The Study of Classification Analysis on Oil Exploration Research Trends and Digging Technology Based on Properties of Biochemical Materials (2012-2013)

2013 ◽  
Vol 859 ◽  
pp. 280-283
Author(s):  
Shiang Hau Wu ◽  
Jiann Jong Guo
Keyword(s):  
Text Mining ◽  
Random Forests ◽  
Research Trends ◽  
Oil Exploration ◽  
Mining Method ◽  
Research Papers ◽  
Classification Analysis ◽  
Relationship Of ◽  
The Relationship ◽  
Random Forests Model

The study aimed at analyzing the keywords of the oil exploration research papers abstracts in 2012 and 2013 and using the random forests model to make the classification analysis in order to find the importance and similarities of 2012 and 2013 research trends. The contribution of the study included the following two points. First, the study used the text mining method in order to explore the content of oil exploration research paper abstracts. Second, the study applied the AdaBoost classification analysis to explore the relationship of the keywords between the two years’ keywords.

Investigating Diseases and Chemicals in COVID-19 Literature with Text Mining (Preprint)

2020 ◽  
Author(s):  
Amir Karami ◽  
Brandon Bookstaver ◽  
Melissa Nolan
Keyword(s):  
Text Mining ◽  
Literature Review ◽  
Topic Modeling ◽  
Large Scale ◽  
Clinical Manifestations ◽  
International Health ◽  
Research Papers ◽  
Strategic Plans ◽  
Funding Agencies ◽  
The Relationship

BACKGROUND The COVID-19 pandemic has impacted nearly all aspects of life and has posed significant threats to international health and the economy. Given the rapidly unfolding nature of the current pandemic, there is an urgent need to streamline literature synthesis of the growing scientific research to elucidate targeted solutions. While traditional systematic literature review studies provide valuable insights, these studies have restrictions, including analyzing a limited number of papers, having various biases, being time-consuming and labor-intensive, focusing on a few topics, incapable of trend analysis, and lack of data-driven tools. OBJECTIVE This study fills the mentioned restrictions in the literature and practice by analyzing two biomedical concepts, clinical manifestations of disease and therapeutic chemical compounds, with text mining methods in a corpus containing COVID-19 research papers and find associations between the two biomedical concepts. METHODS This research has collected papers representing COVID-19 pre-prints and peer-reviewed research published in 2020. We used frequency analysis to find highly frequent manifestations and therapeutic chemicals, representing the importance of the two biomedical concepts. This study also applied topic modeling to find the relationship between the two biomedical concepts. RESULTS We analyzed 9,298 research papers published through May 5, 2020 and found 3,645 disease-related and 2,434 chemical-related articles. The most frequent clinical manifestations of disease terminology included COVID-19, SARS, cancer, pneumonia, fever, and cough. The most frequent chemical-related terminology included Lopinavir, Ritonavir, Oxygen, Chloroquine, Remdesivir, and water. Topic modeling provided 25 categories showing relationships between our two overarching categories. These categories represent statistically significant associations between multiple aspects of each category, some connections of which were novel and not previously identified by the scientific community. CONCLUSIONS Appreciation of this context is vital due to the lack of a systematic large-scale literature review survey and the importance of fast literature review during the current COVID-19 pandemic for developing treatments. This study is beneficial to researchers for obtaining a macro-level picture of literature, to educators for knowing the scope of literature, to journals for exploring most discussed disease symptoms and pharmaceutical targets, and to policymakers and funding agencies for creating scientific strategic plans regarding COVID-19.

scholarly journals Use of a text mining method for classifying citizen report data and analyzing the occurrence trend of local problems

2019 ◽  
Vol 8 (2) ◽  
pp. 1
Author(s):  
Eiji Kano ◽  
Kazuhiko Tsuda
Keyword(s):  
Text Mining ◽  
Traffic Safety ◽  
Living Environment ◽  
Mining Method ◽  
Local Problems ◽  
Problem Detection ◽  
Report System ◽  
Report Data ◽  
Maintenance And Inspection ◽  
The Relationship

