Ontology reasoning using SPARQL query: A case study of e-learning usage

The involvement of learning pedagogy towards implementation of e-learning contribute to the additional values, and it is assign as a benchmark when the investigation and evaluation will carry out. The results obtained later believed would be fit to the domain problem.The results might provide instructional theories including recommendation after reasoning that can be used to improve the quality of teaching and learning in the virtual classroom. Ontology as formal conceptualization has been chosen as research methodology. Ontology conceptualization helps to illustrate the e-learning usage including activities and actions, likewise learning pedagogy in the form of concepts, class, relationships and instances. The ontology constructed in this paper is used in conjunction with the SPARQL rules, which are designed to test the reasoning ability of ontology. Reasoning results should be able to describe the knowledge contained in ontology, as well the facts on it. The SPARQL rules contains triplets to verify if the students are actively engaged in a meaningful way towards e-learning usage. The backward engine is optimized to store the facts obtained from queries. Development of ontology knowledge based and reasoning rules with SPARQL queries allow to contribute a sustainable competitive advantages regarding the e-learning utilization. Eventually, this research produced a learning ontology with reasoning capability to get meaningful information

A commentary on standardization in the Semantic Web, Common Logic and MultiAgent Systems

Given the ubiquity of the Web, the Semantic Web (SW) offers MultiAgent Systems (MAS) a most wide-ranging platform by which they could intercommunicate. It can be argued however that MAS require levels of logic that the current Semantic Web has yet to provide. As ISO Common Logic (CL) ISO/IEC IS 24707:2007 provides a firstorder logic capability for MAS in an interoperable way, it seems natural to investigate how CL may itself integrate with the SW thus providing a more expressive means by which MAS can interoperate effectively across the SW. A commentary is accordingly presented on how this may be achieved. Whilst it notes that certain limitations remain to be addressed, the commentary proposes that standardising the SW with CL provides the vehicle by which MAS can achieve their potential.</p

Automatic Concept Extraction in Semantic Summarization Process

The Semantic Web offers a generic infrastructure for interchange, integration and creative reuse of structured data, which can help to cross some of the boundaries that Web 2.0 is facing. Currently, Web 2.0 offers poor query possibilities apart from searching by keywords or tags. There has been a great deal of interest in the development of semantic-based systems to facilitate knowledge representation and extraction and content integration [1], [2]. Semantic-based approach to retrieving relevant material can be useful to address issues like trying to determine the type or the quality of the information suggested from a personalized environment. In this context, standard keyword search has a very limited effectiveness. For example, it cannot filter for the type of information, the level of information or the quality of information. Potentially, one of the biggest application areas of content-based exploration might be personalized searching framework (e.g., [3],[4]). Whereas search engines provide nowadays largely anonymous information, new framework might highlight or recommend web pages related to key concepts. We can consider semantic information representation as an important step towards a wide efficient manipulation and retrieval of information [5], [6], [7]. In the digital library community a flat list of attribute/value pairs is often assumed to be available. In the Semantic Web community, annotations are often assumed to be an instance of an ontology. Through the ontologies the system will express key entities and relationships describing resources in a formal machine-processable representation. An ontology-based knowledge representation could be used for content analysis and object recognition, for reasoning processes and for enabling user-friendly and intelligent multimedia content search and retrieval. Text summarization has been an interesting and active research area since the 60’s. The definition and assumption are that a small portion or several keywords of the original long document can represent the whole informatively and/or indicatively. Reading or processing this shorter version of the document would save time and other resources [8]. This property is especially true and urgently needed at present due to the vast availability of information. Concept-based approach to represent dynamic and unstructured information can be useful to address issues like trying to determine the key concepts and to summarize the information exchanged within a personalized environment. In this context, a concept is represented with a Wikipedia article. With millions of articles and thousands of contributors, this online repository of knowledge is the largest and fastest growing encyclopedia in existence. The problem described above can then be divided into three steps: • Mapping of a series of terms with the most appropriate Wikipedia article (disambiguation). • Assigning a score for each item identified on the basis of its importance in the given context. • Extraction of n items with the highest score. Text summarization can be applied to many fields: from information retrieval to text mining processes and text display. Also in personalized searching framework text summarization could be very useful. The chapter is organized as follows: the next Section introduces personalized searching framework as one of the possible application areas of automatic concept extraction systems. Section three describes the summarization process, providing details on system architecture, used methodology and tools. Section four provides an overview about document summarization approaches that have been recently developed. Section five summarizes a number of real-world applications which might benefit from WSD. Section six introduces Wikipedia and WordNet as used in our project. Section seven describes the logical structure of the project, describing software components and databases. Finally, Section eight provides some consideration..

