Universal Query Research Articles

Query-driven Qualitative Constraint Acquisition

Many planning, scheduling or multi-dimensional packing problems involve the design of subtle logical combinations of temporal or spatial constraints. Recently, we introduced GEQCA-I, which stands for Generic Qualitative Constraint Acquisition, as a new active constraint acquisition method for learning qualitative constraints using qualitative queries. In this paper, we revise and extend GEQCA-I to GEQCA-II with a new type of query, universal query, for qualitative constraint acquisition, with a deeper query-driven acquisition algorithm. Our extended experimental evaluation shows the efficiency and usefulness of the concept of universal query in learning randomly-generated qualitative networks, including both temporal networks based on Allen’s algebra and spatial networks based on region connection calculus. We also show the effectiveness of GEQCA-II in learning the qualitative part of real scheduling problems.

GIG economy and sustainable development: bibliometric analysis and identification of future research directions

Purpose: The aim of this article is to identify the most common fields of study undertaken by researchers in scientific papers covering simultaneously the gig economy and sustainable development. Design/methodology/approach: The research study used a structured literature review method. The structured bibliometric query Q1 allowed for the exploration of the Scopus database. As a result, 48 scientific studies from the period 2017-2023 were selected for analysis, which simultaneously addressed the issues of the gig economy and sustainable development. Findings: The analyses carried out showed that the issue of sustainable development is addressed in the context of the gig economy. This is a relatively new research area, as shown, for example, by the generated database of studies used for the bibliometric analyses conducted. The issues of sharing economy and decent work are important areas addressed in the context of the gig economy. It was noticed that there was a lack of author keywords covering 'green' issues. Research limitations/implications: Research results based on other databases (e.g. Web of Science) may lead to different results. It should be noted that the different bibliometric databases do not overlap, which is related to the indexing of scientific journals or publications in the databases. Nonetheless, a universal query was used in the study, which can be used in the various bibliometric databases once it has been adapted to their respective query form. In addition, the various databases are constantly being supplemented with new scientific papers, which also depends on the publishing process. Hence, the content of the Q1 query can in future be used for comparison purposes with the results obtained, or to compare different bibliometric databases with each other. Originality/value: In the discussion that followed, attention was drawn to the issues of green jobs and green self-employment. In the authors' opinion, such research directions, although not yet visible in the authors' keywords, will be developed soon in the context of studies covering the issues of the gig economy and sustainable development considering the green transformation of the economy taking place. This article is addressed to all those who are interested in the issues of the gig economy and sustainable development. Keywords: gig economy, green jobs, green labor market, green self-employment, sustainable development. Category of the paper: Literature review.

Universal Query Language for Unified State Model

Unified State Model USM is a single data model that allows conveying objects of major programming languages and databases. USM exploits and emphasizes common properties of their data models. USM is equipped with mappings from these data models onto it. With USM at hand, we have faced the next natural research question whether numerous query languages for the data subsumed by USM can be clearly mapped onto a common language. We have designed and proposed such a language called the Unified Query Language UQL. UQL is intended to be a minimalistic and elegant query language that allows expressing queries of languages of data models covered by USM. In this paper we define UQL and its concise set of operators. Next we conduct a mild introduction into UQL features by showing examples of SQL and ODMG OQL queries and their mapping onto UQL. We conclude by presenting the mapping of the theoretical foundations of these two major query languages onto UQL. They are the multiset relational algebra and the object query algebra. This is an important step towards the establishment of a fully-fledged common query language for USM and its subsumed data models.

Universal Query Language for Unified State Model

Unified State Model USM is a single data model that allows conveying objects of major programming languages and databases. USM exploits and emphasizes common properties of their data models. USM is...

Information Retrieval from Deep Web Based on Visual Query Interpretation

Deep Web is growing rapidly. More than 90% of relevant information in web comes from deep Web. Users are usually interested by products which satisfy their needs at the best prices and quality of service .Hence, user’s needs concerns not only one service but many competitive services at the same time. However, for commercial reasons, there is no way to compare all web services products. Each web service is a black box which accepts queries through its own query interface and returns results. As consequence, users ask separately different web services and spend a lot of time comparing products in order to find the best one. This is a burden for novice users. In this paper, the authors propose a new approach which integrates query interfaces of many web services into one universal web service. The new interface describes visually the universal query and is used to ask many web services at the same time. The authors have evaluated their approach on standard datasets and have proved good performances.

Architecture for Knowledge-Based and Federated Search of Online Clinical Evidence

BackgroundIt is increasingly difficult for clinicians to keep up-to-date with the rapidly growing biomedical literature. Online evidence retrieval methods are now seen as a core tool to support evidence-based health practice. However, standard search engine technology is not designed to manage the many different types of evidence sources that are available or to handle the very different information needs of various clinical groups, who often work in widely different settings.ObjectivesThe objectives of this paper are (1) to describe the design considerations and system architecture of a wrapper-mediator approach to federate search system design, including the use of knowledge-based, meta-search filters, and (2) to analyze the implications of system design choices on performance measurements.MethodsA trial was performed to evaluate the technical performance of a federated evidence retrieval system, which provided access to eight distinct online resources, including e-journals, PubMed, and electronic guidelines. The Quick Clinical system architecture utilized a universal query language to reformulate queries internally and utilized meta-search filters to optimize search strategies across resources. We recruited 227 family physicians from across Australia who used the system to retrieve evidence in a routine clinical setting over a 4-week period. The total search time for a query was recorded, along with the duration of individual queries sent to different online resources.ResultsClinicians performed 1662 searches over the trial. The average search duration was 4.9 ± 3.2 s (N = 1662 searches). Mean search duration to the individual sources was between 0.05 s and 4.55 s. Average system time (ie, system overhead) was 0.12 s.ConclusionsThe relatively small system overhead compared to the average time it takes to perform a search for an individual source shows that the system achieves a good trade-off between performance and reliability. Furthermore, despite the additional effort required to incorporate the capabilities of each individual source (to improve the quality of search results), system maintenance requires only a small additional overhead.

Optimizing universal queries in relational databases

AbstractIn a relational database system based on the universal relation interface, users do not have to specify access paths when constructing universal queries. Moreover, users cannot control how to evaluate the queries efficiently (though they can construct usual queries, such as relational algebraic expressions, considering their processing costs). Thus, it is important for the system to evaluate given universal queries efficiently. This paper considers the representative instance of a database as a universal relation, and presents an optimization algorithm for evaluating a universal query for computing specified components of the tuples in the universal relation which satisfies a specified condition.