Computing Classification System Research Articles

Aggregate Functions in Categorical Data Skyline Search (CDSS) for Multi-keyword Document Search

Literature review is the first step in starting research for a deep understanding of the research interest. However, finding literature relevant to research interests is difficult and takes time. Skyline query is a method that can be used for filtering. An object p is said to dominate object q if p equals q on all of its attributes, and p is at least better than q on one attribute. Categorical Data Skyline Search (CDSS) is an algorithm that can filter skyline objects in categorical data types such as documents. CDSS uses Extended Distance Wu and Palmer (DEWP) to calculate the distance between the user query and document keywords. The document keywords and user queries are represented as nodes in the ACM CCS ontology, and documents are assumed to be represented by a single keyword. This study aims to use the CDSS algorithm to search for skyline documents represented by more than one keyword by adding an aggregate function (average, minimum, maximum) to the CDSS algorithm, especially in calculating DEWP. This study used the thesis documents from the IPB University computer science department. Document keywords will be extracted using the Term Frequency-Inverse Term Frequency (TF-IDF) method. The collected keywords will be mapped in a mixed ontology tree that refers to the Association of Computing Machinery Computing Classification System 2012 (ACM CCS 2012) and Computer Science Ontology (CSO) as ontology standards in computer science. The skyline query algorithm for determining skyline documents is Block Nested Loop (BNL). The evaluation method uses the skyline ratio of each aggregate function in the CDSS. Based on the ratio value, CDSS using the maximum DEWP has the most relevant skyline results compared to the average DEWP and minimum DEWP.

A parametric similarity method: Comparative experiments based on semantically annotated large datasets

We present the parametric method SemSimp aimed at measuring semantic similarity of digital resources. SemSimp is based on the notion of information content, and it leverages a reference ontology and taxonomic reasoning, encompassing different approaches for weighting the concepts of the ontology. In particular, weights can be computed by considering either the available digital resources or the structure of the reference ontology of a given domain. SemSimp is assessed against six representative semantic similarity methods for comparing sets of concepts proposed in the literature, by carrying out an experimentation that includes both a statistical analysis and an expert judgment evaluation. To the purpose of achieving a reliable assessment, we used a real-world large dataset based on the Digital Library of the Association for Computing Machinery (ACM), and a reference ontology derived from the ACM Computing Classification System (ACM-CCS). For each method, we considered two indicators. The first concerns the degree of confidence to identify the similarity among the papers belonging to some special issues selected from the ACM Transactions on Information Systems journal, the second the Pearson correlation with human judgment. The results reveal that one of the configurations of SemSimp outperforms the other assessed methods. An additional experiment performed in the domain of physics shows that, in general, SemSimp provides better results than the other similarity methods.

Software Engineering Education Knowledge Versus Industrial Needs

Contribution: Determine and analyze the gap between software practitioners' education outlined in the 2014IEEE/ACM Software Engineering Education Knowledge (SEEK) and industrial needs pointed by Wikipedia articles referenced in Stack Overflow (SO) posts. Background: Previous work has uncovered deficiencies in the coverage of computer fundamentals, people skills, software processes, and human-computer interaction, suggesting rebalancing. Research Questions: 1) To what extent are developers' needs, in terms of Wikipedia articles referenced in SO posts, covered by the SEEK knowledge units? 2) How does the popularity of Wikipedia articles relate to their SEEK coverage? 3) What areas of computing knowledge can be better covered by the SEEK knowledge units? 4) Why are Wikipedia articles covered by the SEEK knowledge units cited on SO? Methodology: Wikipedia articles were systematically collected from SO posts. The most cited were manually mapped to the SEEK knowledge units, assessed according to their degree of coverage. Articles insufficiently covered by the SEEK were classified by hand using the 2012 ACM Computing Classification System. A sample of posts referencing sufficiently covered articles was manually analyzed. A survey was conducted on software practitioners to validate the study findings. Findings: SEEK appears to cover sufficiently computer science fundamentals, software design and mathematical concepts, but less so areas like the World Wide Web, software engineering components, and computer graphics. Developers seek advice, best practices and explanations about software topics, and code review assistance. Future SEEK models and the computing education could dive deeper in information systems, design, testing, security, and soft skills.

Twenty-five Years of Journal of Universal Computer Science: A Bibliometric Overview

The Journal of Universal Computer Science is a monthly peer-reviewed open-access scientific journal covering all aspects of computer science, launched in 1994, so becoming twenty-five years old in 2019. In order to celebrate its anniversary, this study presents a bibliometric overview of the leading publication and citation trends occurring in the journal. The aim of the work is to identify the most relevant authors, institutions, countries, and analyze their evolution through time. The article uses the Web of Science Core Collection citations and the ACM Computing Classification System in order to search for the bibliographic information. Our study also develops a graphical mapping of the bibliometric material by using the visualization of similarities (VOS) viewer. With this software, the work analyzes bibliographic coupling, citation and co-citation analysis, co-authorship, and co-occurrence of keywords. The results underline the significant growth of the journal through time and its international diversity having publications from countries all over the world and covering a wide range of categories which confirms the “universal” character of the journal.

