Basic Components of a Search Engine

Research on a popular search engine and explain the reasons behind this popularity.

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 search engines, providing system analysis of search engines, and then accentuating the ideal features of Google search engine.

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.

Four Distinctive Features for Comparing the Effectiveness of Search Engines

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

Where, = /E

E=

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 than. 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
= no. of different paths with  clicks

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.

Google: The Ideal Search Engine

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 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 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.

References

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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).