Thesis submitted in fulfilment of the requirements for the degree Magister Technologiae in Information Technology in the Faculty of Informatics and Design at the CAPE PENINSULA UNIVERSITY OF TECHNOLOGY 2007 / The objective of this study was to investigate and report on user preference of Search Engine Optimisation (SEO), versus Pay Per Click (PPC) results. This will assist online advertisers to identify their optimal Search Engine Marketing (SEM) strategy for their specific target market. Research shows that online advertisers perceive PPC as a more effective SEM strategy than SEO. However, empirical evidence exists that PPC may not be the best strategy for online advertisers, creating confusion for advertisers considering a SEM campaign. Furthermore, not all advertisers have the funds to implement a dual strategy and as a result advertisers need to choose between a SEO and PPC campaign. In order for online advertisers to choose the most relevant SEM strategy, it is of importance to understand user perceptions of these strategies. A quantitative research design was used to conduct the study, with the purpose to collect and analyse data. A questionnaire was designed and hosted on a busy website to ensure maximal exposure. The questionnaire focused on how search engine users perceive SEM and their click response towards SEO and PPC respectively. A qualitative research method was also used in the form of an interview. The interview was conducted with representatives of a leading South African search engine, to verify the results and gain experts’ opinions. The data was analysed and the results interpreted. Results indicated that the user perceived relevancy split is 45% for PPC results, and 55% for SEO results, regardless of demographic factors. Failing to invest in either one could cause a significant loss of website traffic. This indicates that advertisers should invest in both PPC and SEO. Advertisers can invest in a PPC campaign for immediate results, and then implement a SEO campaign over a period of time. The results can further be used to adjust a SEM strategy according to the target market group profile of an advertiser, which will ensure maximum effectiveness.

Thesis Submitted in fulfilment of the requirements for the degree MAGISTER TECHNOLOGIAE In BUSINESS INFORMATION SYSTEMS in the FACULTY OF BUSINESS at the CAPE PENINSULA UNIVERSITY OF TECHNOLOGY 2011 / With over a billion Internet users surfing the Web daily in search of information, buying, selling and accessing social networks, marketers focus intensively on developing websites that are appealing to both the searchers and the search engines. Millions of webpages are submitted each day for indexing to search engines. The success of a search engine lies in its ability to provide accurate search results. Search engines’ algorithms constantly evaluate websites and webpages that could violate their respective policies. For this reason some websites and webpages are subsequently blacklisted from their index. Websites are increasingly being utilised as marketing tools, which result in major competition amongst websites. Website developers strive to develop websites of high quality, which are unique and content rich as this will assist them in obtaining a high ranking from search engines. By focusing on websites of a high standard, website developers utilise search engine optimisation (SEO) strategies to earn a high search engine ranking. From time to time SEO practitioners abuse SEO techniques in order to trick the search engine algorithms, but the algorithms are programmed to identify and flag these techniques as spamdexing. Search engines do not clearly explain how they interpret keyword stuffing (one form of spamdexing) in a webpage. However, they regard spamdexing in many different ways and do not provide enough detail to clarify what crawlers take into consideration when interpreting the spamdexing status of a website. Furthermore, search engines differ in the way that they interpret spamdexing, but offer no clear quantitative evidence for the crossover point of keyword dense website text to spamdexing. Scholars have indicated different views in respect of spamdexing, characterised by different keyword density measurements in the body text of a webpage. This raised several fundamental questions that form the basis of this research. This research was carried out using triangulation in order to determine how the scholars, search engines and SEO practitioners interpret spamdexing. Five websites with varying keyword densities were designed and submitted to Google, Yahoo! and Bing. Two phases of the experiment were done and the results were recorded. During both phases almost all of the webpages, including the one with a 97.3% keyword density, were indexed. The aforementioned enabled this research to conclusively disregard the keyword stuffing issue, blacklisting and any form of penalisation. Designers are urged to rather concentrate on usability and good values behind building a website. The research explored the fundamental contribution of keywords to webpage indexing and visibility. Keywords used with or without an optimum level of measurement of richness and poorness result in website ranking and indexing. However, the focus should be on the way in which the end user would interpret the content displayed, rather than how the search engine would react towards the content. Furthermore, spamdexing is likely to scare away potential clients and end users instead of embracing them, which is why the time spent on spamdexing should rather be used to produce quality content.