Knowledge base enrichment by relation learning from social tagging data

There has been considerable interest in transforming unstructured social tagging data into structured knowledge for semantic-based retrieval and recommendation. Research in this line mostly exploits data co-occurrence and often overlooks the complex and ambiguous meanings of tags. Furthermore, there have been few comprehensive evaluation studies regarding the quality of the discovered knowledge. We propose a supervised learning method to discover subsumption relations from tags. The key to this method is quantifying the probabilistic association among tags to better characterise their relations. We further develop an algorithm to organise tags into hierarchies based on the learned relations. Experiments were conducted using a large, publicly available dataset, Bibsonomy, and three popular, human-engineered or data-driven knowledge bases: DBpedia, Microsoft Concept Graph, and ACM Computing Classification System. We performed a comprehensive evaluation using different strategies: relation-level, ontology-level, and knowledge base enrichment based evaluation. The results clearly show that the proposed method can extract knowledge of better quality than the existing methods against the gold standard knowledge bases. The proposed approach can also enrich knowledge bases with new subsumption relations, having the potential to significantly reduce time and human effort for knowledge base maintenance and ontology evolution.

Extracting scientific trends by mining topics from Call for Papers

PurposeThe purpose of this paper is to present a novel approach for mining scientific trends using topics from Call for Papers (CFP). The work contributes a valuable input for researchers, academics, funding institutes and research administration departments by sharing the trends to set directions of research path.Design/methodology/approachThe authors procure an innovative CFP data set to analyse scientific evolution and prestige of conferences that set scientific trends using scientific publications indexed in DBLP. Using the Field of Research code 804 from Australian Research Council, the authors identify 146 conferences (from 2006 to 2015) into different thematic areas by matching the terms extracted from publication titles with the Association for Computing Machinery Computing Classification System. Furthermore, the authors enrich the vocabulary of terms from the WordNet dictionary and Growbag data set. To measure the significance of terms, the authors adopt the following weighting schemas: probabilistic, gram, relative, accumulative and hierarchal.FindingsThe results indicate the rise of “big data analytics” from CFP topics in the last few years. Whereas the topics related to “privacy and security” show an exponential increase, the topics related to “semantic web” show a downfall in recent years. While analysing publication output in DBLP that matches CFP indexed in ERA Core A* to C rank conference, the authors identified that A* and A tier conferences not merely set publication trends, since B or C tier conferences target similar CFP.Originality/valueOverall, the analyses presented in this research are prolific for the scientific community and research administrators to study research trends and better data management of digital libraries pertaining to the scientific literature.

Parsimonious generalization of fuzzy thematic sets in taxonomies applied to the analysis of tendencies of research in data science

This paper proposes a novel method, referred to as ParGenFS, for finding a most specific generalization of a query set represented by a fuzzy set of topics assigned to leaves of the rooted tree of a taxonomy. The query set is generalized by “lifting” it to one or more “head subjects” in the higher ranks of the taxonomy. The head subjects should cover the query set, with the possible addition of some “gaps”, taxonomy nodes covered by the head subject but irrelevant to the query set. To decrease the numbers of gaps, we admit some “offshoots”, nodes belonging to the query set but not covered by a head subject. The method globally minimizes the total number of head subjects, gaps and offshoots, each suitably weighted. Our algorithm is applied to the structural analysis and description of a collection of 17,685 abstracts of research papers published in 17 Springer journals related to Data Science for the 20-year period 1998–2017. Our taxonomy of Data Science (TDS) is extracted from the Association for Computing Machinery Computing Classification System 2012 (ACM-CCS), a six-level hierarchical taxonomy manually developed by a team of ACM experts. The TDS also includes a number of additional leaves that we added to cater for recent developments not represented in the ACM-CCS taxonomy. We find fuzzy clusters of leaf topics over the text collection, using specially developed machinery. Three of the clusters are indeed thematic, relating to the Data Science sub-areas of (a) learning, (b) information retrieval, and (c) clustering. These three clusters are then lifted in the TDS using ParGenFS, which allows us to draw some conclusions about tendencies in developments in these areas.

