scholarly journals Specialized medical search-engines are no better than general search-engines in sourcing consumer information about androgen deficiency

2003 ◽  
Vol 18 (3) ◽  
pp. 557-561 ◽  
Author(s):  
D. Ilic
Keyword(s):  
Search Engines ◽  
Consumer Information ◽  
Androgen Deficiency ◽  
General Search ◽  
Better Than

scholarly journals Journals in Aging, Geriatrics, and Gerontology: A Survey

2019 ◽  
Author(s):  
Robert J. Wolff ◽  
Hannah L. Bowser
Keyword(s):  
Older People ◽  
Search Engines ◽  
Total Population ◽  
Scholarly Journals ◽  
Predatory Journals ◽  
Broad Field ◽  
Recent Increase ◽  
General Search ◽  
Expected Increase

AbstractAging, geriatrics, gerontology, and related areas are important areas of research as the population of older people increases in relationship to the total population. Researchers in these fields would benefit from guidance regarding sources for publishing and finding relevant scholarly journals and articles. Multiple database sites of journals were searched to provide a list of relevant publications. This list was expanded via perusal of published citation lists and searches in general search engines. A total of 243 journals were identified and examined. Of those journals, 198 journals are currently publishing and 45 journals have ceased publication. In terms of publication medium, 39% of the currently publishing journals are online-only, 4% are print-only and 59% of the journals publish both online and in print. Journals with aging in the title represent 36%, geriatrics 30% and gerontology 23%. Less than 10% have been identified as predatory journals. An expected increase in journals in the broad field of aging is indicated by the 49% of listed titles beginning in 2000 or later. This recent increase in available journals provides a need for the information listed in this paper.

Digital image access: an exploration of the best practices of online resources

2014 ◽  
Vol 32 (1) ◽  
pp. 98-119 ◽  
Author(s):  
Elaine Menard ◽  
Margaret Smithglass
Keyword(s):  
Best Practices ◽  
Image Retrieval ◽  
Search Engines ◽  
Research Project ◽  
Content Type ◽  
Retrieval Systems ◽  
Image Access ◽  
General Search ◽  
High Degree ◽  
Very High

Purpose – The purpose of this paper is to present the results of the first phase of a research project that aims to develop a bilingual interface for the retrieval of digital images. The main objective of this extensive exploration was to identify the characteristics and functionalities of existing search interfaces and similar tools available for image retrieval. Design/methodology/approach – An examination of 159 resources that offer image retrieval was carried out. First, general search functionalities offered by content-based image retrieval systems and text-based systems are described. Second, image retrieval in a multilingual context is explored. Finally, the search functionalities provided by four types of organisations (libraries, museums, image search engines and stock photography databases) are investigated. Findings – The analysis of functionalities offered by online image resources revealed a very high degree of consistency within the types of resources examined. The resources found to be the most navigable and interesting to use were those built with standardised vocabularies combined with a clear, compact and efficient user interface. The analysis also highlights that many search engines are equipped with multiple language support features. A translation device, however, is implemented in only a few search engines. Originality/value – The examination of best practices for image retrieval and the analysis of the real users' expectations, which will be obtained in the next phase of the research project, constitute the foundation upon which the search interface model that the authors propose to develop is based. It also provides valuable suggestions and guidelines for search engine researchers, designers and developers.

Research and Implementation on Personalized Search Engine

2011 ◽  
Vol 467-469 ◽  
pp. 129-133 ◽  
Author(s):  
Qing Wei Zeng ◽  
Jie Jiang
Keyword(s):  
Information System ◽  
Search Engine ◽  
Search Engines ◽  
Rapid Development ◽  
User Feedback ◽  
Personalized Search ◽  
Feedback Information ◽  
General Search

With the rapid development of Internet, how to find useful information rapidly is becoming more and more important. General search engines somewhat satisfy users’ search needs. However, they do not consider users’ interests or background. Search engine will be more personal, intelligent and professional. It is necessary that personalized search engines come to reality. This paper designed and realized personalized search engines system by learning user feedback information. System can be able to optimize searching results and return the results that user is most interested in, also can tell users about other users’ interested modes, in order to make users share searching results with each other and improve the efficiency of searching.

