Business Communication and research Standards PDF

Running Head: BUSINESS COMMUNICATION AND REASEARCH STANDARDS
Search Engine
Name
Institution

BUSINESS COMMUNICATION AND REASEARCH STANDARDS 2
Introduction
Levene (2011) defines search engine as “a tool that allows a user to enter keywords
and retrieve information on websites contained in its catalogue or database.” Search engines
are integral part of the electronic commerce operations. In practice, when users post queries
on the search engines, the aim is not usually to search the entire web but to search “the index
of the search engine over the web” (Buddenbrock, 2016). The main factors that limit the user
from searching the entire web are speed, capabilities, and cost (Kent, 2013). Generally,
searching information involves four steps: an internet user fires the query by posting a phrase
or a word in the search box and then the search engine surfs through every page in the
database. Consequently, the search engine accentuates the pertinent web pages, and then
answers to the search are displayed on the Search Engine Result Page (SERP) in accordance
to the order of relevance. Search can be very short but involves sophisticated algorithms that
are running through the whole process.
The basic components of search engine include “web crawler, indexer, and query
processor” (Shah, 2016). Crawling is a programmed process that collects data via web
spiders. Crawlers develop full text index by collecting web pages and listing them in an
engine’s database. Indexing deals with categorizing raw data and organizing it in an
accessible fashion. Search engines adopt sophisticated mathematical equations to rank results
retrieved in order of importance to achieve optimization. There are number of search engines
that online users can employ to access information. However, some are have received more
ratings due to their effectiveness in retrieving information. This paper dissects why Google is
a popular search engine by first identifying ranking criteria of comparing the effectiveness of

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search engines, providing system analysis of search engines, and then accentuating the ideal
features of Google search engine.
Identification of Issues
According to Tarakeswar and Kavitha (2011), web pages are compared based on four
distinctive features: technology, capability, actuality, and the size of the database. Actuality is
the ability of the crawler to update Web pages continuously and periodically. Clarke (2017)
argues that crawling should be a continuous process. Ideal search engine must have up-to-
date database. GoogleBot, the Google web crawler, updates the Web sites every day while
Bing uses MNSbot to update its sites regularly (Buddenbrock, 2016). The second feature is
the size of the database. There is no standardized way of measuring the size of search engine
database. However, the common experiment is by typing a word that is likely to be found in
every page, for instance entering the word ‘the.” Empirical evidence shows that Google has
the most number of pages with the word “the” (Kent, 2013).
The third feature is the capability of the search engine. Most search engines have slots
for basic and advance search fields to enable user find the results. Boolean operators like
AND is used in joining words, for example Samson Delilah= Samson AND Delilah; NOT
and OR are used to show corresponding terms. The main search operators that Google and
Yahoo use are - to remove, + to include, wildcards, and stemming (Tarakeswar and Kavitha,
2011). Google operator has 46 languages for Google while Yahoo has 32. The final feature of
the search engine is the technology. The main aspects as far as technology is concerned are
ranking and speed. Search engines that take longer time to have few numbers of searches.
Speed is vital part of the search engine. Google has Google Instant, a feature that makes it
exceptionally faster by popping out results before you complete typing (Kent, 2013). The
aforementioned features are what make Google an ideal search engine compared to the rest.

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Systematic Analysis
Web is like a directed graph that contains pages that reflects nodes and hyperlinks that
reflect directed edges. Web graph is said to have two interconnected nodes if there is
presence of directed paths between two nodes. Ideally, connectedness is equal to relation and
divides web graph into disjointed components. The sub-graph under the influence of these
components is known as community. When the nodes of the community are combined and
analyse one node, the web-graph will reduce and become acyclic graph— where no more
than one community node can follow the same directed path. This graph is k own as reduced
web-graph (Garoufallou and Emmanouel, 2015). The element of each community node is
represented by ek. The exponential mean of [ek] is
v=∏k
ek ck
Where, ck= ek/E
E= ∑
k
ek
Bearing that the in-degree of community node indicates the appropriateness of the Web, it is
reasonable to accord special importance to that community that has in-degree that is not less
thanv. If a search engine starts from “an arbitrary node” and surfs within the community, the
web crawler will take infinite paths with multiple hyperlinks (Garoufallou and Emmanouel,
2015). This gives the surfer freedom in a community. Freedom is represented by
lim
N → ∞
log 2 PŅ
N
PŅ= no. of different paths with N clicks
Findings: Why Google is Popular search Engine