Search engines have become integral to the way in which we use the Web of today. Not only are they an important real time source of links to relevant information, but they also serve as a starting point to the Web. A veritable treasure trove of the latest news, satellite images, directions from anywhere to anywhere, local traffic updates and global trends ranging from the spread of influenza to which celebrity happens to be the most popular at a particular time. The more popular search engines are collecting incredible amounts of information. In addition to indexing significant portions of the Web they record what hundreds of millions of users around the world are searching for. As more people use a particular search engine, it has the potential to record more information on what is deemed relevant (and in doing so provide better relevance in the future, thereby attracting more users). Unfortunately, the relevance derived from this cycle between the search user and the search engine comes at a cost: privacy. In this work, we take an in depth look at what privacy means within the context of search. We discuss why it is that the search engine must be considered a threat to search privacy. We then investigate potential solutions and eventually propose our own in a bid to enhance search privacy. / Thesis (PhD)--University of Pretoria, 2011. / Computer Science / unrestricted

An essential software development tool, code search engines are expected to provide superior accuracy, usability, and performance. However, prior research has neither (1) summarized, categorized, and compared representative code search engines, nor (2) analyzed the actual expectations that developers have for code search engines. This missing knowledge can empower developers to fully benefit from search engines, academic researchers to uncover promising research directions, and industry practitioners to properly marshal their efforts. This thesis fills the aforementioned gaps by drawing a comprehensive picture of code search engines, including their definition, standard processes, existing solutions, common alternatives, and developers' perspectives. We first study the state of the art in code search engines by analyzing academic papers, industry releases, and open-source projects. We then survey more than a 100 software developers to ascertain their usage of and preferences for code search engines. Finally, we juxtapose the results of our study and survey to synthesize a call-for-action for researchers and industry practitioners to better meet the demands software developers make on code search engines. We present the first comprehensive overview of state-of-the-art code search engines by categorizing and comparing them based on their respective search strategies, applicability, and performance. Our user survey revealed a surprising lack of awareness among many developers w.r.t. code search engines, with a high preference for using general-purpose search engines (e.g., Google) or code repositories (e.g., GitHub) to search for code. Our results also clearly identify typical usage scenarios and sought-after properties of code search engines. Our findings can guide software developers in selecting code search engines most suitable for their programming pursuits, suggest new research directions for researchers, and help programming tool builders in creating effective code search engine solutions. / Master of Science / When developing software, programmers rely on source code search engines to find code snippets related to the programming task at hand. Given their importance for software development, source code engines have become the focus of numerous research and industry projects. However, researchers and developers remain largely unaware of each other's efforts and expectations. As a consequence, developers find themselves struggling to determine which engine would best fit their needs, while researchers remain unaware what developers expect from search engines. This thesis address this problem via a three-pronged approach: (1) it provides a systematic review of the research literature and major engines; (2) it analyzes the results of surveying software developers about their experiences with and expectations for code search engines; (3) it presents actionable insights that can guide future research and industry efforts in code search engines to better meet the needs of software developers.

After completing this tutorial you will be able to access "Google", conduct a simple search, and interpret the search results.