An important task of any municipality is the maintenance and improvement of the street-related living environment and traffic safety for citizens.  For this, their department of street maintenance is expected to efficiently perform the maintenance and inspection of streets according to priority with limited human and budgetary resources.  Recently, municipalities in various countries are adopting “the citizen report system,” which is a system of reporting problems of streets, such as damaged streets, by citizens to their municipality, for citizens to perform part of street maintenance and inspection.  It is possible that the data obtained by municipalities through the citizen report system can be utilized not only for early problem detection but also for prioritizing administrative measures by using it for analyzing the occurrence trend of problems.  Problems reported by citizens, however, are classified by different methods from municipality to municipality, and thus the collection and comparative analysis of such data across municipalities is difficult.  This study presents a method of commonly classifying such data, regardless of different classification standards, by analyzing the contents of citizen reports by using text mining.  We then analyze the relationship between the trend of citizen reports and the occurrence trend of problems concerning the living environment and traffic safety, using the citizen report data of three large municipalities classified by this method, and infer the occurrence trend of problems.  This study has confirmed that citizen report data possibly contributes to municipalities’ prioritization of the maintenance and improvement of the living environment and traffic safety.

scholarly journals Automated Analysis of Domestic Violence Police Reports to Explore Abuse Types and Victim Injuries: Text Mining Study (Preprint)

2018 ◽  
Author(s):  
George Karystianis ◽  
Armita Adily ◽  
Peter W Schofield ◽  
David Greenberg ◽  
Louisa Jorm ◽  
...  
Keyword(s):  
Domestic Violence ◽  
Text Mining ◽  
Automated Analysis ◽  
Public Health Research ◽  
Free Text ◽  
Large Set ◽  
South Wales ◽  
Police Reports ◽  
Relationship Of ◽  
The Relationship

BACKGROUND The police attend numerous domestic violence events each year, recording details of these events as both structured (coded) data and unstructured free-text narratives. Abuse types (including physical, psychological, emotional, and financial) conducted by persons of interest (POIs) along with any injuries sustained by victims are typically recorded in long descriptive narratives. OBJECTIVE We aimed to determine if an automated text mining method could identify abuse types and any injuries sustained by domestic violence victims in narratives contained in a large police dataset from the New South Wales Police Force. METHODS We used a training set of 200 recorded domestic violence events to design a knowledge-driven approach based on syntactical patterns in the text and then applied this approach to a large set of police reports. RESULTS Testing our approach on an evaluation set of 100 domestic violence events provided precision values of 90.2% and 85.0% for abuse type and victim injuries, respectively. In a set of 492,393 domestic violence reports, we found 71.32% (351,178) of events with mentions of the abuse type(s) and more than one-third (177,117 events; 35.97%) contained victim injuries. “Emotional/verbal abuse” (33.46%; 117,488) was the most common abuse type, followed by “punching” (86,322 events; 24.58%) and “property damage” (22.27%; 78,203 events). “Bruising” was the most common form of injury sustained (51,455 events; 29.03%), with “cut/abrasion” (28.93%; 51,284 events) and “red marks/signs” (23.71%; 42,038 events) ranking second and third, respectively. CONCLUSIONS The results suggest that text mining can automatically extract information from police-recorded domestic violence events that can support further public health research into domestic violence, such as examining the relationship of abuse types with victim injuries and of gender and abuse types with risk escalation for victims of domestic violence. Potential also exists for this extracted information to be linked to information on the mental health status.

Using Text-mining Method to Identify Research Trends of Freshwater Exotic Species in Korea.

