scholarly journals Fusing website usability and search engine optimisation

2014 ◽  
Vol 16 (1) ◽  
Author(s):  
Eugene B. Visser ◽  
Melius Weideman
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Experimental Results ◽  
New Model ◽  
High Ranking ◽  
Website Usability ◽  
The Individual

Background: Most websites, especially those with a commercial orientation, need a high ranking on a search engine for one or more keywords or phrases. The search engine optimisation process attempts to achieve this. Furthermore, website users expect easy navigation, interaction and transactional ability. The application of website usability principles attempts to achieve this. Ideally, designers should achieve both goals when they design websites.Objectives: This research intended to establish a relationship between search engine optimisation and website usability in order to guide the industry. The authors found a discrepancy between the perceived roles of search engines and website usability.Method: The authors designed three test websites. Each had different combinations of usability, visibility and other attributes. They recorded and analysed the conversions and financial spending on these experimental websites. Finally, they designed a model that fuses search engine optimisation and website usability.Results: Initially, it seemed that website usability and search engine optimisation complemented each other. However, some contradictions between the two, based on content, keywords and their presentation, emerged. Industry experts do not acknowledge these contradictions, although they agree on the existence of the individual elements. The new model highlights the complementary and contradictory aspects.Conclusion: The authors found no evidence of any previous empirical experimental results that could confirm or refute the role of the model. In the fast-paced world of competition between commercial websites, this adds value and originality to the websites of organisations whose websites play important roles.

scholarly journals Affective capitalism of knowing and the society of search engine

2016 ◽  
Vol 68 (5) ◽  
pp. 566-588 ◽  
Author(s):  
Isto Huvila
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Design Methodology ◽  
Ways Of Knowing ◽  
Contemporary Society ◽  
Extensive Discussion ◽  
Content Type ◽  
Conceptual Discussion

Purpose The purpose of this paper is to discuss the affective premises and economics of the influence of search engines on knowing and informing in the contemporary society. Design/methodology/approach A conceptual discussion of the affective premises and framings of the capitalist economics of knowing is presented. Findings The main proposition of this text is that the exploitation of affects is entwined in the competing market and emancipatory discourses and counter-discourses both as intentional interventions, and perhaps even more significantly, as unintentional influences that shape the ways of knowing in the peripheries of the regime that shape cultural constellations of their own. Affective capitalism bounds and frames our ways of knowing in ways that are difficult to anticipate and read even from the context of the regime itself. Originality/value In the relatively extensive discussion on the role of affects in the contemporary capitalism, influence of affects on knowing and their relation to search engine use has received little explicit attention so far.

A Study on Web Searching

2004 ◽  
pp. 208-225
Author(s):  
Shanfeng Zhu ◽  
Xiaotie Deng ◽  
Qizhi Fang ◽  
Weimin Zhang
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Web Search ◽  
Experimental Results ◽  
Web Searching ◽  
Search Results ◽  
Total Index ◽  
Depth Study ◽  
Web Search Engines ◽  
The Web

Web search engines are one of the most popular services to help users find useful information on the Web. Although many studies have been carried out to estimate the size and overlap of the general web search engines, it may not benefit the ordinary web searching users, since they care more about the overlap of the top N (N=10, 20 or 50) search results on concrete queries, but not the overlap of the total index database. In this study, we present experimental results on the comparison of the overlap of the top N (N=10, 20 or 50) search results from AlltheWeb, Google, AltaVista and WiseNut for the 58 most popular queries, as well as for the distance of the overlapped results. These 58 queries are chosen from WordTracker service, which records the most popular queries submitted to some famous metasearch engines, such as MetaCrawler and Dogpile. We divide these 58 queries into three categories for further investigation. Through in-depth study, we observe a number of interesting results: the overlap of the top N results retrieved by different search engines is very small; the search results of the queries in different categories behave in dramatically different ways; Google, on average, has the highest overlap among these four search engines; each search engine tends to adopt a different rank algorithm independently.

