State of the Art in the Contribution of an Ontology-Oriented Knowledge Base to the Development of a Collaborative Information System

2019 ◽  
pp. 603-617
Author(s):  
Meryam El Mrini ◽  
El Hassan Megder ◽  
Mostafa El yassa
Keyword(s):  
Information System ◽  
Knowledge Base ◽  
State Of The Art ◽  
Collaborative Information System

EXPERT MANAGEMENT SYSTEMS OF AGROTECHNOLOGIES IN CLOUD INFORMATION TECHNOLOGY

1970 ◽  
pp. 12-17
Author(s):  
I. М. Mikhaylenko ◽  
V. N. Timoshin
Keyword(s):  
Decision Making ◽  
Pattern Recognition ◽  
Information System ◽  
Knowledge Base ◽  
Information Technologies ◽  
Agricultural Sector ◽  
Perennial Grasses ◽  
Management Decision ◽  
Agricultural Technologies ◽  
Automation Systems

The transition to "intellectual" agriculture is the main vector of modernization of the agricultural sector of the economy. It is based on integrated automation and robotization of production, the use of automated decision-making systems. This is inevitably accompanied by a significant increase in data flow from sensors, monitoring systems, meteorological stations, drones, satellites and other external systems. Farm management has the opportunity to use various online applications for accurate recommendations and making various kinds of management decisions. In this regard, the most effective use of cloud information technologies, allowing implementing the most complex information and technical level of automation systems for management of agricultural technologies. The purpose of this work is to test the approach to creating expert management decision support systems (DSS) through the knowledge base (KB), formed in the cloud information system. For this, we consider an example of constructing a DSS for choosing the optimal date for preparing forage from perennial grasses. A complete theoretical and algorithmic database of the analytical DSS implemented in the data processing center of the cloud information system is given. On its basis, a KB is formed for a variety of different decision-making conditions. This knowledge base is transmitted to the local DSS. To make decisions about the optimal dates for the preparation of the local DSS, two variants of algorithms are used. The first option is based on management models, and the second uses the pattern recognition method. The approbation of the algorithms was carried out according to the BZ from 50 cases. According to the results of testing, the method of pattern recognition proved to be more accurate, which provides a more flexible adjustment of the situation on the local DSS to a similar situation in the KB. The considered technique can be extended to other crops.

scholarly journals An Agent-Aware Computing Based Mixed Reality Information System

2017 ◽  
Vol 17 (3) ◽  
pp. 1-14 ◽  
Author(s):  
Charles Z. Liu ◽  
Manolya Kavakli
Keyword(s):  
Information System ◽  
Mixed Reality ◽  
Computing System ◽  
Test Results ◽  
System Synthesis ◽  
Human System ◽  
Qos Management ◽  
Collaborative Information System

In this paper, we present an agent- aware computing based collaborative information sys- tem scheme for MR applications. The HCI issues in VR, AR, and MR, have been discussed firstly. Besides the equipment, the lack of understanding of users also ac- counts for a significant bottleneck of improving user ex- perience and immersion during the interaction. Aiming at the issues, an agent-aware computing based scheme is proposed and implemented. The corresponding sys- tematic scheme is presented in the views of functional- ity, modules and system workflow and discussed in de- sign, implementation, and system synthesis. By means of the human-aware computing, system-aware comput- ing and human-system aware computing, issues such as mixed reality fusion, QoE-QoS management, confiden- tiality, and security, are addressed by the applying agent- aware computing based scheme into an implementation of the collaborative information system for mixed real- ity. Related modules along with their function and test results are given and discussed.

DeLone & McLean IS Success Model in Evaluating Knowledge Transfer in a Virtual Learning Environment

2012 ◽  
pp. 100-113
Author(s):  
Raija Halonen ◽  
Heli Thomander ◽  
Elisa Laukkanen
Keyword(s):  
Information System ◽  
Knowledge Base ◽  
Virtual Learning Environment ◽  
Educational Services ◽  
Is Success ◽  
Information System Success ◽  
Success Model ◽  
Educational Institute ◽  
Information System Success Model

DeLone & McLean’s success model has been actively used since its first introduction in 1992. In this article, the authors extend this model to describe the success of knowledge sharing in an information system that included a part of the knowledge base of a private educational institute. As the supply of private education is increased, it is vital to be aware if the offered educational services support the use of the knowledge base and if the service is perceived satisfactory by the customers. In this descriptive qualitative case study, the authors discuss how the DeLone & McLean’s information system success model can be used to assess educational services when apprenticeships form a salient part of teaching. This paper focuses on issues that interested the target organization.

