• International Journal of Knowledge Content Development & Technology
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• v.9 no.3
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• pp.7-22
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• 2019

This Study examines and explores through a web metric ranking analysis of the websites of 22 state universities in Tamil Nadu. It discussed the domain systems of the websites; WISER Web ranking for the year 2016 and 2017. Similarly, the researchers manipulated a new ranking tools for ranking the websites of State universities of Tamil Nadu, According to WISER ranking, Anna University is ranked first with 2469.4 WISER value followed by Tamil Nadu Agricultural University which is ranked second with 4031.4 WISER value. University of Madras is ranked third with 4333.8 WISER values in the year 2017. But when we used the PRIMOEX ranking, Anna University is ranked first with 3653.3 PRIMOEX value followed by Tamil Nadu Agricultural University which is ranked second with 4090.6 PRIMOEX value. Madurai Kamaraj University is ranked third with 4136.1 PRIMOEX values. Alagappa University is ranked fourth with 4956.1 PRIMOEX value and Alagappa University with 6001.9 PRIMOEX value is ranked fifth. It found that PRIMOEX good tool to measure the ranking of websites of state universities of Tamil Nadu.

• International Journal of Advanced Culture Technology
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• v.11 no.2
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• pp.358-365
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• 2023

As the Internet is used as a major channel for marketing and sales, the top ranking of search engine results is becoming a key competitor among websites. Various methods exist to maintain the top ranking of websites in search engines, typically investing heavily in organic coding or search engine optimization. The purpose of this paper, we present the ranking by recognizing factors that should be removed as negative factors when designing a web page in consideration of website visibility (SEO) because if website visibility is not met, the ranking may fall behind or be completely removed from the search engine index. The experiments that recognized and ranked the negative factors of website visibility proposed in this paper were provided through theory and experiments based on the existing website visibility analysis model. The models analyzed in this paper, we expressed or quantified as scores based on the methodology of each model, and 10 items were selected as negative factors through experiments and ranked as high scores. Therefore, when designing a website, it should be considered that the website is not removed from the search engine index as it is designed by excluding high-ranking items, which are negative factors.

• Journal of Community Nutrition
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• v.8 no.1
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• pp.9-15
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• 2006

Health care is one of the most popular reasons for accessing the Internet. Of concern is the amount of information from disreputable sources available on the Internet. A review of websites offering nutrition consulting services suggests sites are controlled by both registered dietitians and non-dietitian professionals marketing themselves as nutrition consultants. The purpose of this study was to investigate structure and content of websites controlled by registered dietitians and nondietitians professionals marketing themselves as nutritionists or nutrition consultants. Internet search queries of 'dietitian', 'dietitian consultant', and 'nutrition consultant' were completed for website selection. Thirty websites controlled by registered dietitians and 10 websites controlled by nutrition consultants were reviewed using an 18-item website evaluation instrument developed for this study. Five evaluators were recruited from the dietetics program at the University of Kentucky. Overall, websites controlled by registered dietitians ranked higher than websites controlled by nutrition consultants in a majority of categories. Sites controlled by registered dietitians ranked statistically higher for the following categories: 'accuracy of information'(p<.0001), 'inclusion of professional resume of owner or primary manager' (p<.05), and 'explanation of the affiliation to externallinks'(p<.05). A majority of sites controlled by both dietitians and nutrition consultants achieved a poor ranking in regards to provision of a legal disclaimer and inclusion of a privacy policy. Prior studies suggest personal privacy is the most important concern for consumers accessing health information on the Internet. Findings from this project will benefit dietitians to assist in development of reputable nutrition related websites.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.272-282
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• 2022

Between 2014 and 2019, the US lost more than 2.1 billion USD to phishing attacks, according to the FBI's Internet Crime Complaint Center, and COVID-19 scam complaints totaled more than 1,200. Phishing attacks reflect these awful effects. Phishing websites (PWs) detection appear in the literature. Previous methods included maintaining a centralized blacklist that is manually updated, but newly created pseudonyms cannot be detected. Several recent studies utilized supervised machine learning (SML) algorithms and schemes to manipulate the PWs detection problem. URL extraction-based algorithms and schemes. These studies demonstrate that some classification algorithms are more effective on different data sets. However, for the phishing site detection problem, no widely known classifier has been developed. This study is aimed at identifying the features and schemes of SML that work best in the face of PWs across all publicly available phishing data sets. The Scikit Learn library has eight widely used classification algorithms configured for assessment on the public phishing datasets. Eight was tested. Later, classification algorithms were used to measure accuracy on three different datasets for statistically significant differences, along with the Welch t-test. Assemblies and neural networks outclass classical algorithms in this study. On three publicly accessible phishing datasets, eight traditional SML algorithms were evaluated, and the results were calculated in terms of classification accuracy and classifier ranking as shown in tables 4 and 8. Eventually, on severely unbalanced datasets, classifiers that obtained higher than 99.0 percent classification accuracy. Finally, the results show that this could also be adapted and outperforms conventional techniques with good precision.