15. Brand identities, search engines, and secondary markets

2019 ◽  
pp. 390-408
Author(s):  
Andrew Murray
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Brand Identity ◽  
Web Browser ◽  
Secondary Markets ◽  
Domain Names ◽  
Online Branding ◽  
Counterfeit Products ◽  
The Impact

This chapter examines brand identities, search engines, and secondary markets and their operation in the information society. It considers jurisdiction and online trademark disputes, as well as search engine optimization and the role of Google and the impact of its search engine services on brand profile and market presence. The chapter goes on to examine secondary markets and the liability of sellers of counterfeit products for the abuse of trademarks. The chapter concludes with a summary of the changing nature of online branding and the diminishing impact of domain names to cement brand identity, as well as the growing influence of developments to web browser functionality on consumer behaviour.

Users’ Click and Bookmark Based Personalization Using Modified Agglomerative Clustering for Web Search Engine

2017 ◽  
Vol 26 (06) ◽  
pp. 1730002 ◽  
Author(s):  
T. Dhiliphan Rajkumar ◽  
S. P. Raja ◽  
A. Suruliandi
Keyword(s):  
Information Retrieval ◽  
Search Engine ◽  
Search Engines ◽  
Web Search ◽  
Irrelevant Information ◽  
Experimental Results ◽  
Agglomerative Clustering ◽  
Semantic Level ◽  
Web Search Engine ◽  
The Web

Short and ambiguous queries are the major problems in search engines which lead to irrelevant information retrieval for the users’ input. The increasing nature of the information on the web also makes various difficulties for the search engine to provide the users needed results. The web search engine experience the ill effects of ambiguity, since the queries are looked at on a rational level rather than the semantic level. In this paper, for improving the performance of search engine as of the users’ interest, personalization is based on the users’ clicks and bookmarking is proposed. Modified agglomerative clustering is used in this work for clustering the results. The experimental results prove that the proposed work scores better precision, recall and F-score.

scholarly journals Automatically Prospecting Feature for Queries from Their Search Impact

2019 ◽  
Vol 9 (1) ◽  
pp. 180-183
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Experimental Results ◽  
Free Text ◽  
Static System ◽  
Search Queries

We recommend that you compile the duplicate lists in the top search engine results to track the aspects of the query and implement a method known as QDMiner. More specifically, QDMiner extracts free text lists, HTML tags and reregions the top search engine results, combining them with groups according to the products they contain, then line up the blocks and products, depending on how the conversation and products are included in the best results. The recommended approach is generic and does not depend on understanding any area. The main purpose of the extraction side differs from the query recommendations. We recommend a structured solution, described as QDMiner, to trace query aspects immediately by removing and grouping repetitive lists in free text results and HTML tags and repeating search engines. We continue to evaluate the support of the list and discover better search queries by looking for exact similarities between menus and penalizing duplicate lists. Experimental results reveal that there are many listings available and QDMiner can find useful queries. The proposed approach is general and does not depend on understanding a particular area. As a result, it can handle opendomain queries. The query supports. Instead of a static system for your problems, we extract the sides of the uploaded document above each query

scholarly journals Architecture of a Commercialized Search Engine Using Mobile Agents

2019 ◽  
Vol 1 (1) ◽  
Author(s):  
Falah Hassan Ali Al-akashi
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Mobile Agents ◽  
Experimental Results ◽  
Market Place ◽  
Unique Challenge ◽  
Search Engine Optimization ◽  
Search Results

Shopping Search Engine (SSE) implies a unique challenge for validating distinct items available online in market place. For sellers, having a user listing appear number one in search results is crucial. Buyers tend to click on and buy from the listings which appear first. Search engine optimization devotes that goal to influence such challenges. In current shopping search platforms, lots of irrelevant itemsretrieved from their indices; e.g. retrieving accessories of exact items rather than retrieving the itemsitself, regardless the price of item were considered or not. In our proposal, we exploit the drawbacks of current shopping search engines. In another side, users tend to move from shoppers to another searching for appropriate items where the time is crucial for consumers. The main goal of this research is to combine and merge multiple search results retrieved from some popular shopping sellers in a listof relevant items. Experimental results showed that our approach is efficient and robust for retrieving acomplete list of desired items with respect to all users‟ query keywords.