A Systematic Mapping of Translation-Enabling Technologies for Sign Languages

Sign languages (SL) are the first language for most deaf people. Consequently, bidirectional communication among deaf and non-deaf people has always been a challenging issue. Sign language usage has increased due to inclusion policies and general public agreement, which must then become evident in information technologies, in the many facets that comprise sign language understanding and its computational treatment. In this study, we conduct a thorough systematic mapping of translation-enabling technologies for sign languages. This mapping has considered the most recommended guidelines for systematic reviews, i.e., those pertaining software engineering, since there is a need to account for interdisciplinary areas of accessibility, human computer interaction, natural language processing, and education, all of them part of ACM (Association for Computing Machinery) computing classification system directly related to software engineering. An ongoing development of a software tool called SYMPLE (SYstematic Mapping and Parallel Loading Engine) facilitated the querying and construction of a base set of candidate studies. A great diversity of topics has been studied over the last 25 years or so, but this systematic mapping allows for comfortable visualization of predominant areas, venues, top authors, and different measures of concentration and dispersion. The systematic review clearly shows a large number of classifications and subclassifications interspersed over time. This is an area of study in which there is much interest, with a basically steady level of scientific publications over the last decade, concentrated mainly in the European continent. The publications by country, nevertheless, usually favor their local sign language.

Design and Development of Metadata Editors: Datacentric and a User-centric Approaches

This paper presents the design and the development of two metadata editors for the RAGE project. The work is based on two conceptually different approaches. One of the editors follows a data-centric approach, while the other follows a user-centric one. Discussed are the design challenges, the internal structure and a comparison of both metadata editors.ACM Computing Classification System (1998): H.5.2, H.3.5, J.1, D.2.8.

Towards Automatic Generation of Serious Maze Games for Education

Serious games based on video mazes can be easily and effectively applied for learning purposes with the goal of facilitating technology-enhanced education. In order to practice game-based learning for various curriculums, educators need software platforms for automatized construction and flexible customization of such games. This article presents an open software platform named Maze Builder built on Unity 3D, which is especially designed for automatic generation and easy modification of maze video games. We discuss the maze game design process, the platform architecture and its data model, the results obtained from the performance tests, and a practical experiment conducted with teachers using the platform for generating maze games with educational tasks embedded into maze rooms. The initial results acquired from these experiments are very positive and encouraging with regard of the usability of the Maze Builder platform by domain specialists who are not IT professionals.ACM Computing Classification System (1998): D.2.6, D.2.10, K.8.0.

Semantic-oriented Architectures and Use of Ontology for Organizing Adaptive Search in Digital Libraries

Over time, the number of knowledge systems is growing and gaining popularity in various fields such as business, science, training, and etc. Their use has been particularly beneficial for the learning process. The use of a digital library is growing over time because the information stored and delivered is reliable, structured and ready to use. Learners not always have necessary knowledge and skills to search for information in a digital library, as their experience in the information space is limited. This necessitates the development of functionalities that facilitate the process of search in a digital library, like semantic-based search, multi-criteria search, contextual search, adaptive search, and etc. The article presents the architecture of a Functional Module for Adaptive Search in a digital library and its main components. The basic scheme of adaptive and customizable logic is also presented. The article ends with directions for future development of the architecture.ACM Computing Classification System (1998): H.3.7, K.3.1.

Supporting European Energy Consumers through Gamification and Competence-based Learning

The European energy market liberalization strategy aims to assign a new role to consumers and end-users’ communities so that they can become active participants on the energy market. In this paper we present the project SOCIALENERGY, EU-funded under the H2020 program. This project aims to promote the EU energy market transformation policy and to deliver supporting instruments. By developing innovative ICT-based tools, the project consortium will empower the EU energy consumers to become more energy efficient and competent. Apart from presenting the advanced features of SOCIALENERGY multi-modular platform, we will highlight the importance of the novel competence-based education (CBE) framework to support educational activities and to promote creation of social communities in the energy efficiency domain.ACM Computing Classification System (1998): J.1, K.3.1, K.4.3, K.5.2.

Review of Policy Envisions and Requirements for STEM Teachers in Bulgaria

The article precents a review of the normative framework in Bulgaria related to the development of STEM teachers’ competences. It studies explicitly defined requirements: pedagogical, academic, administrative and communicative competences, as well as implicitly defined ones, integrated in National Educational Standards and students’ curricula: research, team work, ICT, work on a project, management of inquiry-based learning, etc. The authors identify dimensions and aspects of STEM teachers’ competences, set out the major issues for consideration in providing teachers’ training, and formulate six Key messages to providers of STEM teachers’ trainings and policy makers, related to forms, content, approaches and responsibilities of institutions.The goal of the research is for the results to be used in European computer-assisted blended learning teacher trainings. They provide requirements to the training design as well as to the software platforms for implementations of trainings.ACM Computing Classification System (1998): K.3.1.

