Online Mental Training Using WebExcellence

2011 ◽  
pp. 1390-1397
Author(s):  
Emma J. Stodel ◽  
Laura G. Farres ◽  
Colla J. MacDonald
Keyword(s):  
Search Engine ◽  
Sport Psychology ◽  
Mental Training ◽  
Internet Search ◽  
Google Search ◽  
The Web

The idea of providing mental training1 (MT) and sport psychology services online is becoming more prevalent as technology continues to shape education and the Web becomes more popular. In September 2000, an Internet search for “mental training” using the Google search engine identified 11,700 sites (Stodel & Farres, 2000a). An identical search in March 2004 revealed approximately 74,700 sites, representing an increase of almost 650%. Although a dynamic and fully interactive online MT environment does not yet appear to have been realised, it surely will not be long before this happens. In this chapter we highlight the importance of thoughtful design when developing such training and present a framework to guide the development of online MT.

scholarly journals TRENDS: How Internet Search Undermines the Validity of Political Knowledge Measures

2019 ◽  
Vol 73 (1) ◽  
pp. 141-155
Author(s):  
Brianna Smith ◽  
Scott Clifford ◽  
Jennifer Jerit
Keyword(s):  
Search Engine ◽  
Observational Studies ◽  
Search Behavior ◽  
Political Knowledge ◽  
Factual Knowledge ◽  
Internet Search ◽  
Online Surveys ◽  
The Web

Political knowledge is central to understanding citizens’ engagement with politics. Yet, as surveys are increasingly conducted online, participants’ ability to search the web may undermine the validity of factual knowledge measures. Recent research shows this search behavior is common, even when respondents are instructed otherwise. However, we know little about how outside search affects the validity of political knowledge measures. Using a series of experimental and observational studies, we provide consistent evidence that outside search degrades the validity of political knowledge measures. Our findings imply that researchers conducting online surveys need to take steps to discourage and diagnose search engine use.

OPTIMASI RISET KEYWORD DENGAN TEKNIK ALLINTITLLE PADA MESIN PENCARI GOOGLE

2018 ◽  
Vol 1 (1) ◽  
pp. 1-5
Author(s):  
Hengki Tamando Sihotang
Keyword(s):  
Search Engine ◽  
Information Needs ◽  
Research Question ◽  
Online Information ◽  
Web Based ◽  
Development Method ◽  
Government Services ◽  
Search Results ◽  
Google Search ◽  
The Web

Online information needs have evolved in the real direction. These needs include the latest information, government services, and commercial products. The research question is how to describe and optimize keyword research with the allintitle technique on the google search engine. The development method used in this research is the prototype method because it is considered able to be evaluated directly on the user. The system testing is done for 3 months by placing keywords on several websites on Google. The conclusion that can be taken is to use the allintitle technique, the search results for the web are easier to find. And this web-based allintitle technique can overcome the challenges of captcha verification from the Google search engine.   Keywords: Allintitle, Google's Search Engine, Keyword competition.

scholarly journals Quantification of competitive value of documents

2009 ◽  
Vol 57 (5) ◽  
pp. 285-290
Author(s):  
Pavel Šimek ◽  
Jiří Vaněk ◽  
Jan Jarolímek
Keyword(s):  
Search Engine ◽  
Market Share ◽  
Full Text ◽  
Search Engines ◽  
Web Site ◽  
Optimization Techniques ◽  
Text Search ◽  
Full Text Search ◽  
Google Search ◽  
The Web

The majority of Internet users use the global network to search for different information using fulltext search engines such as Google, Yahoo!, or Seznam. The web presentation operators are trying, with the help of different optimization techniques, to get to the top places in the results of fulltext search engines. Right there is a great importance of Search Engine Optimization and Search Engine Marketing, because normal users usually try links only on the first few pages of the fulltext search engines results on certain keywords and in catalogs they use primarily hierarchically higher placed links in each category. Key to success is the application of optimization methods which deal with the issue of keywords, structure and quality of content, domain names, individual sites and quantity and reliability of backward links. The process is demanding, long-lasting and without a guaranteed outcome. A website operator without advanced analytical tools do not identify the contribution of individual documents from which the entire web site consists. If the web presentation operators want to have an overview of their documents and web site in global, it is appropriate to quantify these positions in a specific way, depending on specific key words. For this purpose serves the quantification of competitive value of documents, which consequently sets global competitive value of a web site. Quantification of competitive values is performed on a specific full-text search engine. For each full-text search engine can be and often are, different results. According to published reports of ClickZ agency or Market Share is according to the number of searches by English-speaking users most widely used Google search engine, which has a market share of more than 80%. The whole procedure of quantification of competitive values is common, however, the initial step which is the analysis of keywords depends on a choice of the fulltext search engine.

