itself from the other existing XML benchmarks in its focus on establishing the basis for comparing the different estimation approaches in the XML domain in terms of their accuracy of the estimations and their completeness in handling different XML querying features.

The current status of this proposed XQuery cardinality estimations framework does not support the estimation of the queries over the order information of the source XML documents and does not support non‐numeric predicates.

The experiments of this XQuery cardinality estimation system demonstrate its effectiveness and show high‐accurate estimation results. Utilizing the cardinality estimation properties during the SQL translation of XQuery expression results in an average improvement of 20 percent on the performance of their execution times.

This paper presents a novel framework for estimating the cardinality of XQuery expressions as well as its sub‐expressions. A novel XQuery cardinality estimation benchmark is introduced to establish the basis of comparison between the different estimation approaches in the XQuery domain.

This article presents a novel user‐oriented interface for generalised informetric analysis and demonstrates how informetric calculations can easily and declaratively be specified through advanced data modelling techniques. The interface is declarative and at a high level. Therefore it is easy to use, flexible and extensible. It enables end users to perform basic informetric ad hoc calculations easily and often with much less effort than in contemporary online retrieval systems. It also provides several fruitful generalisations of typical informetric measurements like impact factors. These are based on substituting traditional foci of analysis, for instance journals, by other object types, such as authors, organisations or countries. In the interface, bibliographic data are modelled as complex objects (non‐first normal form relations) and terminological and citation networks involving transitive relationships are modelled as binary relations for deductive processing. The interface is flexible, because it makes it easy to switch focus between various object types for informetric calculations, e.g. from authors to institutions. Moreover, it is demonstrated that all informetric data can easily be broken down by criteria that foster advanced analysis, e.g. by years or content‐bearing attributes. Such modelling allows flexible data aggregation along many dimensions. These salient features emerge from the query interface‘s general data restructuring and aggregation capabilities combined with transitive processing capabilities. The features are illustrated by means of sample queries and results in the article.

The aims of this study were to identify the retrieval features for online databases; difficulties faced by users; and retrieval features expected by users. A total of 25 databases were surveyed and 40 users were interviewed after the training sessions. Common retrieval features included Boolean operators, phrase searching, match of exact words or phrases, field specific and limit fields searches, truncation, and wildcard. Even though features are offered in many systems, their interpretation and implementation are different. Unique features included lateral searching, density and frequency of terms, reference link, and searching via table of content. The expected features included relevance feedback and term weighting other than those already offered by ACM Digital Library and IEEE Xplore. Such expectations were influenced by the users' background in ICT. Difficulties included application of the retrieval features in searching. Database providers must include the expected features, synonyms linked to terms in the thesaurus, and extensive search examples.

The current literature on the educational progress of immigrant students within the host system is encapsulated in the thesis that these students will face difficulties, and that these difficulties will more often than not lead to a failure to meet the demands of the system for the majority of the immigrant students. An apposite comment by Portes (1996), queried whether the children of immigrants would be able to work their way upwards into “…the middle-class mainstream” or whether they would be blocked in this ascent based on their migrant status, and become part of an “multiethnic underclass or join an expanded multiethnic underclass.” Súarez-Orozco and Súarez-Orozco (1995, 2000) completed this perception by uncovering the implicit viewpoint within which this query was nested. He foregrounded the domination of sensationalism and myth in discussions of the “natural process” of assimilation of minorities. Finally, current discussion on the issue of these so-called at-risk students centres on how they can be made successful at school.