43,381 research outputs found

    Application of Developers' and Users' Dependent Factors in App Store Optimization

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    This paper presents an application of developers' and users' dependent factors in the app store optimization. The application is based on two main fields: developers' dependent factors and users' dependent factors. Developers' dependent factors are identified as: developer name, app name, subtitle, genre, short description, long description, content rating, system requirements, page url, last update, what's new and price. Users' dependent factors are identified as: download volume, average rating, rating volume and reviews. The proposed application in its final form is modelled after mining sample data from two leading app stores: Google Play and Apple App Store. Results from analyzing collected data show that developer dependent elements can be better optimized. Names and descriptions of mobile apps are not fully utilized. In Google Play there is one significant correlation between download volume and number of reviews, whereas in App Store there is no significant correlation between factors

    Business Process Retrieval Based on Behavioral Semantics

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    This paper develops a framework for retrieving business processes considering search requirements based on behavioral semantics properties; it presents a framework called "BeMantics" for retrieving business processes based on structural, linguistics, and behavioral semantics properties. The relevance of the framework is evaluated retrieving business processes from a repository, and collecting a set of relevant business processes manually issued by human judges. The "BeMantics" framework scored high precision values (0.717) but low recall values (0.558), which implies that even when the framework avoided false negatives, it prone to false positives. The highest pre- cision value was scored in the linguistic criterion showing that using semantic inference in the tasks comparison allowed to reduce around 23.6 % the number of false positives. Using semantic inference to compare tasks of business processes can improve the precision; but if the ontologies are from narrow and specific domains, they limit the semantic expressiveness obtained with ontologies from more general domains. Regarding the perform- ance, it can be improved by using a filter phase which indexes business processes taking into account behavioral semantics propertie

    Experiences and opportunities in teaching ukrainian students at the faculty of mining and geoengineering in AGH University of Science and Technology

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    The paper presents the influence of various factors on the process of internationalisation of higher education in Poland, and particularly in AGH University of Science and Technology from the perspective of the Faculty of Mining and Geoengineering. It lays out educational opportunities for learners at mining and geology study courses, and the benefits stemming therefrom for international students, including students from Ukraine. Possibilities of academic exchange were discussed and that of international cooperation, in particular with Ukraine, in order to support the potential of science and higher education in both countries. Lastly, factors were indicated in favour of taking education with AGH

    Pragmatic Ontology Evolution: Reconciling User Requirements and Application Performance

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    Increasingly, organizations are adopting ontologies to describe their large catalogues of items. These ontologies need to evolve regularly in response to changes in the domain and the emergence of new requirements. An important step of this process is the selection of candidate concepts to include in the new version of the ontology. This operation needs to take into account a variety of factors and in particular reconcile user requirements and application performance. Current ontology evolution methods focus either on ranking concepts according to their relevance or on preserving compatibility with existing applications. However, they do not take in consideration the impact of the ontology evolution process on the performance of computational tasks – e.g., in this work we focus on instance tagging, similarity computation, generation of recommendations, and data clustering. In this paper, we propose the Pragmatic Ontology Evolution (POE) framework, a novel approach for selecting from a group of candidates a set of concepts able to produce a new version of a given ontology that i) is consistent with the a set of user requirements (e.g., max number of concepts in the ontology), ii) is parametrised with respect to a number of dimensions (e.g., topological considerations), and iii) effectively supports relevant computational tasks. Our approach also supports users in navigating the space of possible solutions by showing how certain choices, such as limiting the number of concepts or privileging trendy concepts rather than historical ones, would reflect on the application performance. An evaluation of POE on the real-world scenario of the evolving Springer Nature taxonomy for editorial classification yielded excellent results, demonstrating a significant improvement over alternative approaches

    Automation of the longwall mining system

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    Cost effective, safe, and technologically sound applications of automation technology to underground coal mining were identified. The longwall analysis commenced with a general search for government and industry experience of mining automation technology. A brief industry survey was conducted to identify longwall operational, safety, and design problems. The prime automation candidates resulting from the industry experience and survey were: (1) the shearer operation, (2) shield and conveyor pan line advance, (3) a management information system to allow improved mine logistics support, and (4) component fault isolation and diagnostics to reduce untimely maintenance delays. A system network analysis indicated that a 40% improvement in productivity was feasible if system delays associated with all of the above four areas were removed. A technology assessment and conceptual system design of each of the four automation candidate areas showed that state of the art digital computer, servomechanism, and actuator technologies could be applied to automate the longwall system

    Defining and identifying the knowledge economy in Scotland: a regional perspective on a global phenomenon

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    The development and growth of a knowledge economy has become a key policy aim forgovernments in all advanced economies. This is based on recognition that technologicalchange, the swift growth of global communications, and the ease of mobility of capital across national borders has dramatically changed the patterns of international trade and investment. The economic fate of individual nations is now inseparably integrated into the ebb and flow of the global economy. When companies can quickly move capital to those geographical locations which offer the best return, a country's long term prosperity is now heavily dependent on its abilityto retain the essential factors of production that are least mobile. This has led to apremium being placed on the knowledge and skills embodied in a country's labourforce, as it has become a widely accepted view that a country which possesses a high level of knowledge and skills in its workforce will have a competitive advantage overothers with a lower domestic skill base. Knowledge and skills are thought to be thebasis for the development of a knowledge economy
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