Thesis (MPhil)--Stellenbosch University, 2004. / ENGLISH ABSTRACT: This study investigated Internet search tools / engines to identify desirable features that can be used as a benchmark or standard to evaluate web search engines. In the past, the Internet was thought of as a big spider's web, ultimately connecting all the bits of information. It has now become clear that this is not the case, and that the bow tie analogy is more accurate. This analogy suggests that there is a central core of well-connected pages, with links IN and OUT to other pages, tendrils and orphan pages. This emphasizes the importance of selecting a search tool that is well connected and linked to the central core. Searchers must take into account that not all search tools search the Invisible Web and this will reflect on the search tool selected. Not all information found on the Web and Internet is reliable, current and accurate, and Web information must be evaluated in terms of authority, currency, bias, purpose of the Web site, etc. Different kinds of search tools are available on the Internet, such as search engines, directories, library gateways, portals, intelligent agents, etc. These search tools were studied and explored. A new categorization for online search tools consisting of Intelligent Agents, Search Engines, Directories and Portals / Hubs is suggested. This categorization distinguishes the major differences between the 21 kinds of search tools studied. Search tools / engines consist of spiders, crawlers, robots, indexes and search tool software. These search tools can be further distinguished by their scope, internal or external searches and whether they search Web pages or Web sites. Most search tools operate within a relationship with other search tools, and they often share results, spiders and databases. This relationship is very dynamic. The major international search engines have identifiable search features. The features of Google, Yahoo, Lycos and Excite were studied in detail. Search engines search for information in different ways, and present their results differently. These characteristics are critical to the Recall/Precision ratio. A well-planned search strategy will improve the Precision/Recall ratio and consider the web-user capabilities and needs. Internet search tools/engines is not a panacea for all information needs, and have pros and cons. The Internet search tool evaluation instrument was developed based on desirable features of the major search tools, and is considered a benchmark or standard for Internet search tools. This instrument, applied to three South African search tools, provided insight into the capabilities of the local search tools compared to the benchmark suggested in this study. The study concludes that the local search engines compare favorably with the major ones, but not enough so to use them exclusively. Further research into this aspect is needed. Intelligent agents are likely to become more popular, but the only certainty in the future of Internet search tools is change, change, and change. / AFRIKAANSE OPSOMMING: Hierdie studie het Internetsoekinstrumente/-enjins ondersoek met die doel om gewenste eienskappe te identifiseer wat as 'n standaard kan dien om soekenjins te evalueer. In die verlede is die Internet gesien as 'n groot spinnerak, wat uiteindelik al die inligtingsdeeltjies verbind. Dit het egter nou duidelik geword dat dit glad nie die geval is nie, en dat die strikdas analogie meer akkuraat is. Hierdie analogie stel voor dat daar 'n sentrale kern van goed gekonnekteerde bladsye is, met skakels IN en UIT na ander bladsye, tentakels en weesbladsye. Dit beklemtoon die belangrikheid om die regte soekinstrument te kies, naamlik een wat goed gekonnekteer is, en geskakel is met die sentrale kern van dokumente. Soekers moet in gedagte hou dat nie alle soekenjins in die Onsigbare Web soek nie, en dit behoort weerspieël te word in die keuse van die soekinstrument. Nie alle inligting wat op die Web en Internet gevind word is betroubaar, op datum en akkuraat nie, en Web-inligting moet geëvalueer word in terme van outoriteit, tydigheid, vooroordeel, doel van die Webruimte, ens. Verskillende soorte soekinstrumente is op die Internet beskikbaar, soos soekenjins, gidse, biblioteekpoorte, portale, intelligente agente, ens. Hierdie soekinstrumente is bestudeer en verken. 'n Nuwe kategorisering vir aanlyn soekinstrumente bestaande uit Intelligente Agente, Soekinstrumente, Gidse en Portale/Middelpunte word voorgestel. Hierdie kategorisering onderskei die hoofverskille tussen die 21 soorte soekinstrumente wat bestudeer is. Soekinstrumente/-enjins bestaan uit spinnekoppe, kruipers, robotte, indekse en soekinstrument sagteware. Hierdie soekinstrumente kan verder onderskei word deur hulle omvang, interne of eksterne soektogte en of hulle op Webbladsye of Webruimtes soek. Die meeste soekinstrumente werk in verhouding met ander soekinstrumente, en hulle deel dikwels resultate, spinnekoppe en databasisse. Hierdie verhouding is baie dinamies. Die hoof internasionale soekenjins het soekeienskappe wat identifiseerbaar is. Die eienskappe van Google, Yahoo en Excite is in besonderhede bestudeer. Soekenjins soek op verskillende maniere na inligting, en lê hulle resultate verskillend voor. Hierdie karaktereienskappe is krities vir die Herwinning/Presisie verhouding. 'n Goedbeplande soekstrategie sal die Herwinning/Presisie verhouding verbeter. Internet soekinstrumente/-enjins is nie die wondermiddel vir alle inligtingsbehoeftes nie, en het voor- en nadele. Die Internet soekinstrument evalueringsmeganisme se ontwikkeling is gebaseer op gewenste eienskappe van die hoof soekinstrumente, en word beskou as 'n standaard vir Internet soekinstrumente. Hierdie instrument, toegepas op drie Suid-Afrikaanse soekenjins, het insae verskaf in die doeltreffendheid van die plaaslike soekinstrumente soos vergelyk met die standaard wat in hierdie studie voorgestel word. In die studie word tot die slotsom gekom dat die plaaslike soekenjins gunstig vergelyk met die hoof soekenjins, maar nie genoegsaam sodat hulle eksklusief gebruik kan word nie. Verdere navorsing oor hierdie aspek is nodig. Intelligente Agente sal waarskynlik meer gewild word, maar die enigste sekerheid vir die toekoms van Internet soekinstrumente is verandering, verandering en nogmaals verandering.

Thesis (DTech (Informatics))--Cape Peninsula University of Technology, 2017. / Any e-commerce venture using a website as main shop-front should invest in marketing their website. Previous empirical evidence shows that most Search Engine Marketing (SEM) spending (approximately 82%) is allocated to Pay Per Click (PPC) campaigns while only 12% was spent on Search Engine Optimisation (SEO). The remaining 6% of the total spending was allocated to other SEM strategies. No empirical work was found on how marketing expenses compare when used solely for either the one or the other of the two main types of SEM. In this study, a model will be designed to guide the development of a dual SEM strategy.

