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Every day we are facing countless texts on various topics. With a growing number of resources, it is getting harder to find valuable content. There is a need for automated tools to evaluate texts and propose new reads based on their similarity to the original one. The paper aims at introducing a method for calculating the semantic distance between two texts. We use well-known morphological tools to disambiguate the meaning and function of each word in the text. Next, we create the similarity matrixes utilizing the weight of WordNet synset relations. Each term can be part of one of three sets, which visualize three levels of semantic distance. While calculating the distance between texts, we consider statistical characteristics that partly use the identification of terms. However, the primary stress is put on the meaning each word brings to the utterance.

Greater attention to the quality of life forces increased activity in the field of air quality monitoring. Many cities official perceive air pollution as an increasing issue worth investigating and managing. Thus, research focuses on delivering reliable real-time information on pollutants across the city area. The main focus of this article is the presentation of a collective framework to predict air pollution implementation. This solution allows informing about air pollution in places where no meters are available. The experimental results showed that the collective framework emerges the collective members’ knowledge and delivers prediction better than any algorithm used for agent predictions. It proves that collectives achieve better results than their members.

The utilization of management control systems in university management poses a considerable challenge because university’s strategic goals are not identical to those applied in profit-oriented management. A university’s management control system should take into account the processing of management information for management purposes, allowing for the relationships between different groups of stakeholders. The specificity of the university operation assumes conducting long-term scientific research and educational programmes. Therefore, the controlling approach to university management should considerat long-term performance measurement as well as management in key areas such as research, provision of education to students, and interaction with the tertiary institution’s socio-economic environment. This paper aims to develop a conceptual framework of the Intelligent Management Control System for Higher Education (IMCSHE) based on cognitive agents. The main findings are related to developing the assumption, model, and technological basis including the artificial intelligence method.

The paper presents a case study of modelling real-case industrial scenario of a grain-trading Polish company with Unified Process Metamodel (UPM). UPM is a novel approach for continuous process modelling. Many industrial processes, such as grain storage, are hard to describe by the use of conventional tools. With this example the authors emphasize the benefits of continuous process modeling paradigm over the token-based methodology and show the facilities of storage modeling and behavioral annotation in the UPM.

Background: This paper describes the use of fluorescence induced by UV radiation to evaluate the share of tracer in feed mixture. Methods: For the purpose of this study, three substances were used. They are as follows: Tinopal, Rhodamine B, and Uranine. Tracer in the form of maize or kardi was added to chicken feed before the mixing process. Grains used in the process were grinded in the mill sieve with a mesh size of 4 and 6 mm. The drawn samples of the mixture were illuminated with UV radiation to make grain tracer light, and then the photo was taken with a digital camera. The acquired images were analyzed with the use of a computer program running on the RGB color model, which was the way to obtain essential information about the percentage share of tracer. Results: It was observed that, in the case of kardi grains, the proposed method gives results significantly deviating from the verification method. Conclusions: Only the tests with the use of maize having an average particle diameter of 2.4 mm and tinted with the solution of Rhodamine B led to acceptable results (consensual with the predetermined verification level).

The monitoring of manufacturing processes is an important issue in nowadays ERP systems. One of the most important issues is to identify and analyze appropriate data for each of the production units taking part in the process. In the paper authors introduce a new approach towards modelling the relation between production units, signals and factors possible to obtain from the production system. The main idea for the system is based on the ontology of production units. The design of the system using advanced knowledge engineering is elaborated. Since, the implementation of proposed system was one of key assumptions, the relational model is presented that ensures possibility to deploy the system in the future.

Research in the field of collective intelligence is currently focused mainly on determining ways to provide a more and more accurate prediction. However, the development of collective intelligence requires a more formal approach. Thus the natural next step is to introduce the formal model of collective. Many scientists seem to see this need, but available solutions usually focus on narrow specialization. The problems within the scope of collective intelligence field typically require complex models. Sometimes more than one model has to be used. This paper addresses both issues. Authors introduce graph-based meta-model of collective that intend to describe all collective’s properties based on psychological knowledge, especially on Surowiecki’s work. Moreover, we introduced the taxonomy of metrics that allow assessing the qualitative aspects of crowd’s structure and dynamics.