scholarly journals Search Engine Optimization with A/B Testing

2019 ◽  
Vol 8 (2) ◽  
pp. 4484-4488
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Digital Marketing ◽  
High Ranking ◽  
Search Engine Optimization ◽  
Search Results ◽  
The World ◽  
Core Elements

The search engine optimization, or in short- SEO, is the largest speck of digital marketing, often the hardest thing to learn. Since there are so many individual components that make the large picture of what SEO is, people assume one can never fully learn SEO. While this can be considered true, due to the constant changes in the world of digital marketing, breaking SEO down to its core elements, and understanding them all individually, will help user better grasp the overall concept. In this paper we will learn the basics of search engine optimization and page rankings and this report will explain user how to start doing SEO with Google and provide user the basic SEO framework. Search engine optimization (SEO) is a methodology of strategies, techniques and tactics used to increase the amount of visitors to a website by obtaining a high-ranking placement in the search results page of a search engine (SERP) — including Google, Bing, Yahoo and other search engines.

scholarly journals MACHINE LEARNING BASED SEARCH ENGINE WITH CRAWLING, INDEXING AND RANKING

2021 ◽  
Vol 10 (7) ◽  
pp. 76-83
Author(s):  
Anuradha T ◽  
Tayyaba Nousheen
Keyword(s):  
Machine Learning ◽  
World Wide Web ◽  
Search Engine ◽  
Search Engines ◽  
World Wide ◽  
Accurate Result ◽  
Web Pages ◽  
The Web

The web is the heap and huge collection of wellspring of data. The Search Engine are used for retrieving the information from World Wide Web (WWW). Search Engines are helpful for searching user keywords and provide the accurate result in fraction of seconds. This paper proposed Machine Learning based search engine which will give more relevant user searches in the form of web pages. To display the user entered query search engine plays a major role of basic interface. Every site comprises of the heaps of site pages that are being made and sent on the server.

A New Approach

2014 ◽  
pp. 13-41
Keyword(s):  
Social Media ◽  
Technological Changes ◽  
New Approach ◽  
New Model ◽  
The Core ◽  
Women In It ◽  
Women In Technology ◽  
Digital Disruption ◽  
The Individual

We are in new times that call for new ways of thinking. Digital disruption is almost the norm, and the power of social media has shaken governments. The emergence of this new disruptive Social Era demands a new model for framing the cultural, social and structural contexts, and influences on women in IT. Such a model is presented in the “STEMcell” Model, a unique 3D Earth-style visualisation that incorporates the influence of social media in its #SocialIT layer and brings new recognition to the central role of the individual at and as its core. The rules have changed, so when viewing women in technology, it is time to adapt and adopt the new model. It is time to consider the core significance of the individual and the seismic digital disruptions and tectonic technological changes we are experiencing and move towards a new approach. The rules of the new social era are translated into new rules of encouraging women in IT in this chapter. The key is that small, fast, fluid, and distributed will prevail over large, stable, and centralised.

A Study on Web Searching

2008 ◽  
pp. 1926-1937
Author(s):  
Shanfeng Chu ◽  
Xiaotie Deng ◽  
Qizhi Fang ◽  
Weimin Zhang
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Web Search ◽  
Experimental Results ◽  
Web Searching ◽  
Search Results ◽  
Total Index ◽  
Depth Study ◽  
Web Search Engines ◽  
The Web

Web search engines are one of the most popular services to help users find useful information on the Web. Although many studies have been carried out to estimate the size and overlap of the general web search engines, it may not benefit the ordinary web searching users, since they care more about the overlap of the top N (N=10, 20 or 50) search results on concrete queries, but not the overlap of the total index database. In this study, we present experimental results on the comparison of the overlap of the top N (N=10, 20 or 50) search results from AlltheWeb, Google, AltaVista and WiseNut for the 58 most popular queries, as well as for the distance of the overlapped results. These 58 queries are chosen from WordTracker service, which records the most popular queries submitted to some famous metasearch engines, such as MetaCrawler and Dogpile. We divide these 58 queries into three categories for further investigation. Through in-depth study, we observe a number of interesting results: the overlap of the top N results retrieved by different search engines is very small; the search results of the queries in different categories behave in dramatically different ways; Google, on average, has the highest overlap among these four search engines; each search engine tends to adopt a different rank algorithm independently.

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