Search

Purpose – The purpose of this paper is to estimate Google search engine’s ranking function from a search engine optimization (SEO) perspective. Design/methodology/approach – The paper proposed an estimation function that defines the query match score of a search result as the weighted sum of scores from a limited set of factors. The search results for a query are re-ranked according to the query match scores. The effectiveness was measured by comparing the new ranks with the original ranks of search results. Findings – The proposed method achieved the best SEO effectiveness when using the top 20 search results for a query. The empirical results reveal that PageRank (PR) is the dominant factor in Google ranking function. The title follows as the second most important, and the snippet and the URL have roughly equal importance with variations among queries. Research limitations/implications – This study considered a limited set of ranking factors. The empirical results reveal that SEO effectiveness can be assessed by a simple estimation of ranking function even when the ranks of the new and original result sets are quite dissimilar. Practical implications – The findings indicate that web marketers should pay particular attention to a webpage’s PR, and then place the keyword in URL, the page title, and snippet. Originality/value – There have been ongoing concerns about how to formulate a simple strategy that can help a website get ranked higher in search engines. This study provides web marketers much needed empirical evidence about a simple way to foresee the ranking success of an SEO effort.

PurposeThe purpose of this paper to investigate the effectiveness of selected search features in the major English and Chinese search engines and compare the search engines’ retrieval effectiveness.Design/approach/methodologyThe search engines Google, Google China, and Baidu were selected for this study. Common search features such as title search, basic search, exact phrase search, PDF search, and URL search, were identified and used. Search results from using the five features in the search engines were collected and compared. One‐way ANOVA and regression analysis were used to compare the retrieval effectiveness of the search engines.FindingsIt was found that Google achieved the best retrieval performance with all five search features among the three search engines. Moreover Google achieved the best webpage ranking performance.Practical implicationsThe findings of this study improve the understanding of English and Chinese search engines and the differences between them in terms of search features, and can be used to assist users in choosing appropriate and effective search strategies when they search for information on the internet.Originality/valueThe original contributions of this paper are that the Chinese and English search engines in both languages are compared for retrieval effectiveness. Five search features were evaluated, compared, and analysed in the two different language environments by using the discounted cumulative gain method.

PurposeThe use of search engines has become increasingly common. While Google has an overwhelming majority of the market share, new and innovative search techniques are being developed. An example of these is the clustering interface used by a number of search engines, whereby results are grouped and visualised according to categories. The purpose of this paper is to examine user perceptions and experience of using clustering.Design/methodology/approachIn total, 12 Palmerston North City Library (New Zealand) staff members and patrons were recruited and the data were gathered through both observations of a search using a clustering search engine (Carrot2Clustering) and via semi‐structured interviews. The data were analysed according to four themes: features, look and feel, results and clusters.FindingsThe findings from this study revealed that the use of clusters can assist users in the search process in several ways. Evidence was also found to support previous research indicating the importance of labelling the clusters.Originality/valueThis exploratory research provides some insights into users' perceived cognitive load in using a clustering search engine as compared to using a list‐based search engine. The authors explored how searchers compare their overall experience of using clustering search engines to using traditional list‐based engines and the extent to which the clustering presentation influences the progression of a search. The authors also examined the extent to which searchers make use of the feedback a clustering search engine provides to refine, rephrase or redefine their initial search.

PurposeThe aim of this paper is to develop a methodology for assessing search results retrieved from different sources.Design/methodology/approachThis is a two phase method, where in the first stage users select and rank the ten best search results from a randomly ordered set. In the second stage they are asked to choose the best pre‐ranked result from a set of possibilities. This two‐stage method allows users to consider each search result separately (in the first stage) and to express their views on the rankings as a whole, as they were retrieved by the search provider. The method was tested in a user study that compared different country‐specific search results of Google and Live Search (now Bing). The users were Israelis and the search results came from six sources: Google Israel, Google.com, Google UK, Live Search Israel, Live Search US and Live Search UK. The users evaluated the results of nine pre‐selected queries, created their own preferred ranking and picked the best ranking from the six sources.FindingsThe results indicate that the group of users in this study preferred their local Google interface, i.e. Google succeeded in its country‐specific customisation of search results. Live Search was much less successful in this aspect.Research limitations/implicationsSearch engines are highly dynamic, thus the findings of the case study have to be viewed cautiously.Originality/valueThe main contribution of the paper is a two‐phase methodology for comparing and evaluating search results from different sources.

PurposeThe purpose of this paper is to introduce two new automatic methods for evaluating the performance of search engines. The reported study uses the methods to experimentally investigate which search engine among three popular search engines (Ask.com, Bing and Google) gives the best performance.Design/methodology/approachThe study assesses the performance of three search engines. For each one the weighted average of similarity degrees between its ranked result list and those of its metasearch engines is measured. Next these measures are compared to establish which search engine gives the best performance. To compute the similarity degree between the lists two measures called the “tendency degree” and “coverage degree” are introduced; the former assesses a search engine in terms of results presentation and the latter evaluates it in terms of retrieval effectiveness. The performance of the search engines is experimentally assessed based on the 50 topics of the 2002 TREC web track. The effectiveness of the methods is also compared with human‐based ones.FindingsGoogle outperformed the others, followed by Bing and Ask.com. Moreover significant degrees of consistency – 92.87 percent and 91.93 percent – were found between automatic and human‐based approaches.Practical implicationsThe findings of this work could help users to select a truly effective search engine. The results also provide motivation for the vendors of web search engines to improve their technology.Originality/valueThe paper focuses on two novel automatic methods to evaluate the performance of search engines and provides valuable experimental results on three popular ones.