Automated reasoning is becoming crucial for information systems. Building one uniform decision support system has become too complicated. The natural approach is to divide the task and combine the results from different subsystems into one uniform answer. It is the basic idea behind the system approach, where one solution is a composition of multiple subsystems. In this paper, the main emphasis is on establishing the theoretical framework that combines various reasoning methods into a collective system. The system’s formal abstraction uses graph theory and provides a discussion on possible aggregation function definitions. The proposed framework is a tool for building and testing specific approaches rather than the solution itself.

A new approach to modeling of various processes, namely Unified Process Metamodel, is presented. This universal solution serves the needs of modeling of modern decision-making systems used in a number of scientific areas. The metamodel uses solutions based on various knowledge engineering techniques. Four functional layers are selected under a new method, in each of them the specific types of components are defined. The particular attention to resource flow and control layer is devoted in the paper.

This paper describes the problems of modeling graph-based structures in Association-Oriented Database Metamodel in the context of knowledge representation system. The basics of Association-Oriented Metamodel solutions, principles of modeling and sample implementations of graph structures have been presented, including labeled graphs as well as generalization of graphs, i.e. hypergraphs. Subsequently, metastructural ontological design patterns dedicated to knowledge representation systems are presented based on example of standard class-instance-feature-value and relationship patterns.

The paper is a wide survey over one of the knowledge representation and processing solutions, namely knowledge bases. Due to current terminological inconsistency authors propose the complex definition of knowledge base in the field of knowledge representation. The overview of the most common reality description methods is provided in order to discuss its usefulness in knowledge base design. Authors not only give the definition of the knowledge base but also prove its completeness on the example of Semantic Knowledge Base project. The project aims at developing the general domain knowledge base using ontology base and semantic networks as basic knowledge representation methods.

Developing a knowledge-based system is a demanding task. One of the basic issues is to build a communication interface with a human. The basis for such an interface is mostly natural language. In this article, the process of building and supplementing data with one of the modules of the Semantic Knowledge Base, which is responsible for user interaction, is presented. For this purpose, the process of data acquisition from the WordNet database was carried out by remodeling it by the use of Association-Oriented Database Metamodel.

User interface is an important element of software system since it provides the means for utilizing applications’ functionalities. There is number of publications that propose guidance for proper interface design, including adaptive approach. Following paper introduces general idea for definition of interface design in a way that allows for easy computing of user interface effectiveness. The introduced factor can be used for recommendation of interface changes and adjustment.

Semantic networks are nowadays one of the most frequently used knowledge representation method. In this paper authors present a novel approach towards the definition and semantics of semantic networks with the use of predefined primitives as key structure elements. The presented solution is a part of Semantic Knowledge Base project, in which it is used to store complex information such as facts and rules. This approach aims at increased expressiveness of knowledge representation with the higher level of clarity of message. It introduces not only a unique duality of nodes types, namely operators and operands, but also provides mechanisms such as multiplicity, quantifiers or modifiers possible to apply to each and every of network elements.

Logic, language and information integration is one of areas broadly explored nowadays and at the same time promising. Authors use that approach in their 8 years long research into Structured Semantic Knowledge Base System. The aim of this paper is to present authors idea of system capable of generating synergy effect while storing various type of information. The key assumption, which has been adopted, is the thesis that the attempt to find universal way of the reality description is very inefficient solution. Combination of several solutions into one system must be based on the principle of supporting rather than on redundancy, ambiguity or mutual antagonism areas of logic, language and information. Natural language processing in the context of logics or information processing is ineffective, not to say pointless in the means of certainty. It is simply caused by the fact that natural languages have been formed long time ago as the main communication channel, rather than for automatic information processing. It was one of the reasons that logic has been founded as the universal language of mathematics and formalized communication in more extensive sense. Information processing however brought more sophisticated problems that mathematics could not smoothly solve, what made computer science appear. Studies over artificial intelligence revealed even more complex issues to solve. The unity of those three areas: logics, language and information is a necessity to acquire complementarity and synergy.