scholarly journals Analysis of Web Scraping Techniques to Get Keywords Suggestion and Allintitle Automatically from Google Search Engines

Compiler ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 71
Author(s):  
Aris Wahyu Murdiyanto ◽  
Adri Priadana
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Evaluation Result ◽  
Search Engine Optimization ◽  
Web Scraping ◽  
Long Time ◽  
Google Search ◽  
The Web

Keyword research is one of the essential activities in Search Engine Optimization (SEO). One of the techniques in doing keyword research is to find out how many articles titles on a website indexed by the Google search engine contain a particular keyword or so-called "allintitle". Moreover, search engines are also able to provide keywords suggestion. Getting keywords suggestions and allintitle will not be effective, efficient, and economical if done manually for relatively extensive keyword research. It will take a long time to decide whether a keyword is needed to be optimized. Based on these problems, this study aimed to analyze the implementation of the web scraping technique to get relevant keyword suggestions from the Google search engine and the number of "allintitle" that are owned automatically. The data used as an experiment in this test consists of ten keywords, which each keyword would generate a maximum of ten keywords suggestion. Therefore, from ten keywords, it will produce at most 100 keywords suggestions and the number of allintitles. Based on the evaluation result, we got an accuracy of 100%. It indicated that the technique could be applied to get keywords suggestions and allintitle from Google search engines with outstanding accuracy values.

scholarly journals Google Web and Image Search Visibility Data for Online Store

Data ◽  
2019 ◽  
Vol 4 (3) ◽  
pp. 125 ◽  
Author(s):  
Artur Strzelecki
Keyword(s):  
Search Engine ◽  
Web Search ◽  
Country Of Origin ◽  
Image Search ◽  
Domain Name ◽  
Online Store ◽  
Google Search ◽  
Research Domains ◽  
The Web ◽  
Ranking Position

This data descriptor describes Google search engine visibility data. The visibility of a domain name in a search engine comes from search engine optimization and can be evaluated based on four data metrics and five data dimensions. The data metrics are the following: Clicks volume (1), impressions volume (2), click-through ratio (3), and ranking position (4). Data dimensions are as follows: queries that are entered into search engines that trigger results with the researched domain name (1), page URLs from research domains which are available in the search engine results page (2), country of origin of search engine visitors (3), type of device used for the search (4), and date of the search (5). Search engine visibility data were obtained from the Google search console for the international online store, which is visible in 240 countries and territories for a period of 15 months. The data contain 123 K clicks and 4.86 M impressions for the web search and 22 K clicks and 9.07 M impressions for the image search. The proposed method for obtaining data can be applied in any other area, not only in the e-commerce industry.

Evolution of Portals

2011 ◽  
pp. 391-396 ◽  
Author(s):  
Lorna Uden ◽  
Kimmo Salmenjoki
Keyword(s):  
Search Engine ◽  
Web Site ◽  
World Wide ◽  
Historical Approach ◽  
The Public ◽  
The World ◽  
On Line ◽  
Definition Of ◽  
Google Search ◽  
The Web

The word portal came from the Latin word porta, which is translated to gate. Anything that acts as a gateway to anything else is a portal. The portal server acts as gateway to the enterprise in a network. However, there are many different definitions of the word portal. A search of the word using Google search engine yields many thousands of references. Some consider portal to be a new name for a Web site. A portal is an entry point to the World Wide Web (WWW) and therefore, more than what a Web site does. According to Internet 101 , a portal is a Web site linking to another Web site. Sometimes search engines have been referred to as portals. Access companies, such as Microsoft Network (MSN) and America On-Line (AOL), have often been referred to as portals. Although the definition of the word portal is still evolving, the definition we will use is a gateway, and a Web portal can thus be seen as a gateway to the information and services on the Web, more specifically to services on both the public Internet and on corporate intranets. This article aims to take the historical approach based on the development of the Web and examine the factors that have contributed to the evolution of portals. The origin of portals came about because of the need for information organisation. Users need to be provided with coherent and understandable information.

