scholarly journals How to Construct a Power Knowledge Graph with Dispatching Data?

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Shixiong Fan ◽  
Xingwei Liu ◽  
Ying Chen ◽  
Zhifang Liao ◽  
Yiqi Zhao ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Semantic Network ◽  
Research Topic ◽  
Knowledge Graph ◽  
Knowledge Model ◽  
Relationship Patterns ◽  
Related Services ◽  
Power Domain ◽  
Power Dispatching ◽  
Automated Labeling

Knowledge graph is a kind of semantic network for information retrieval. How to construct a knowledge graph that can serve the power system based on the behavior data of dispatchers is a hot research topic in the area of electric power artificial intelligence. In this paper, we propose a method to construct the dispatch knowledge graph for the power grid. By leveraging on dispatch data from the power domain, this method first extracts entities and then identifies dispatching behavior relationship patterns. More specifically, the method includes three steps. First, we construct a corpus of power dispatching behaviors by semi-automated labeling. And then, we propose a model, called the BiLSTM-CRF model, to extract entities and identify the dispatching behavior relationship patterns. Finally, we construct a knowledge graph of power dispatching data. The knowledge graph provides an underlying knowledge model for automated power dispatching and related services and helps dispatchers perform better power dispatch knowledge retrieval and other operations during the dispatch process.

scholarly journals Development of Knowledge Graph for Data Management Related to Flooding Disasters Using Open Data

2021 ◽  
Vol 13 (5) ◽  
pp. 124
Author(s):  
Jiseong Son ◽  
Chul-Su Lim ◽  
Hyoung-Seop Shim ◽  
Ji-Sun Kang
Keyword(s):  
Artificial Intelligence ◽  
Domain Knowledge ◽  
Open Data ◽  
Heterogeneous Data ◽  
Big Data Analysis ◽  
Knowledge Graph ◽  
Cross Domain ◽  
Disaster Data ◽  
Knowledge Graphs ◽  
Open Datasets

Despite the development of various technologies and systems using artificial intelligence (AI) to solve problems related to disasters, difficult challenges are still being encountered. Data are the foundation to solving diverse disaster problems using AI, big data analysis, and so on. Therefore, we must focus on these various data. Disaster data depend on the domain by disaster type and include heterogeneous data and lack interoperability. In particular, in the case of open data related to disasters, there are several issues, where the source and format of data are different because various data are collected by different organizations. Moreover, the vocabularies used for each domain are inconsistent. This study proposes a knowledge graph to resolve the heterogeneity among various disaster data and provide interoperability among domains. Among disaster domains, we describe the knowledge graph for flooding disasters using Korean open datasets and cross-domain knowledge graphs. Furthermore, the proposed knowledge graph is used to assist, solve, and manage disaster problems.

scholarly journals A Survey of Techniques for Constructing Chinese Knowledge Graphs and Their Applications

2018 ◽  
Vol 10 (9) ◽  
pp. 3245 ◽  
Author(s):  
Tianxing Wu ◽  
Guilin Qi ◽  
Cheng Li ◽  
Meng Wang
Keyword(s):  
Artificial Intelligence ◽  
Question Answering ◽  
Knowledge Representation And Reasoning ◽  
Knowledge Graph ◽  
Development History ◽  
One Belt One Road ◽  
History Of ◽  
Knowledge Graphs ◽  
The One ◽  
The Impact

With the continuous development of intelligent technologies, knowledge graph, the backbone of artificial intelligence, has attracted much attention from both academic and industrial communities due to its powerful capability of knowledge representation and reasoning. In recent years, knowledge graph has been widely applied in different kinds of applications, such as semantic search, question answering, knowledge management and so on. Techniques for building Chinese knowledge graphs are also developing rapidly and different Chinese knowledge graphs have been constructed to support various applications. Under the background of the “One Belt One Road (OBOR)” initiative, cooperating with the countries along OBOR on studying knowledge graph techniques and applications will greatly promote the development of artificial intelligence. At the same time, the accumulated experience of China in developing knowledge graphs is also a good reference to develop non-English knowledge graphs. In this paper, we aim to introduce the techniques of constructing Chinese knowledge graphs and their applications, as well as analyse the impact of knowledge graph on OBOR. We first describe the background of OBOR, and then introduce the concept and development history of knowledge graph and typical Chinese knowledge graphs. Afterwards, we present the details of techniques for constructing Chinese knowledge graphs, and demonstrate several applications of Chinese knowledge graphs. Finally, we list some examples to explain the potential impacts of knowledge graph on OBOR.

scholarly journals Knowledge Graphs and Network Text Analysis

2003 ◽  
Vol 42 (1) ◽  
pp. 91-106 ◽  
Author(s):  
Roel Popping
Keyword(s):  
Present State ◽  
Text Analysis ◽  
Scientific Theory ◽  
Semantic Network ◽  
Labour Markets ◽  
Knowledge Graph ◽  
Causal Relations ◽  
Network Text Analysis ◽  
Knowledge Graphs

A knowledge graph is a kind of semantic network representing some scientific theory. The article describes the present state of this field and addresses a number of problems that have not yet been solved. These problems are implicit relations, strength of (causal) relations, and exclusiveness. Concepts might be too broad or complex to be used properly, so directions for solving these problems are explored. The solutions are applied to a knowledge graph in the field of labour markets.

