scholarly journals Search Engine Optimization Method of Online Course Management Platform

2021 ◽  
Vol 2138 (1) ◽  
pp. 012023
Author(s):  
Bixi Wang ◽  
Wenbin Wu ◽  
Wenfeng Zheng ◽  
Qilong Gong ◽  
Lirong Yin
Keyword(s):  
Search Engine ◽  
Evaluation Method ◽  
Keyword Search ◽  
Optimization Method ◽  
Volume Data ◽  
Search Engine Optimization ◽  
Management Platform ◽  
Search Volume ◽  
Comprehensive Index ◽  
Index Evaluation

Abstract This study proposes a method of keyword selection in search engine optimization to improve the accuracy of search engine and website rankings. To promote the development of scientific and technological innovation, this paper selects the innovation and entrepreneurship curriculum platform as the experimental object. By comparing different search engine optimization strategies, the keyword search volume data is analyzed based on “comprehensive index evaluation method”, which analyzes and calculates the change of keyword search comparison and the number of related keywords. Therefore, this paper will use the comprehensive index evaluation method for keyword selection, and establish a set of practical keyword selection method combined with the actual situation of innovation and enterprise curriculum platform. The results show that this program can improve search accuracy and website ranking.

Discovering business information from search engine query data

2014 ◽  
Vol 38 (4) ◽  
pp. 562-574 ◽  
Author(s):  
Liwen Vaughan
Keyword(s):  
Search Engine ◽  
Business Performance ◽  
Google Trends ◽  
Volume Data ◽  
Content Type ◽  
Search Volume ◽  
Business Information ◽  
Position Data ◽  
Search Data ◽  
One Year

Purpose – The purpose of this paper is to examine the feasibility of discovering business information from search engine query data. Specifically the study tried to determine whether search volumes of company names are correlated with the companies’ business performance and position data. Design/methodology/approach – The top 50 US companies in the 2012 Fortune 500 list were included in the study. The following business performance and position data were collected: revenues, profits, assets, stockholders’ equity, profits as a percentage of revenues, and profits as a percentage of assets. Data on the search volumes of the company names were collected from Google Trends, which is based on search queries users enter into Google. Google Trends data were collected in the two scenarios of worldwide searches and US searches. Findings – The study found significant correlations between search volume data and business performance and position data, suggesting that search engine query data can be used to discover business information. Google Trends’ worldwide search data were better than the US domestic search data for this purpose. Research limitations/implications – The study is limited to only one country and to one year of data. Practical implications – Publicly available search engine query data such as those from Google Trends can be used to estimate business performance and position data which are not always publicly available. Search engine query data are timelier than business data. Originality/value – This is the first study to establish a relationship between search engine query data and business performance and position data.

Complex dynamics of our economic life on different scales: insights from search engine query data

2010 ◽  
Vol 368 (1933) ◽  
pp. 5707-5719 ◽  
Author(s):  
Tobias Preis ◽  
Daniel Reith ◽  
H. Eugene Stanley
Keyword(s):  
Time Series ◽  
Search Engine ◽  
Financial Market ◽  
Complex Dynamics ◽  
Economic Life ◽  
Volume Data ◽  
Market Participants ◽  
Search Terms ◽  
Search Volume ◽  
Internet Users

Search engine query data deliver insight into the behaviour of individuals who are the smallest possible scale of our economic life. Individuals are submitting several hundred million search engine queries around the world each day. We study weekly search volume data for various search terms from 2004 to 2010 that are offered by the search engine Google for scientific use, providing information about our economic life on an aggregated collective level. We ask the question whether there is a link between search volume data and financial market fluctuations on a weekly time scale. Both collective ‘swarm intelligence’ of Internet users and the group of financial market participants can be regarded as a complex system of many interacting subunits that react quickly to external changes. We find clear evidence that weekly transaction volumes of S&P 500 companies are correlated with weekly search volume of corresponding company names. Furthermore, we apply a recently introduced method for quantifying complex correlations in time series with which we find a clear tendency that search volume time series and transaction volume time series show recurring patterns.

Study on the Assessment of Ecological Environment in Haikou City

2013 ◽  
Vol 838-841 ◽  
pp. 2570-2577
Author(s):  
Xin Chen ◽  
Bei Bei Liu ◽  
Li Xu Peng
Keyword(s):  
Evaluation Method ◽  
Time Series Data ◽  
Ecological Environment ◽  
Series Data ◽  
Land Resources ◽  
Environment Quality ◽  
Comprehensive Index ◽  
Level Ii ◽  
Index Evaluation ◽  
The City

Based on the time series data of ecological environment in Haikou during 2001-2011 and determined the weights of ecological factor by the factor analysis method, the urban ecological environment of Haikou were evaluated dynamically using the comprehensive index evaluation method. The results show that the city ecological environment quality comprehensive index of Haikou is the level III and the ecological degree is general during 2001-2007，while the index of Haikou is the level II and has a higher degree of ecological during 2008-2011. It indicates that Haikou government is effect on promoting the ecological environment construction of the city. In order to construct the ecological environment of Haikou, we should increase the utilize level of water resources, change the use pattern of land resources, focus on the development of economy, improve the people's income level, improve the city medical level and increase the investment of science & technology education.

Comprehensive index evaluation of the spontaneous combustion capability of different ranks of coal

Fuel ◽  
2021 ◽  
Vol 291 ◽  
pp. 120087
Author(s):  
Cai-Ping Wang ◽  
Xiao-Yong Zhao ◽  
Zu-Jin Bai ◽  
Jun Deng ◽  
Chi-Min Shu ◽  
...  
Keyword(s):  
Spontaneous Combustion ◽  
Comprehensive Index ◽  
Index Evaluation

scholarly journals Content Management Systems Performance and Compliance Assessment Based on a Data-Driven Search Engine Optimization Methodology

Information ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 259
Author(s):  
Ioannis Drivas ◽  
Dimitrios Kouis ◽  
Daphne Kyriaki-Manessi ◽  
Georgios Giannakopoulos
Keyword(s):  
Search Engine ◽  
Common Knowledge ◽  
Organizational Structures ◽  
Content Management ◽  
Data Driven ◽  
Management Systems ◽  
Search Engine Optimization ◽  
Optimization Methodology ◽  
Content Management Systems ◽  
The Web

While digitalization of cultural organizations is in full swing and growth, it is common knowledge that websites can be used as a beacon to expand the awareness and consideration of their services on the Web. Nevertheless, recent research results indicate the managerial difficulties in deploying strategies for expanding the discoverability, visibility, and accessibility of these websites. In this paper, a three-stage data-driven Search Engine Optimization schema is proposed to assess the performance of Libraries, Archives, and Museums websites (LAMs), thus helping administrators expand their discoverability, visibility, and accessibility within the Web realm. To do so, the authors examine the performance of 341 related websites from all over the world based on three different factors, Content Curation, Speed, and Security. In the first stage, a statistically reliable and consistent assessment schema for evaluating the SEO performance of LAMs websites through the integration of more than 30 variables is presented. Subsequently, the second stage involves a descriptive data summarization for initial performance estimations of the examined websites in each factor is taking place. In the third stage, predictive regression models are developed to understand and compare the SEO performance of three different Content Management Systems, namely the Drupal, WordPress, and custom approaches, that LAMs websites have adopted. The results of this study constitute a solid stepping-stone both for practitioners and researchers to adopt and improve such methods that focus on end-users and boost organizational structures and culture that relied on data-driven approaches for expanding the visibility of LAMs services.

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