2015 ◽  
Vol 48 (3) ◽  
pp. 195-202 ◽  
Author(s):  
Yuno Do ◽  
◽  
Eui-Jeong Ko ◽  
Young-Min Kim ◽  
Hyo-Gyeom Kim ◽  
...  
Keyword(s):  
Text Mining ◽  
Exotic Species ◽  
Research Trends ◽  
Mining Method

Relationship of Corporate Governance with Firms Performance and Dividend Payout: A Literature Review

Think India ◽  
2018 ◽  
Vol 21 (2) ◽  
pp. 26-35
Author(s):  
Sushila Soriya ◽  
Narender Kumar
Keyword(s):  
Corporate Governance ◽  
Firm Performance ◽  
Research Work ◽  
Future Research ◽  
Governance Mechanism ◽  
Research Papers ◽  
Dividend Payout ◽  
Corporate Governance Mechanism ◽  
Relationship Of ◽  
The Relationship

The present study aims to find the research gap between corporate governance, firm performance, and dividend payout through available literature and develop future scope of the study. The study reviewed 100 research papers covering time from 1995 to 2016. The papers were classified and analyzed based on various approaches. The review of literature indicates that research work on area of corporate governance has increased after 2007-08 crises. The study reveals that the relationship of different variables of corporate governance with dividend payout and firm performance are mixed in nature. It also indicates that different countries have different socio-economic, cultural, political, and legal dimensions that in turn affect the governance regulations of any country. Present study classifies, summarizes, and analyzes the past literature and provides a comprehensive review on corporate governance mechanism, which may be helpful for future research in same area.

For Your Information

1982 ◽  
Vol 5 (1) ◽  
pp. 24-24
Keyword(s):  
New York ◽  
Criminal Behavior ◽  
World Trade Center ◽  
Research Papers ◽  
Anthropological Perspective ◽  
Trade Center ◽  
The University ◽  
Relationship Of ◽  
The Relationship ◽  
Unpublished Research

Information is requested for the publication of an article on the relationship of alcohol use to violence and criminal behavior. The article, employing a cross-cultural anthropological perspective, is to appear in the book Alcohol and Aggression edited by Paul F. Brain of the University of Swansea, to be published in England. Reprints, unpublished research papers, dissertations, dissertation abstracts, and project reports by anthropologists or other qualitative researchers should be sent by January 1, 1983 to David Strug, Narcotic and Drug Research, Inc., Room 6754, Two World Trade Center, New York, NY 10047.

Corporate governance: mapping the change

2018 ◽  
Vol 60 (1) ◽  
pp. 19-33 ◽  
Author(s):  
Varnita Srivastava ◽  
Niladri Das ◽  
Jamini Kanta Pattanayak
Keyword(s):  
Corporate Governance ◽  
Firm Performance ◽  
Design Methodology ◽  
Cost Of Capital ◽  
Research Papers ◽  
Content Type ◽  
Evolution And Development ◽  
Indian Context ◽  
Relationship Of ◽  
The Relationship

Purpose This paper aims to explore the relationship of corporate governance attributes with cost of capital and firm performance. This paper also tries to find some widely discussed corporate governance attributes that hold importance in Indian context. Design/methodology/approach This paper is based on literature survey of 241 research papers, both conceptual and empirical, which covers literature published over a period of three decades, ranging from 1986 to 2016. The literature includes those papers that studied the relation of corporate governance with cost of capital and firm performance, also it includes those research papers which discuss the evolution and development of corporate governance as a concept. Findings This study finds that the idea of corporate governance has shifted from the protection of shareholders’ rights to a firm’s need for survival. There is a dearth of literature studying the relation between corporate governance and cost of capital in India. It is observed that cost of capital is a better measure than Tobin’s q in Indian context. Research limitations/implications This paper mainly focuses on themes like cost of capital and firm performance therefore, some other firm-related measures which are also influenced by corporate governance may have been ignored. Originality/value This study enhances the literature on corporate governance especially in Indian context. Empirically testing the framework developed in this study will help in identifying the significance of various corporate governance attributes in Indian context.

Sign in / Sign up

Export Citation Format

Share Document