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.

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.”

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 Search Engine Optimization with Google-Web

2019 ◽  
pp. 227-230
Author(s):  
Pratik C. Jambhale
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Page Rank ◽  
Web Presence ◽  
Search Engine Optimization ◽  
Search Results ◽  
Web Document ◽  
Search Patterns ◽  
User Friendly ◽  
Google Search

Search engine optimization is a technique to take a web document in top search results of a search engine. Web presence Companies is not only an easy way to reach among the target users but it may be profitable for Business is exactly find the target users as of the reason that most of the time user search out with the keywords of their use rather than searching the Company name, and if the Company Website page come in the top positions then the page may be profitable. This work describes the tweaks of taking the page on top position in Google by increasing the Page rank which may result in the improved visibility and profitable deal for a Business. Google is most user-friendly search engine to prove for the all users which give user-oriented results. In addition ,most of other search engines use Google search patterns so we have concentrated on it. So, if a page is Register on Google it Is Display on most of the search engines.

scholarly journals Structuring of Web Pages using XML Framework for Information Filtering

2019 ◽  
Vol 8 (S2) ◽  
pp. 35-38
Author(s):  
Mu. Annalakshmi ◽  
A. Padmapriya
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Information Filtering ◽  
Web Pages ◽  
Video Search ◽  
Search Engine Optimization ◽  
Text Images ◽  
Vast Area ◽  
The Web

Finding the required information in the vast area of web has been increasingly difficult in recent days since the web is overloaded with enormous content in the form of text, images, audio and video. Search engines help in this context to some extent but there are difficulties with them also. This paper proposes a framework in XML for the web pages in results of the search engines which helps in information filtering and search engine optimization.

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.

scholarly journals Big Data Analytics for Search Engine Optimization

2020 ◽  
Vol 4 (2) ◽  
pp. 5 ◽  
Author(s):  
Ioannis C. Drivas ◽  
Damianos P. Sakas ◽  
Georgios A. Giannakopoulos ◽  
Daphne Kyriaki-Manessi
Keyword(s):  
Big Data ◽  
Cultural Heritage ◽  
Search Engine ◽  
Data Analytics ◽  
User Behavior ◽  
Big Data Analytics ◽  
Data Types ◽  
Search Engine Optimization ◽  
The Impact ◽  
The Web

In the Big Data era, search engine optimization deals with the encapsulation of datasets that are related to website performance in terms of architecture, content curation, and user behavior, with the purpose to convert them into actionable insights and improve visibility and findability on the Web. In this respect, big data analytics expands the opportunities for developing new methodological frameworks that are composed of valid, reliable, and consistent analytics that are practically useful to develop well-informed strategies for organic traffic optimization. In this paper, a novel methodology is implemented in order to increase organic search engine visits based on the impact of multiple SEO factors. In order to achieve this purpose, the authors examined 171 cultural heritage websites and their retrieved data analytics about their performance and user experience inside them. Massive amounts of Web-based collections are included and presented by cultural heritage organizations through their websites. Subsequently, users interact with these collections, producing behavioral analytics in a variety of different data types that come from multiple devices, with high velocity, in large volumes. Nevertheless, prior research efforts indicate that these massive cultural collections are difficult to browse while expressing low visibility and findability in the semantic Web era. Against this backdrop, this paper proposes the computational development of a search engine optimization (SEO) strategy that utilizes the generated big cultural data analytics and improves the visibility of cultural heritage websites. One step further, the statistical results of the study are integrated into a predictive model that is composed of two stages. First, a fuzzy cognitive mapping process is generated as an aggregated macro-level descriptive model. Secondly, a micro-level data-driven agent-based model follows up. The purpose of the model is to predict the most effective combinations of factors that achieve enhanced visibility and organic traffic on cultural heritage organizations’ websites. To this end, the study contributes to the knowledge expansion of researchers and practitioners in the big cultural analytics sector with the purpose to implement potential strategies for greater visibility and findability of cultural collections on the Web.

Search Engine Update

2001 ◽  
Vol 1 (3) ◽  
pp. 28-31 ◽  
Author(s):  
Valerie Stevenson
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Search Strategy ◽  
Search Strategies ◽  
Boolean Logic ◽  
Web Searches ◽  
Search Techniques ◽  
Looking Back ◽  
The Web

Looking back to 1999, there were a number of search engines which performed equally well. I recommended defining the search strategy very carefully, using Boolean logic and field search techniques, and always running the search in more than one search engine. Numerous articles and Web columns comparing the performance of different search engines came to different conclusions on the ‘best’ search engines. Over the last year, however, all the speakers at conferences and seminars I have attended have recommended Google as their preferred tool for locating all kinds of information on the Web. I confess that I have now abandoned most of my carefully worked out search strategies and comparison tests, and use Google for most of my own Web searches.

Automatic Keyword Extraction Algorithm and Implementation

2010 ◽  
Vol 44-47 ◽  
pp. 4041-4049 ◽  
Author(s):  
Hong Zhao ◽  
Chen Sheng Bai ◽  
Song Zhu
Keyword(s):  
Search Engine ◽  
Word Frequency ◽  
Search Engines ◽  
Keyword Extraction ◽  
Web Page ◽  
C Language ◽  
Search Engine Optimization ◽  
Page Ranking ◽  
Extraction Algorithm ◽  
A Site

Search engines can bring a lot of benefit to the website. For a site, each page’s search engine ranking is very important. To make web page ranking in search engine ahead, Search engine optimization (SEO) make effect on the ranking. Web page needs to set the keywords as “keywords" to use SEO. The paper focuses on the content of a given word, and extracts the keywords of each page by calculating the word frequency. The algorithm is implemented by C # language. Keywords setting of webpage are of great importance on the information and products

Seek and Ye Shall Find

2011 ◽  
pp. 740-754 ◽  
Author(s):  
Suely Fragoso
Keyword(s):  
Mass Media ◽  
Search Engine ◽  
Mass Distribution ◽  
Search Engines ◽  
Distribution Model ◽  
The Internet ◽  
Information Distribution ◽  
Distribution Mode ◽  
History Of ◽  
The Web

This chapter proposes that search engines apply a verticalizing pressure on the WWW many-to-many information distribution model, forcing this to revert to a distributive model similar to that of the mass media. The argument for this starts with a critical descriptive examination of the history of search mechanisms for the Internet. Parallel to this there is a discussion of the increasing ties between the search engines and the advertising market. The chapter then presents questions concerning the concentration of traffic on the Web around a small number of search engines which are in the hands of an equally limited number of enterprises. This reality is accentuated by the confidence that users place in the search engine and by the ongoing acquisition of collaborative systems and smaller players by the large search engines. This scenario demonstrates the verticalizing pressure that the search engines apply to the majority of WWW users, that bring it back toward the mass distribution mode.

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