Master of Science / Department of Computing and Information Sciences / Doina Caragea / The web contains a massive amount of information and is continuously growing every day. Extracting information that is relevant to a user is an uphill task. Search engines such as Google TM, Yahoo! TM have made the task a lot easier and have indeed made people much more "smarter". However, most of the existing search engines still rely on the traditional keyword-based searching techniques i.e. returning documents that contain the keywords in the query. They do not take the associated semantics into consideration. To incorporate semantics into search, one could proceed in at least two ways. Firstly, we could plunge into the world of "Semantic Web", where the information is represented in formal formats such as RDF, N3 etc which can effectively capture the associated semantics in the documents. Secondly, we could try to explore a new semantic world in the existing structure of World Wide Web (WWW). While the first approach can be very effective when semantic information is available in RDF/N3 formats, for many web pages such information is not readily available. This is why we consider the second approach in this work. In this work, we attempt to capture the semantics associated with a query by rst extracting the concepts relevant to the query. For this purpose, we propose a novel Link Analysis based Concept Extractor (LACE) that extract the concepts associated with the query by exploiting the meta data of a web page. Next, we propose a method to determine relationships between a query and its extracted concepts. Finally, we show how LACE can be used to compute a statistical measure of semantic similarity between concepts. At each step, we evaluate our approach by comparison with other existing techniques (on benchmark data sets, when available) and show that our results are competitive with existing state of the art results or even outperform them.

In multimedia databases, data are images, audio, video, texts, etc. Research interests in these types of databases have increased in the last decade or so, especially with the advent of the Internet and Semantic Web. Fundamental research issues vary from unified data modelling, retrieval of data items and dynamic nature of updates. The thesis builds on findings in Semantic Web and retrieval techniques and explores novel tagging methods for identifying data items. Tagging systems have become popular which enable the users to add tags to Internet resources such as images, video and audio to make them more manageable. Collaborative tagging is concerned with the relationship between people and resources. Most of these resources have metadata in machine processable format and enable users to use free- text keywords (so-called tags) as search techniques. This research references some tagging systems, e.g. Flicker, delicious and myweb2.0. The limitation with such techniques includes polysemy (one word and different meaning), synonymy (different words and one meaning), different lexical forms (singular, plural, and conjugated words) and misspelling errors or alternate spellings. The work presented in this thesis introduces semantic characterization of web resources that describes the structure and organization of tagging, aiming to extend the existing Multimedia Query using similarity measures to cater for collaborative tagging. In addition, we discuss the semantic difficulties of tagging systems, suggesting improvements in their accuracies. The scope of our work is classified as follows: (i) Increase the accuracy and confidence of multimedia tagging systems. (ii) Increase the similarity measures of images by integrating varieties of measures. To address the first shortcoming, we use the WordNet based on a tagging system for social sharing and retrieval of images as a semantic lingual ontology resource. For the second shortcoming we use the similarity measures in different ways to recognise the multimedia tagging system. Fundamental to our work is the novel information model that we have constructed for our computation. This is based on the fact that an image is a rich object that can be characterised and formulated in n-dimensions, each dimension contains valuable information that will help in increasing the accuracy of the search. For example an image of a tree in a forest contains more information than an image of the same tree but in a different environment. In this thesis we characterise a data item (an image) by a primary description, followed by n-secondary descriptions. As n increases, the accuracy of the search improves. We give various techniques to analyse data and its associated query. To increase the accuracy of the tagging system we have performed different experiments on many images using similarity measures and various techniques from VoI (Value of Information). The findings have shown the linkage/integration between similarity measures and that VoI improves searches and helps/guides a tagger in choosing the most adequate of tags.

In this thesis we study a problem that arises in answering boolean queries submitted to a search engine. Usually a search engine stores the set of IDs of documents containing each word in a pre-computed sorted order and to evaluate a query like "computer AND science" the search engine has to evaluate the union of the sets of documents containing the words "computer" and "science". More complex queries will result in more complex set expressions. In this thesis we consider the problem of evaluation of a set expression with union and intersection as operators and ordered sets as operands. We explore properties of comparison-based algorithms for the problem. A <i>proof of a set expression</i> is the set of comparisons that a comparison-based algorithm performs before it can determine the result of the expression. We discuss the properties of the proofs of set expressions and based on how complex the smallest proofs of a set expression <i>E</i> are, we define a measurement for determining how difficult it is for <i>E</i> to be computed. Then, we design an algorithm that is adaptive to the difficulty of the input expression and we show that the running time of the algorithm is roughly proportional to difficulty of the input expression, where the factor is roughly logarithmic in the number of the operands of the input expression.