The following paper is a description of an approach adopted in the Semantic Knowledge Base in regard to the identification of meaning across multiple languages. The solution proposed separates the meaning from the text strings identifying it in a particular language. This solutions allows to create information collections that are subject to low risk of semantic ambiguity.

The paper proposes the \(\textsf {Unified\;Process\;Management\;for\;Service\;and\;Manufacture\;(UPM}^{\mathsf {Srv}}_{\mathsf {Mnf}}\textsf {)}\), the intent of which is to constitute integrated platform for modelling and exchange of information in the field of production processes. The \({\textsf {UPM}}^{\mathsf {Srv}}_{\mathsf {Mnf}}\) consists of a theoretical basis, formal notation, modeling language, algorithms, and methods of processing information as well as modeling methodology. This article focuses on the passage concerning the most theoretical foundations in the identification of selected categories and relations such as generalization-specialization, part–whole, class-feature, class-instance, and property-instance. The platform used to build \({\textsf {UPM}}^{\mathsf {Srv}}_{\mathsf {Mnf}}\) is the Semantic Knowledge Base (SKB), which is the result of a research project on methods of representation and processing of knowledge.

This article is a concise description of solutions for supplementing classic semantic networks with new functionality developed by the authors. Ths study is based on the Semantic Knowledge Base modeled in association-oriented database metamodel. It was the Extended Semantic Networks Module that has been introduced with modifiers, quantifiers, multiplicities and certainity factor extending classical approach towards semantic networks and expanding theirs knowledge representation capacity.

Following paper presents main concepts of Semantic Knowledge Base in particular linguistic module. The main assumption is to develop solution that would be easily adoptable by various languages. The module design will be presented in Association Oriented Model to maintain inner compatibility of the Knowledgebase.

The following text presents the method of supplementing and verifying information stored in a framework system of the semantic knowledge base. The indicated method refers to the knowledge of ontological character, in other words to information about definitions of concepts and relationships among them. The aim of the method is the constant supplementing and verifying of the knowledge, and making more precise and detailed information about existing connections between concepts. The key aspect of the method is questions generating strictly dependent on the preconceived structure of stored knowledge.

The main purpose of this paper is to show possible positive effect of 3D modeling application in rehabilitation. Authors provide clinic example of patient with ACL reconstruction. The patient has undertaken the therapy consisting of regular rehabilitation sessions as well as those enhanced by 3D rehabilitation application. The improvement in ACL rehabilitation was significant and worth further exploration.

The paper deals with active knowledge acquisition based on dialogue between AI system and its user. Presented method uses Conceptual Ontological Object Orientated System (COOS) to distinguish differences between concepts and to unequivocally process the input stream. In case of concepts, that do not exist in the system yet, adequate algorithms are being used to position them in ontological core. Separate concepts differ in attributes values or in sets of direct connections with other concepts. The communication aspect of the system deliver information that allow generating proper interpretation for userpsilas statement.

This paper describes principles of binary scene [1] morphological analysis in script based application - APR (Analysis, Processing and Recognition). The aim of the method is to find object on the scene and then to describe theirs basic features like edges, neighbors and surface [2]. The algorithm construction gives benefits in terms speed as well as to computation costs, at the same time being capable of presenting number of attributes values for scene and each of the objects. There are also some practical algorithm applications showed.

This paper deals with AI in aspect of knowledge acquisition and ontology base structure. The core of the system was designed in an object model to optimize it for further processing. Direct concept linking was used to assure fast semantic network processing. Predefined attributes used in the core minimize the number of basic connections within the ontology and help in inference. The system is assumed to generate questions and to specify the knowledge. The AI system defined in this way opens a possibility for better understanding of such basic human mind mechanisms as learning or analyzing.

The main purpose of this paper is to deliver appropriate tool to find similarities between texts. The area of interest covers comparing large amount of different texts grouped in various areas of knowledge. Similarity is defined as distance between two texts and as this the measure may be calculated as the set of parameters based on features.