Review on knowledge graph and its application in power dispatching

2021 ◽  
Author(s):  
Kedong Zhu ◽  
Jing Zhou ◽  
Xiaorui Guo ◽  
Feng Li ◽  
Huibiao Yang
Keyword(s):  
Knowledge Graph ◽  
Power Dispatching

Non-Player Characters and Artificial Intelligence

Gamification ◽  
2015 ◽  
pp. 488-514
Author(s):  
Gonçalo Pereira ◽  
António Brisson ◽  
João Dias ◽  
André Carvalho ◽  
Joana Dimas ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Computational Models ◽  
Research Topic ◽  
Interactive Systems ◽  
Learning Activity ◽  
Willingness To Accept ◽  
User Engagement ◽  
Efficient Communication ◽  
Game Environment ◽  
Computational Systems

Serious Games rely on interactive systems to provide an efficient communication medium between the tutor and the user. Designing and implementing such medium is a multi-disciplinary task that aims at an environment that engages the user in a learning activity. User engagement is significantly related to the users' sense of immersion or his willingness to accept the reality proposed by a game environment. This is a very relevant research topic for Artificial Intelligence (AI), since it requires computational systems to generate believable behaviors that can promote the users' willingness to enter and engage in the game environment. In order to do this, AI research has been relying on social sciences, in particular psychology and sociology models, to ground the creation of computational models for non-player characters that behave according to the users' expectations. In this chapter, the authors present some of the most relevant NPC research contributions following this approach.

What Prevents You to Plug in to Online Surveys?

2022 ◽  
pp. 131-148
Author(s):  
Burcu Karabulut Coşkun ◽  
Ezgi Mor Dirlik
Keyword(s):  
Artificial Intelligence ◽  
Online Survey ◽  
Response Rate ◽  
Data Gathering ◽  
Theoretical Framework ◽  
Research Topic ◽  
Online Surveys ◽  
Online Data ◽  
Factors Affecting ◽  
Response Behaviors

In today's world, which has been administered by computers and artificial intelligence in many areas, online data gathering has become an inevitable way of collecting data. Many researchers have preferred online surveying, considering the advantages of this method over the classical ones. Hence, the factors that may affect the response rate of online surveying have become a prominent research topic. In line with the popularity of this issue, the purpose of this chapter was to clarify the concept of online surveys; give information about their types, advantages, and usage; and investigate the factors that affect the participants' response behaviors. Besides the discussions on the theoretical framework of online surveying, an online survey aiming to determine the factors affecting the participation in online surveying was administered to a group of people to investigate the response behaviors thoroughly. The findings revealed that rs might affect ants' response behaviors to online surveys in various ways radically.

scholarly journals Automation of management processes

2019 ◽  
Vol 132 ◽  
pp. 01020
Author(s):  
Luis Ochoa Siguencia ◽  
Piotr Halemba
Keyword(s):  
Artificial Intelligence ◽  
Service Management ◽  
Environmental Changes ◽  
Technology Development ◽  
New Paradigm ◽  
Convenience Sample ◽  
Related Services ◽  
Tourism Management ◽  
Information Technology Development ◽  
Management Students

Artificial intelligence and service automation are the key to these kinds of new, product-related services. They increasingly penetrate the traditional mechanical and plant engineering sector and open up potentials for innovative services. Tourism services providers are going through rapid changes and the role of Information and Communication Technology, artificial intelligence and service automation is increasing in all spheres of the service management system. When the organization is threatened by environmental changes such as crises or competition as a result of information technology development or increased customer demands, the need for communication increases. This paper presents the first step of an ongoing investigation that focuses on the tourist services experiences and construction of management knowledge on undergraduate tourism management students. We report and discuss the result of a survey conducted involving the students of Tourism management at The Jerzy Kukuczka Physical Education Academy in Katowice - Poland. Structured questionnaires based on a 12-item importance scale were administered to a convenience sample of respondents. The authors present a new paradigm that emerges as a response to polarisation and treats communication as more receiver-centered, stakeholder ⚟ based, relationship ⚟ building ⚟ oriented and of strategic importance.

scholarly journals Archetypal Use of Artificial Intelligence for Bridge Structural Monitoring

2020 ◽  
Vol 10 (20) ◽  
pp. 7157
Author(s):  
Bernardino Chiaia ◽  
Valerio De Biagi
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Damage Detection ◽  
Working Life ◽  
Research Topic ◽  
Structural Monitoring ◽  
The Sixties ◽  
Relevant Role ◽  
Measurement Devices

Structural monitoring is a research topic that is receiving more and more attention, especially in light of the fact that a large part our infrastructural heritage was built in the Sixties and is aging and approaching the end of its design working life. The detection of damage is usually performed through artificial intelligence techniques. In contrast, tools for the localization and the estimation of the extent of the damage are limited, mainly due to the complete datasets of damages needed for training the system. The proposed approach consists in numerically generating datasets of damaged structures on the basis of random variables representing the actions and the possible damages. Neural networks were trained to perform the main structural monitoring tasks: damage detection, localization, and estimation. The artificial intelligence tool interpreted the measurements on a real structure. To simulate real measurements more accurately, noise was added to the synthetic dataset. The results indicate that the accuracy of the measurement devices plays a relevant role in the quality of the monitoring.

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