Eliciting Evolving Topics, Trends and Foresight about Self-driving Cars Using Dynamic Topic Modeling

2020 ◽  
pp. 488-509
Author(s):  
Workneh Y. Ayele ◽  
Gustaf Juell-Skielse
Keyword(s):  
Topic Modeling ◽  
Self Driving Cars

Artificial Intelligence in Logistics

2019 ◽  
Vol 12 (1) ◽  
pp. 47-60
Author(s):  
László Kota
Keyword(s):  
Artificial Intelligence ◽  
Computing Power ◽  
Self Driving Cars

The artificial intelligence undergoes an enormous development since its appearance in the fifties. The computing power has grown exponentially since then, enabling the use of artificial intelligence applications in different areas. Since then, artificial intelligence applications are not only present in the industry, but they have slowly conquered households as well. Their use in logistics is becoming more and more widespread, just think of self-driving cars and trucks. In this paper, the author attempts to summarize and present the artificial intelligence logistical applications, its development and impact on logistics.

Innovative Approach to Information Search by Example of a Patent Analysis of an Important Substitution Plan

2020 ◽  
pp. 143-157
Author(s):  
Maria A. Milkova
Keyword(s):  
Information Search ◽  
Topic Modeling ◽  
Cognitive Biases ◽  
A Priori ◽  
Import Substitution ◽  
Innovative Approach ◽  
Iterative Search ◽  
Comprehensive Picture ◽  
Priori Information ◽  
Selection Of

Nowadays the process of information accumulation is so rapid that the concept of the usual iterative search requires revision. Being in the world of oversaturated information in order to comprehensively cover and analyze the problem under study, it is necessary to make high demands on the search methods. An innovative approach to search should flexibly take into account the large amount of already accumulated knowledge and a priori requirements for results. The results, in turn, should immediately provide a roadmap of the direction being studied with the possibility of as much detail as possible. The approach to search based on topic modeling, the so-called topic search, allows you to take into account all these requirements and thereby streamline the nature of working with information, increase the efficiency of knowledge production, avoid cognitive biases in the perception of information, which is important both on micro and macro level. In order to demonstrate an example of applying topic search, the article considers the task of analyzing an import substitution program based on patent data. The program includes plans for 22 industries and contains more than 1,500 products and technologies for the proposed import substitution. The use of patent search based on topic modeling allows to search immediately by the blocks of a priori information – terms of industrial plans for import substitution and at the output get a selection of relevant documents for each of the industries. This approach allows not only to provide a comprehensive picture of the effectiveness of the program as a whole, but also to visually obtain more detailed information about which groups of products and technologies have been patented.

A Topic Modeling Analysis on the Major Social Issues of the Students’ Human Rights Ordinance in Korea

2017 ◽  
Vol 18 (4) ◽  
pp. 683-711
Author(s):  
Hyun-Jeong Park ◽  
Hanna Kim ◽  
YuJung Hong
Keyword(s):  
Human Rights ◽  
Topic Modeling ◽  
Social Issues ◽  
Modeling Analysis

Research Trends of Consumer Education Using Topic Modeling

2020 ◽  
Vol 16 (2) ◽  
pp. 83-115
Author(s):  
Mira Kim ◽  
◽  
Hye Sun Hwang ◽  
Xu Li
Keyword(s):  
Topic Modeling ◽  
Research Trends ◽  
Consumer Education

The Effect of Reference List in the Article on Topic Modeling using LDA

2019 ◽  
Vol 58 (6) ◽  
pp. 197-207
Author(s):  
Juhae Baeck ◽  
Hyungil Kwon ◽  
Mihwa Choi ◽  
Yi-Hsiu Lin
Keyword(s):  
Topic Modeling ◽  
Reference List

Fields of spatial research on urban areas in the context of organisational solutions to new forms of transportation

2018 ◽  
Vol 58 (1) ◽  
pp. 53-60
Author(s):  
Bartosz Czarnecki
Keyword(s):  
Urban Areas ◽  
Transportation System ◽  
Present Knowledge ◽  
Future Research ◽  
Use Of Self ◽  
Large Share ◽  
Main Achievement ◽  
Self Driving Cars

Abstract The paper discusses the spatial consequences of the widespread use of self-driving cars and the resulting changes in the structure of urban areas. Analysing present knowledge on the technology, functionality and future forms of organisation of mobility with this type of means of transportation, conclusions are presented concerning the expected changes in the organisation of space in urban areas. The main achievement of the investigation is an outline of the fields of future research on the spatial consequences of a transportation system with a large share of self-driving cars.

SCM Patent Analysis Using Topic Modeling: 1997~2016

2017 ◽  
Vol 17 (2) ◽  
pp. 19-29
Author(s):  
Mi-Ae Kim ◽  
Chang-Kyo Suh
Keyword(s):  
Topic Modeling ◽  
Patent Analysis
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