PurposeThe purpose of the paper is to evaluate the performance and efficiency of the five most used search engines, i.e. Google, Yahoo!, Live, Ask, and AOL, in retrieving internet resources at specific points of time using a large number of complex queries.Design/methodology/approachIn order to examine the performance of the five search engines, five sets of experiments were conducted using 50 complex queries within two different time frames. The data were evaluated using Excel and SPSS software.FindingsThe paper results highlight the fact that different web search engines, which use different technology to find and present web information, yield different first page search results. The overall analysis of the findings of different measures reveals that Google has a significantly higher rate of performance in retrieving web resources as compared with the other four search engines. Yahoo! is the second best in terms of retrieval performance. The other three search engines did not performed satisfactorily compared with Google and Yahoo!Originality/valueThe paper will provide important insight into the effectiveness of major search engines and their ability to retrieve relevant internet resources. This paper has produced key findings that are important for all web search engine users and researchers, and the web industry. The findings will also assist search companies to improve their services.

PurposeThe purpose of this paper is to present a new method for evaluating the performance of metasearch engines (MSEs), which was used in the reported study to investigate which of eight popular MSEs (Clusty, Dogpile, Excite, Mamma, MetaCrawler, Search.com, WebCrawler and Webfetch) is the best.Design/methodology/approachThis research evaluated the performance of eight MSEs. For each MSE the average of closeness degrees between its ranked result list and those of its underlying search engines (SEs) was measured. Next, these measures were compared to each other to determine which MSE gives the best performance. Furthermore the experiment was repeated ten times with ten different queries to reach a stable result.FindingsThe findings revealed that Dogpile outperformed all the others, followed by MetaCrawler, Excite, Webfetch and then Mamma. MetaCrawler and WebCrawler had almost the same performance and occupied the next positions. Clusty and Search.com performed poorly in comparison to the others.Practical implicationsThe findings of this research would be useful for MSE designers as well as helping the numerous users of MSEs to choose a truly effective one.Originality/valueThis paper provides a novel method for assessing the performance of MSEs and valuable experimental results on eight popular ones.

PurposeThe purpose of this paper is to discuss how many web‐wide search engines are actually needed.Design/methodology/approachThis paper was researched by testing and reviewing different search engines and studying comparative papers about the popularity of web‐wide search engines.FindingsThe author tests and reviews the new search engine Cuil, and discusses its ability as a search engine, with varying results. The paper also compares this new search engine to other more favourable search engines.Originality/valueThe paper provides insight into the requirements of new search engines and whether there is any need for more search engines within the world wide web.

PurposeThis paper aims to understand how students experience the search tools Google Scholar and Metalib and the role of prior instruction.Design/methodology/approachA total of 32 undergraduate students searched academic articles for their thesis work. Searches were recorded using Morae software and were analysed along with the number of articles saved and responses to a questionnaire. All searched with both tools. Half of the students received training before searching.FindingsGoogle Scholar performed better in almost all measures. Training had a positive effect on the amount and quality of articles saved. Responses to Google Scholar were more positive than to Metalib. However, the students were not overwhelmingly enthusiastic about either of the tools. Research limitations/implications – Each Metalib implementation is to some extent unique, which limits the extent to which results can be generalised to other implementations.Practical implicationsTraining is valuable for both tools. The user interface to Metalib does not conform with students' expectations and needs further improvement. Both tools strive to be a first alternative search tool for academic literature but neither performed well enough in this study to recommend it to be used in that role in an academic library setting.Originality/valueThese tools are important to academic libraries but few user studies have been published, particularly on Google Scholar. To one's knowledge no other user study on these tools has looked at the effects of instruction.

PurposeThe purpose of this study is to investigate whether question and keyword‐format queries are more successfully processed by search engines encouraging answers to searching and keyword‐format querying, respectively. This study aims to investigate whether web user characteristics and choice of search engine affects the relevancy scores and precision of the results.Design/methodology/approachThe results of two search engines, Google and AskJeeves, were compared for question and keyword‐format queries. It was observed that AskJeeves was slightly more successful in processing question‐format queries, but this finding was not statistically supported. However, Google provided results on keyword‐format queries and the entire set of queries, which were statistically superior to those of AskJeeves.FindingsAnalysis of variance (ANOVA) showed that the age of web user is not as affective on the relevancy score and precision of results as other factors. Interactions of the main factors were also affective on the relevancy scores and precision, meaning that the different combinations of various factors cause a synergy in terms of relevancy scores and precision.Research limitations/implicationsThis was a preliminary work on the effect of user characteristics on comprehension and evaluation of search query results. Future work includes expanding this study to include more web user characteristics, more levels of the web user characteristics, and inclusion of more search engines.Originality/valueThe findings of this study provide statistical proof for the relationship between the characteristics of web users, choice of search engine and the relevancy scores and precision of search results.

Search engines usually offer a date‐restricted search on their advanced search pages. But determining the actual update of a web page is not without problems. Conducts a study testing date‐restricted queries on the search engines Google, Teoma and Yahoo! Finds that these searches fail to work properly in the engines examined. Finally, discusses implications of this for further research and search engine development.

This paper describes an investigation of 20 different meta‐search engines. Their features were characterised and classified into six distinct categories based on their functionality and use. The most used features and unique features were specified and explained in detail. The findings of this study will benefit both meta‐search‐engine developers and ordinary search users.