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Peter the Great St.Petersburg Polytechnic University, Russian Federation

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4 Papers

Identification of User Activity Types using Issue Tracker Events

Topics: Business Process Management; Big Data and Analytics

Authors: Inna Kurnosova ¹ , Dmitrii Timofeev ² and Alexander Samochadin ²

Affiliations: ¹ NeuroTech Lab, Institute of Applied Mathematics and Mechanics, Peter the Great St. Petersburg Polytechnic University, St. Petersburg and Russia , ² Mobile Device Management Lab, Institute of Computer Science and Technology, Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia, Higher School of Software Engineering, Institute of Computer Science and Technology, Peter the Great St. Petersburg Polytechnic University, St. Petersburg and Russia

Digital Object Identifier: 10.5220/0008383604050411

Proceedings of KMIS 2019, ISBN: 978-989-758-382-7

Quick Abstract

The paper studies the roles users play when contributing to open-source projects using modern code hosting and issue tracking platforms like GITHUB. Role identification has been performed using cluster analysis of the feature vectors generated from the events corresponding to user activity. The method was applied to three open-source projects of different sizes. The roles of maintainers and developers (core team), casual contributors, and watchers were identified, as well as the differences in work organization in these projects.

Related Ontology Subjects/Areas/Topics (8)

Artificial Intelligence	Enterprise Engineering	Knowledge-Based Systems
Business Process Management	Enterprise Information Systems	Symbolic Systems
e-Business	Knowledge Management and Information Sharing

An Unified Representation of Source Code Authoring Workflows

Topics: Metadata and Structured Documents; Business Process Management

Authors: Dmitrii Timofeev ¹ and Alexander Samochadin ²

Affiliations: ¹ Mobile Device Management Laboratory, Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya 29, St. Petersburg and Russia , ² Mobile Device Management Laboratory, Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya 29, St. Petersburg, Russia, Higher School of Software Engineering, Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya 21, St. Petersburg and Russia

Digital Object Identifier: 10.5220/0007229902280232

Proceedings of KMIS 2018, ISBN: 978-989-758-330-8

Quick Abstract

Existing approaches to modeling software development processes mostly deal with high-level processes at the level of project management. There are specific tasks that involve the analysis of processes at the level of writing and modifying the program code, but they lack a common reusable modeling framework. We suggest that a model of source code editing workflow would be beneficial for many tasks, from defect prediction to teaching programming to novices. We propose a unified approach that combines several levels of annotations, from keyboard events to task tracker issues and project planning.

Related Ontology Subjects/Areas/Topics (9)

Artificial Intelligence	Enterprise Engineering	Knowledge-Based Systems
Business Process Management	Enterprise Information Systems	Metadata and Structured Documents
e-Business	Knowledge Management and Information Sharing	Symbolic Systems

Training Process Modeling of Hammer Throwers Taking into Account Peculiarities of Stress Adaptation

Topic: Coaching

Authors: Alexander Bolotin and Vladislav Bakayev

Affiliation: Institute of Physical Education, Sports and Tourism, Peter the Great St. Petersburg Polytechnic University, St. Petersburg and Russian Federation

Digital Object Identifier: 10.5220/0006847300790083

Proceedings of icSPORTS 2018, ISBN: 978-989-758-325-4

Quick Abstract

The article considers the solution of the forecast problem to improve the efficiency of the training process of hammer throwers taking into account the peculiarities of their adaptation to the load. This problem was solved by computer modelling. To solve this problem, restrictions were set on the control and managed parameters. The number of parameters that were entered into the model was determined by the methods of expert assessments. These parameters were adjusted in the process of modelling the dynamics of the training system in time on a personal computer. Basing on the results of forecasting it was revealed that taking account the peculiarities of stress adaptation in hammer throwers training led to doubled number of sportsmen’s who fulfilled the qualification norm successfully.

Related Ontology Subjects/Areas/Topics (3)

Coaching

Health, Sports Performance and Support Technology

Sport Science Research and Technology

Process Extraction from Texts using Semantic Unification

Topics: Metadata and Structured Documents; Tools and Technology for Knowledge Management; Intelligent Information Systems; Business Process Management

Authors: Konstantin Sokolov ¹ , Dimitri Timofeev ² and Alexander Samochadin ²

Affiliations: ¹ Peter the Great St. Petersburg Polytechnic University and St. Petersburg State University, Russian Federation , ² Peter the Great St. Petersburg Polytechnic University, Russian Federation

Digital Object Identifier: 10.5220/0005638302540259

Proceedings of KMIS 2015/IC3K, ISBN: 978-989-758-158-8

Quick Abstract

In order to extract a process model from natural language sources, process elements such as agents, resources or actions have to be identified across one or multiple texts. Natural language descriptions tend to provide only partial and potentially contradictory information. Inability to systematically reconcile partial information significantly limits capabilities of current systems. We propose to address this problem by means of semantic unification integrated in the common text processing pipeline.

Related Ontology Subjects/Areas/Topics (11)

Artificial Intelligence	Enterprise Information Systems	Metadata and Structured Documents
Business Process Management	Intelligent Information Systems	Symbolic Systems
e-Business	Knowledge Management and Information Sharing	Tools and Technology for Knowledge Management
Enterprise Engineering	Knowledge-Based Systems