Web Resources on Medical Tourism

2019 ◽  
pp. 174-195
Author(s):  
S. Naseehath
Keyword(s):  
Information Retrieval ◽  
Search Engine ◽  
Search Engines ◽  
Medical Tourism ◽  
Engine Performance ◽  
Link Analysis ◽  
Search Results ◽  
Retrieval Systems ◽  
Information Retrieval Systems ◽  
General Search

Webometric research has fallen into two main categories, namely link analysis and search engine evaluation. Search engines are also used to collect data for link analysis. A set of measurements is proposed for evaluating web search engine performance. Some measurements are adapted from the concepts of recall and precision, which are commonly used in evaluating traditional information retrieval systems. Others are newly developed to evaluate search engine stability, which is unique to web information retrieval systems. Overlapping of search results, annual growth of search results on each search engines, variation of results on search using synonyms are also used to evaluate the relative efficiency of search engines. In this study, the investigator attempts to conduct a webometric study on the topic medical tourism in Kerala using six search engines; these include three general search engines, namely Bing, Google, and Lycos, and three metasearch engines, namely Dogpile, ixquick, and WebCrawler.

Search engine effectiveness using query classification: a study

2016 ◽  
Vol 40 (4) ◽  
pp. 515-528 ◽  
Author(s):  
Sabha Ali ◽  
Sumeer Gul
Keyword(s):  
Search Engines ◽  
Social Networking Sites ◽  
Information Science ◽  
Research Work ◽  
Training Data ◽  
Library And Information Science ◽  
Data Set ◽  
Content Type ◽  
Retrieval Effectiveness ◽  
General Search

Purpose – The purpose of this paper is to highlight the retrieval effectiveness of search engines taking into consideration both precision and relative recall. Design/methodology/approach – The study is based on search engines that are selected on the basis of Alexa (Actionable Analytics for the web) Rank. Alexa listed top 500 sites, namely, search engines, portals, directories, social networking sites, networking tools, etc. But the scope of study is confined to only general search engines on the basis of language which was confined to English. Therefore only two general search engines are selected for the study . Alexa reports Google.com as the most visited website worldwide and Yahoo.com as the fourth most visited website globally. A total of 15 queries were selected randomly from PG students of Department of Library and Information Science during a period of eight days (from May 8 to May 15, 2014) which are classified manually into navigational, informational and transactional queries. However, queries are largely distributed on the two selected search engines to check their retrieval effectiveness as a training data set in order to define some characteristics of each type. Each query was submitted to the selected search engines which retrieved a large number of results but only the first 30 results were evaluated to limit the study in view of the fact that most of the users usually look up under the first hits of a query. Findings – The study estimated the precision and relative recall of Google and Yahoo. Queries using concepts in the field of Library and Information Science were tested and were divided into navigational queries, informational queries and transactional queries. Results of the study showed that the mean precision of Google was high with (1.10) followed by Yahoo with (0.88). While as, mean relative recall of Google was high with (0.68) followed by Yahoo with (0.31), respectively. Research limitations/implications – The study highlights the retrieval effectiveness of only two search engines. Originality/value – The research work is authentic and does not contain any plagiarized work.