How to Account for the Uncertainty in The QoS Selection Task

The paper presents an approach to QoS selection of webservices. It introduces a theoretical frame and respective applicableselection procedures, in which the solution accounts for the uncertainty ofthe existing metrics data and client preference. Methods of two generalcases are revealed in detail. The first method considers a selection basedon one service quality. The second method assesses the integrated QoS ofinteresting properties. The theoretical analysis is validated throughexperimental investigation of real data of services’ quality metrics.ACM Computing Classification System (1998): H.3.7, K.3.1.* The author acknowledges the financial support of the National Science Fund, BulgarianMinistry of Education and Science, under project grant DN 02/11 and the Science Fund ofthe St. Kliment Ohridski University of Sofia under project grant No 80-10-196/24.04.2017.

Big Data Research and Application - A Systematic Literature Review

In the recent years Big Data has become a research topic forboth academia and industry. Given the data value for applications indifferent domains, as well as the business value of the data per se, there isan urgent need for solid end-to-end, data-driven and data-orientedsolutions to guide strategic decisions. Such solutions should include a setof mechanisms for runtime adaptations across the complete data lifecycleof Big Data Value Chain. Thus, advanced data functions enabling data tobe structured, cleaned, stored, aggregated, modelled, processed, andanalyzed are needed.Considering the significant value of Big Data, this paper presents asystematic literature review. Its main goal is to provide a holistic view ofBig Data challenges as a result of a thorough analysis of state-of-the-artresearch and applications.ACM Computing Classification System (1998): Y.1.0, Z.2.1.*This work was supported by the European Commission under grant agreement No 763566,by the National Science Fund, Bulgarian Ministry of Education and Science, within projectNo DN 02/11, and by the Science Fund of the St. Kliment Ohridski University of Sofa withinproject 80-10-192/24.04.2017.

Global Asymptotic Stability of a Functional Differential Model with Time Delay of an Anaerobic Biodegradation Process

We study a nonlinear functional differential model of an anaerobicdigestion process of wastewater treatment with biogas production. Themodel equations of biomass include two different discrete time delays. Amathematical analysis of the model is completed including existence andlocal stability of nontrivial equilibrium points, existence and boundednessof the model solutions as well as global stabilizability towards an admissibleequilibrium point. We propose and apply a numerical extremum seekingalgorithm for maximizing the biogas flow rate in real time. Numerical simulation results are also included.ACM Computing Classification System (1998): D.2.6, G.1.10, J.2.

Strategic Trade Between Two Countries—Exploring the Case of Partial Local Consumer Protection

The paper develops a dynamic model of trade between twocountries where the trading entities interact in a strategic context. Consumersin both countries are endowed with certain incomes and try to acquireas much as possible of the quantities available on the markets. Consumershave privileged access to some of the good supplied locally, a form of partiallocal protection. Over time, prices are adjusted to respond to the outcomesof trading. For this setup, we prove the existence of Nash equilibria andsimulate the model numerically in Python to illustrate the possibility of obtainingdifferent types of price dynamics depending on the price adjustmentrule used.ACM Computing Classification System (1998): J4, G4, I.6.3.

Manipulation by Merging and Annexation in Weighted Voting Games

The problem of manipulation in voting is fundamental and hasreceived attention in recent research in game theory. In this paper, we considertwo cases of manipulation in weighted voting games done by mergingof coalitions into single players and by annexation of a part or all of thevoting weights of another player viewed from two perspectives: of the effectof swings of players and of the role of the Banzhaf power index. We provetwo theorems for manipulation by merging and annexation, and show severalattractive properties in these two processes.ACM Computing Classification System (1998): J.4, I.2.1.

Fast Bitwise Implementation of the Algebraic Normal Form Transform

The representation of Boolean functions by their algebraic normalforms (ANFs) is very important for cryptography, coding theory andother scientific areas. The ANFs are used in computing the algebraic degreeof S-boxes, some other cryptographic criteria and parameters of errorcorrectingcodes. Their applications require these criteria and parameters tobe computed by fast algorithms. Hence the corresponding ANFs should alsobe obtained by fast algorithms. Here we continue our previous work on fastcomputing of the ANFs of Boolean functions. We present and investigatethe full version of bitwise implementation of the ANF transform. The experimental results show that this implementation ismore than 25 times faster in comparison to the well-known byte-wise ANFtransform.ACM Computing Classification System (1998): F.2.1, F.2.2.

What is Genselfdual?

This paper presents developed software in the area of CodingTheory. Using it, all binary self-dual codes with given properties can beclassified. The programs have consequent and parallel implementations.ACM Computing Classification System (1998): G.4, E.4.