Search Engine Optimization: An Analysis of Rhinoplasty Web sites

2017 ◽  
Vol 33 (06) ◽  
pp. 665-669 ◽  
Author(s):  
Amar Gupta ◽  
Michael Nissan ◽  
Michael Carron ◽  
Giancarlo Zuliani ◽  
Hani Rayess
Keyword(s):  
Search Engine ◽  
Web Sites ◽  
Search Engines ◽  
Web Site ◽  
Third Party ◽  
Site Quality ◽  
Search Engine Optimization ◽  
Facial Plastic ◽  
Google Search ◽  
The Web

AbstractThe Internet is the primary source of information for facial plastic surgery patients. Most patients only analyze information in the first 10 Web sites retrieved. The aim of this study was to determine factors critical for improving Web site traffic and search engine optimization. A Google search of “rhinoplasty” was performed in Michigan. The first 20 distinct Web sites originating from private sources were included. Private was defined as personal Web sites for private practice physicians. The Web sites were evaluated using SEOquake and WooRANK, publicly available programs that analyze Web sites. Factors examined included the presence of social media, the number of distinct pages on the Web site, the traffic to the Web site, use of keywords, such as rhinoplasty in the heading and meta description, average visit duration, traffic coming from search, bounce rate, and the number of advertisements. Readability and Web site quality were also analyzed using the DISCERN and Health on the Net Foundation code principles. The first 10 Web sites were compared with the latter 10 Web sites using Student's t-tests. The first 10 Web sites received a significantly lower portion of traffic from search engines than the second 10 Web sites. The first 10 Web sites also had significantly fewer tags of the keyword “nose” in the meta description of the Web site. The first 10 Web sites were significantly more reliable according to the DISCERN instrument, scoring an average of 2.42 compared with 2.05 for the second 10 Web sites (p = 0.029). Search engine optimization is critical for facial plastic surgeons as it improves online presence. This may potentially result in increased traffic and an increase in patient visits. However, Web sites that rely too heavily on search engines for traffic are less likely to be in the top 10 search results. Web site curators should maintain a wide focus for obtaining Web site traffic, possibly including advertising and publishing information in third party sources such as “RealSelf.”

How well does Google work with Persian documents?

2016 ◽  
Vol 43 (3) ◽  
pp. 316-327 ◽  
Author(s):  
Mohammad Sadeghi ◽  
Jesús Vegas
Keyword(s):  
Information Retrieval ◽  
Search Engine ◽  
Morphological Analysis ◽  
Retrieval System ◽  
Relevant Information ◽  
Information Retrieval System ◽  
Search Results ◽  
Persian Language ◽  
Google Search ◽  
The Web

The performance evaluation of an information retrieval system is a decisive aspect of the measure of the improvements in search technology. The Google search engine, as a tool for retrieving information on the Web, is used by almost 92% of Iranian users. The purpose of this paper is to study Google’s performance in retrieving relevant information from Persian documents. The information retrieval effectiveness is based on the precision measures of the search results done to a website that we have built with the documents of a TREC standard corpus. We asked Google for 100 topics available on the corpus and we compared the retrieved webpages with the relevant documents. The obtained results indicated that the morphological analysis of the Persian language is not fully taken into account by the Google search engine. The incorrect text tokenisation, considering the stop words as the content keywords of a document and the wrong ‘variants encountered’ of words found by Google are the main reasons that affect the relevance of the Persian information retrieval on the Web for this search engine.

scholarly journals As lost as a pun in a corpus: an investigation into noncanonical phraseological occurrences in large corpora and translation

Tradterm ◽  
2021 ◽  
Vol 37 (2) ◽  
pp. 460-487
Author(s):  
Adauri Brezolin
Keyword(s):  
Search Engine ◽  
Corpus Linguistics ◽  
Canonical Forms ◽  
Search Queries ◽  
Data Source ◽  
Fixed Expressions ◽  
Google Search ◽  
The Web

Although it might appear contradictory to investigate noncanonical phraseological combinations in corpora, corpus linguistics research has revealed that they exceed canonical forms in number (Philip 2008). This paper intends to discuss the idea of fixedness by analyzing variant forms of idioms, and if they qualify as wordplay. The Web, our data source, is employed for collecting such noncanonical occurrences in both English and Portuguese using keywords on the Google Search Engine. Our discussion mainly draws on studies relating to fixed phrases (Kjellmer 1991; Granger & Paquot 2008; Tagnin 2013); phraseological skeletons (Renouf & Sinclair 1991; Philip 2008), and idiom transformations (Veisbergs 1997; Barta 2005). Due attention is also given to search queries of nonstandard forms of fixed expressions in corpora (Philip 2008), and the translation of idiom-based wordplay (Veisbergs 1997; Brezolin 2020)

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