Performance evaluation of web search engines in image retrieval: An experimental study

2021 ◽  
pp. 026666692110102
Author(s):  
Mehrdad (Mozaffar) CheshmehSohrabi ◽  
Elham Adnani Sadati
Keyword(s):  
Experimental Study ◽  
Performance Evaluation ◽  
Image Retrieval ◽  
Search Engine ◽  
Search Engines ◽  
Web Search ◽  
Image Search ◽  
Intense Competition ◽  
Significant Difference ◽  
General Search

This experimental study used a checklist to evaluate the performance of seven search engines consisting of four Image General Search Engines (IGSEs) (namely, Google, Yahoo DuckDuckGo and Bing), and three Image Specialized Search Engines (ISSEs) (namely, Flicker, PicSearch, and GettyImages) in image retrieval. The findings indicated that the recall average of Image General Search Engines and Image Specialized Search Engines was found to be 76.32% and 24/51% with the precision average of 82/08% and 32/21%, respectively. As the results showed, Yahoo, Google and DuckDuckGo ranked at the top in image retrieval with no significant difference. However, a remarkable superiority with almost 50% difference was observed between the general and specialized image search engines. It was also found that an intense competition existed between Google, Yahoo and DuckDuckGo in image retrieval. The overall results can provide valuable insights for new search engine designers and users in choosing the appropriate search engines for image retrieval. Moreover, the results obtained through the applied equations could be used in assessing and evaluating other search tools, including search engines.

Factors influencing search engine usage behavior

2018 ◽  
Vol 46 (1) ◽  
pp. 1-10
Author(s):  
Yi Li ◽  
Zhihui Yuan ◽  
Yujie Li ◽  
Jing Liu
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Contextual Factors ◽  
Individual Factors ◽  
Negative Experience ◽  
Beneficial Effects ◽  
Factors Influencing ◽  
Usage Behavior ◽  
General Search ◽  
Specific Search

We analyzed the effect of individual factors, contextual factors, and perception of search engine advertising on users' search engine usage behavior. The sample comprised 404 Chinese who used search engines in the context of their paid employment. Results showed that (a) perceived search skills and perceived search engine reliance significantly and positively impacted users' general search engine usage, (b) perceived advertising clutter reduced the beneficial effects of perceived search skills on users' general search engine usage, (c) users with higher perceived search engine reliance preferred search engines to other online search methods, and (d) prior negative experience reduced the positive link between perceived search engine reliance and users' specific search engine usage. Our findings suggest that search engine designers and operators should focus on individual and contextual factors influencing search engine usage behavior, and should consider users' perception of advertising on search engine programs.

scholarly journals Hit count estimate variability for website-specific queries in search engines

2018 ◽  
Vol 70 (2) ◽  
pp. 192-213 ◽  
Author(s):  
Cristina I. Font-Julian ◽  
José-Antonio Ontalba-Ruipérez ◽  
Enrique Orduña-Malea
Keyword(s):  
Search Engines ◽  
Design Methodology ◽  
Threshold Value ◽  
Content Type ◽  
Future Studies ◽  
Discriminating Power ◽  
General Search ◽  
And Performance ◽  
Practical Implications ◽  
Count Estimation

Purpose The purpose of this paper is to determine the effect of the chosen search engine results page (SERP) on the website-specific hit count estimation indicator. Design/methodology/approach A sample of 100 Spanish rare disease association websites is analysed, obtaining the website-specific hit count estimation for the first and last SERPs in two search engines (Google and Bing) at two different periods in time (2016 and 2017). Findings It has been empirically demonstrated that there are differences between the number of hits returned on the first and last SERP in both Google and Bing. These differences are significant when they exceed a threshold value on the first SERP. Research limitations/implications Future studies considering other samples, more SERPs and generating different queries other than website page count (<site>) would be desirable to draw more general conclusions on the nature of quantitative data provided by general search engines. Practical implications Selecting a wrong SERP to calculate some metrics (in this case, website-specific hit count estimation) might provide misleading results, comparisons and performance rankings. The empirical data suggest that the first SERP captures the differences between websites better because it has a greater discriminating power and is more appropriate for webometric longitudinal studies. Social implications The findings allow improving future quantitative webometric analyses based on website-specific hit count estimation metrics in general search engines. Originality/value The website-specific hit count estimation variability between SERPs has been empirically analysed, considering two different search engines (Google and Bing), a set of 100 websites focussed on a similar market (Spanish rare diseases associations), and two annual samples, making this study the most exhaustive on this issue to date.

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