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Google’s mission is underpinned on organizing the word’s information and making it
“universally accessible and useful” (Buddenbrock, 2016). Google started as a college
research centre in 1995 by Sergey Brin and Larry Page— Stanford University computer
science students. Google has become popular with the internet users due to its accuracy and
simplicity. According to Levy (2011), Google.com is the most frequently visited online site
in the entire world. Google has its head office in Mountain, View California. It also has
offices across the globe.
Google search engine has been updating new features as time goes by. (Buddenbrock,
2016) observes that Google is popular because of simplistic and continuously updating
feature. Computer scientists, engineers, and library professionals are always at the centre of
ensuring that the search engine is updated with quality features and search results with wide
scope of coverage. Another feature that makes Google search engine popular is the presence
of Google scholar (Levy, 2011). This is a beta version that filters search that are related to
academic research. Google search enables academicians to conveniently access relevant
scholarly literature hence aiding their research. Through Google scholar, one can access
books, articles, theses, reviewed articles, abstracts, academic publishers, scholarly
organizations, preprint repositories, universities, and professional societies. The service
enables colleges, students, and librarians to access information from their own library based
on IP address verification. Another unique component of Google search engine is Google
Books (Tarakeswar and Kavitha, 2011). Book search enables the internet users to access the
global information and publish books online.
Another unique feature of the Google search engine is Google Translator (Levy,
2011). This a web page translating facility that uses translation technology to online users to
access information that has been published on other languages. The service if significantly

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important to the library professionals who need to identify different subjects and classifies the
documents. Librarian can access the online abstract of non-English publication in English
language. Additional benefit of Google search engine is that it uses several small servers that
divide searching task effectively so that searches takes very little time (Levy, 2011). Google
search engine also has an ideal speed that delivers results in seconds or less. Google also
displays results by ranking them in order of relevance and objectivity, not based on the
commercial fee. More importantly, Google search engine separates advertisements and
designates them at the top right of the screen labelled “sponsored links” (Tarakeswar and
Kavitha, 2011). Ideally, Google search engine has “power tools,” which makes searching
simpler and effective.
Levy (2011) observes that many search engines are designed to show the headings of
the web pages that they index only while some only read the fifty words of the entire page.
These search engines assume that that the mentioned words are adequate to indicate the
page’s content. However, Google not only index the whole page but also take you through
the whole page, which other search engines usually miss. Besides, Google helps with
correcting misspelt words. When you type words or phrase that are consistent with the
Google search dictionary, you do not just the results of what you intended to search, but you
get the results with corrected spellings. Another unique feature of Google search engine is the
Google map, which provides the online user with directions, locations, and business
information.
Conclusion
The concept of search engines is significant to both scholars, researchers, and
librarians to facilitate their academic activities. Corporate organizations also use Search
Engine Optimization (SEO) to improve their digital marketing. An ideal search engine is the

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one is constantly updating the Web page, is faster, ranks searches in order of relevance, and
has sufficient information database. Based on these factors, the paper has accentuated Google
as one of the popular search engines. Other features that make Google popular include
Google Scholar, Google Book, Google Map, and Google Translator.

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References
Buddenbrock, F. (2016). Search Engine Optimization: Getting to Google’s First Page.
Google It, 195-204. doi:10.1007/978-1-4939-6415-4_5
Clarke, A. (2017). SEO 2017: Learn search engine optimization with smart Internet
marketing strategies.
Garoufallou, & Emmanouel. (2015). Evaluating search engines: A comparative study
between international and Greek SE by Greek librarians. Emerald Group Publishing
Limited.
Kent, P. (2013). Search engine optimization for dummies. Hoboken, NJ: John Wiley & Sons.
Levene, M. (2010). An Introduction to Search Engines and Web Navigation. Hoboken, NJ:
Wiley.
Levy, S. (2011). In the plex: How Google thinks, works, and shapes our lives. New York:
Simon & Schuster.
Lewandowski, D. (2012). Web Search Engine Research. Bingley, U.K: Emerald.
Ortega, J. L., & Ohio Library and Information Network. (2014). Academic Search Engines: A
quantitative outlook. Oxford, UK: Elsevier/Chandos Pub.
Shah, V. (2016). Comparative Study Of Semantic Search Engines. International Journal Of
Engineering And Computer Science. doi:10.18535/ijecs/v4i11.17
Tarakeswar, K., & Kavitha, D. (2011). Search Engines:A Study. Journal of Computer
Applications (JCA), 4(1).