УПРАВЛІННЯ ПРОЦЕСОМ ОЦІНЮВАННЯ ЗНАНЬ ПРИ ПІДГОТОВЦІ РЯ- ТУВАЛЬНИКІВ З ВИКОРИСТАННЯМ ОНТОЛОГІЇ НАВЧАЛЬНИХ КУРСІВ

In connection with the expansion of distance education there is a necessity of the development and use of computer-aided learning and knowledge control. The main attention is paid to the peculiarities of software development and the problems of optimization of the educational material structure, and the development of a methodology of knowledge testing and methods of verification remain on the sidelines. This article proposes a new approach to the development of automated control systems of knowledge based on ontology of subject areas, which in this case are the training courses. The formation of ontology and logic scheme of control of knowledge allows structuring the learning material, to identify topics and issues that represent challenges for the cadets (students), as well as to develop a software wrapper for uniform formation of control systems of knowledge of various training courses.У зв'язку з поширенням дистанційної освіти виникає необхідність розробки і використання засобів автоматизованого навчання і контролю знань. При цьому головну увагу звертають на особливості розробки програмного забезпечення, а проблеми оптимізації структури навчального матеріалу, а також розробки методології тестування знань і методів її верифікації залишаються осторонь. Запропоновано новий підхід до розробки автоматизованих систем контролю знань, заснований на онтологіях предметних областей, якими в даному випадку є навчальні курси. Формування онтології та логічної схеми контролю знань дозволяє структурувати навчальний матеріал, визначити теми і питання, які становлять труднощі для курсантів (студентів), а також розробити програмну оболонку для уніфікованого формування систем контролю знань з різних навчальних курсів

Sensory semantic user interfaces (SenSUI)

Rapid evolution of the World Wide Web with its underlying sources of data, knowledge, services and applications continually attempts to support a variety of users, with different backgrounds, requirements and capabilities. In such an environment, it is highly unlikely that a single user interface will prevail and be able to fulfill the requirements of each user adequately. Adaptive user interfaces are able to adapt information and application functionalities to the user context. In contrast, pervasive computing and sensor networks open new opportunities for context aware platforms, one that is able to improve user interface adaptation reacting to environmental and user sensors. Semantic web technologies and ontologies are able to capture sensor data and provide contextual information about the user, their actions, required applications and environment. This paper investigates the viability of an approach where semantic web technologies are used to maximize the efficacy of interface adaptation through the use of available ontology

PEMBUATAN ONTOLOGY LEARNING OBJECT PADA E-LEARNING

Salah satu komponen penting web e-learning adalah content. Dalam perkembangannya, e-learning content berubah menjadi learning object dengan penambahan metadata di dalamnya. Metadata ini kemudian dimasukan ke dalam ontology sehingga diharapkan dapat memudahkan penyebaran dan pencarian materi tersebut. Penulisan ini akan menjabarkan proses pembuatan ontology beserta implementasinya untuk dimanfaatkan dalam proses pencarian suatu learning object. Dengan memanfaatkan ontology ini hasil pencarian diharapkan dapat lebih tepat dan sesuai

Ontologies for Personalised Adaptive Learning

In recent years there has been an increasing interest in individual education. Consequently, one of the hot research topics is to adapt learning content to learner’s learning needs. Furthermore, recent developments in the field of semantic web have led to a renewed attention with focus in ontology-based e-learning system. This paper proposes an innovative ontological approach to design a personalised e-learning system which creates tailored contents for individual learners. The learning content associated with sequencing logic provides a clear separation between the domain and content models to increase the reusability and flexibility of the system. Additionally, in the proposed approach learner’s profiles are modelled to describe learner’s characteristics