Ubiquitous Learning Supporting Systems

2015 ◽  
pp. 202-225
Author(s):  
Elena B. Durán ◽  
Margarita Álvarez
Keyword(s):  
Information System ◽  
State Of The Art ◽  
The State ◽  
System Research ◽  
Ubiquitous Learning ◽  
Information System Research ◽  
The Future ◽  
National University ◽  
The Right ◽  
Research Institute

Ubiquitous learning features intuitive ways of identifying appropriate learning collaborators and right learning contents and services at the right place and at the right time. Consequently, there are many aspects that must be considered in designing computing applications that support this kind of learning. In this chapter, ubiquitous learning is introduced and characterized, the challenges that must be faced by those in charge of designing and developing such applications are reviewed, and the state of the art of this recently initiated line of research at the Informatics and Information System Research Institute of the National University of Santiago del Estero are presented. The developments achieved to date as well as the future guidelines are also shown.

scholarly journals Combining Axiom Injection and Knowledge Base Completion for Efficient Natural Language Inference

2019 ◽  
Vol 33 ◽  
pp. 7410-7417 ◽  
Author(s):  
Masashi Yoshikawa ◽  
Koji Mineshima ◽  
Hiroshi Noji ◽  
Daisuke Bekki
Keyword(s):  
Natural Language ◽  
Knowledge Base ◽  
Processing Speed ◽  
Processing Time ◽  
State Of The Art ◽  
Proof Automation ◽  
New Knowledge ◽  
Textual Entailment ◽  
Amount Of Knowledge ◽  
Recognizing Textual Entailment

In logic-based approaches to reasoning tasks such as Recognizing Textual Entailment (RTE), it is important for a system to have a large amount of knowledge data. However, there is a tradeoff between adding more knowledge data for improved RTE performance and maintaining an efficient RTE system, as such a big database is problematic in terms of the memory usage and computational complexity. In this work, we show the processing time of a state-of-the-art logic-based RTE system can be significantly reduced by replacing its search-based axiom injection (abduction) mechanism by that based on Knowledge Base Completion (KBC). We integrate this mechanism in a Coq plugin that provides a proof automation tactic for natural language inference. Additionally, we show empirically that adding new knowledge data contributes to better RTE performance while not harming the processing speed in this framework.

scholarly journals Deep Cascade Multi-Task Learning for Slot Filling in Online Shopping Assistant

2019 ◽  
Vol 33 ◽  
pp. 6465-6472 ◽  
Author(s):  
Yu Gong ◽  
Xusheng Luo ◽  
Yu Zhu ◽  
Wenwu Ou ◽  
Zhao Li ◽  
...  
Keyword(s):  
Natural Language ◽  
Knowledge Base ◽  
Online Shopping ◽  
State Of The Art ◽  
Language Understanding ◽  
Dialog Systems ◽  
Named Entity ◽  
Online Test ◽  
Benchmark Datasets ◽  
Slot Filling

Slot filling is a critical task in natural language understanding (NLU) for dialog systems. State-of-the-art approaches treat it as a sequence labeling problem and adopt such models as BiLSTM-CRF. While these models work relatively well on standard benchmark datasets, they face challenges in the context of E-commerce where the slot labels are more informative and carry richer expressions. In this work, inspired by the unique structure of E-commerce knowledge base, we propose a novel multi-task model with cascade and residual connections, which jointly learns segment tagging, named entity tagging and slot filling. Experiments show the effectiveness of the proposed cascade and residual structures. Our model has a 14.6% advantage in F1 score over the strong baseline methods on a new Chinese E-commerce shopping assistant dataset, while achieving competitive accuracies on a standard dataset. Furthermore, online test deployed on such dominant E-commerce platform shows 130% improvement on accuracy of understanding user utterances. Our model has already gone into production in the E-commerce platform.

Knowledge-Based Environmental Information System Support for Wetland Resources Protection and Utilization

2010 ◽  
Vol 113-116 ◽  
pp. 1256-1260
Author(s):  
Jun Luo ◽  
Wei Guo Zhang ◽  
Bing Shan Wu
Keyword(s):  
Sustainable Development ◽  
Information System ◽  
Knowledge Base ◽  
Environmental Information ◽  
Base System ◽  
The Sustainable Development ◽  
Knowledge Based ◽  
Environmental Information System ◽  
Protection And Utilization ◽  
Wetland Resources

Unsuitable development of wetland area will cause serious environmental problems. Thus, wetland development and environmental protection has become an issue of national emphasis for the environmental management in the world. There is a demand for planning and decision strategies in this complex area. Because of the complexity and the enormous amount of relevant data, the decision makers need effective support for their decisions. The use of a knowledge-based approach is a solution for reducing this complexity. Accordingly, this study adopts knowledge management techniques and information technology to acquire and retain all kind of knowledge needed for the decision making process, and discusses the development of knowledge-based environmental information system promote the sustainable development wetland. The aim of this paper is to develop knowledge base system integrate with the existing information database and improve the knowledge base associated with environmental decision processes to help the sustainable development of wetland.

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