• Journal of the Korean Society for information Management
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• v.18 no.2
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• pp.31-56
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• 2001

The number of websites in Korea is increasing rapidly as demonstrated by more than 510,000websites registered under the ".kr" domain as of the end of December 2000. In order to effectively copewith the deluge of web information and maintain ready access to useful information on the web,utilization and management of web information through websites that have been evaluated and ratedfavorably is becoming increasingly important. As websites now increasingly provide industry-specificinformation, information managers are now finding it essential to meet their specific information needsthrough separation and ranking of useful information from the rest.However, evaluation of industry-specific information requires industry-specific expertise as well asgeneral website evaluation tools. This paper develops a website evaluation model and attempts to rankindustry-specific websites through case studies of previous website evaluation and consultation withexperts in specific industries. Based on the model developed, this paper selects 100 outstanding websitesin 10 areas of construction industry. The research also hypothesizes that, with appropriate modifications,the rating models used for the construction industry can also be applied to other industries for moreefficient information management.e efficient information management.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.2752-2768
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• 2020

Phishing websites can have devastating effects on governmental, financial, and social services, as well as on individual privacy. Currently, many phishing detection solutions are evaluated using small datasets and, thus, are prone to sampling issues, such as representing legitimate websites by only high-ranking websites, which could make their evaluation less relevant in practice. Phishing detection solutions which depend only on the URL are attractive, as they can be used in limited systems, such as with firewalls. In this paper, we present a URL-only phishing detection solution based on a convolutional neural network (CNN) model. The proposed CNN takes the URL as the input, rather than using predetermined features such as URL length. For training and evaluation, we have collected over two million URLs in a massive URL phishing detection (MUPD) dataset. We split MUPD into training, validation and testing datasets. The proposed CNN achieves approximately 96% accuracy on the testing dataset; this accuracy is achieved with URL schemes (such as HTTP and HTTPS) removed from the URL. Our proposed solution achieved better accuracy compared to an existing state-of-the-art URL-only model on a published dataset. Finally, the results of our experiment suggest keeping the CNN up-to-date for better results in practice.

• Information Systems Review
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• v.16 no.3
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• pp.49-68
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• 2014

These days, consumers have increasingly preferred to digital real-time streamlining and downloading to listen to music because this is convenient and affordable for the consumers. Accordingly, sales of music in compact disk formats have steadily declined. In this regards, online digital music has become a new communication channel to listen musics, where digital files can be delivered over various online networks to people's computing devices. The majority of online digital music distributors has Music Recommender Systems for sales of digital music on their websites. Music Recommender Systems are parts of information filtering systems that provide the ratings or preferences that users give to music. Korean online digital music distributors have Music Recommender Systems. But those online music distributors didn't provide any rules or clear procedures that recommend music. Therefore, we raise important questions as follows: "Is Music Recommender Systems Fair?", "What is the impact of Music Recommender Systems on online music rankings and sales?" While previous studies have focused on usefulness of Music Recommender Systems, this study investigates not only fairness of Current Music Recommender Systems but also Relationship between Music Recommender Systems and online Music Charts. This study examines these issues based on Bandwagon effect, ranking effect, Slot effect theories. For our empirical analysis, we selected the most famous five online digital music distributors in terms of market shares. We found that all recommended music is exposed to the top of 'daily music charts' in online digital music distributors' websites. We collected music ranking data and recommended music data from 'daily music chart' during a one month. The result shows that online music recommender systems are not fair, since they mainly recommend particular music that supported by a specific music production company. In addition, the recommended music are always exposed to the top of music ranking charts. We also find that recommended music usually appear at the top 20 ranking charts within one or two days. Also, the most music in the top 50 or 100 ranks are the recommended music. Moreover, recommended music usually remain the ranking charts more than one month while non-recommended music often disappear at the ranking charts within two week. Our study provides an important implication to online music industry. Because music recommender systems and music ranking charts are closely related, music distributors may improperly use their recommender systems to boost the sales of music that related to their own companies. Therefore, online digital music distributor must clearly announce the rules and procedures about music recommender systems for the better music industry.

• International Journal of Knowledge Content Development & Technology
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• v.8 no.3
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• pp.41-52
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• 2018

Digital Library websites plays an important role in dissemination of information of the institution and library resources. It acts as a trustworthy mirror of the institute. To evaluate the library website performance webometrics tools and indicators are required. The aim of the present research is study the webometrics of Digital Libraries of Iranian Universities of Medical Sciences on the Web to determine the amount of the visibility a website and web pages. The URL and link of 42 digital library website is obtained directly by visiting the university's website. To extract the number of indexed web pages (size), rich files have used the Google search engine Also, to extract the number of scientific resources retrieved have used the Google Scholar search engine. To calculate and obtain the number of links received have used the MOZ search engine. Generally, the results indicated that the website of Iranian digital libraries did not have a good performance in term of webometric indexes, and none of them were not rated at all indexes, only some of the websites mentioned in one or two indicators.

• Journal of Information Science Theory and Practice
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• v.8 no.2
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• pp.55-67
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• 2020

Webometric research in the Russian library sector is just beginning to gain momentum. This article examines the experience of webometric research in libraries from the perspective of the global practice. In particular, it highlights a number of foreign works, which may have a special practical value for Russian libraries, and emphasizes important webometrics areas for libraries. The purpose of this study is to research the practical application of key performance indicators (KPIs) abroad and conduct a webometric analysis of the websites of some leading Siberian and Far Eastern scientific libraries based on selected KPIs. The study data were collected with SimilarWeb and other analytical tools. The study revealed that key traffic metrics are the basis of webometric research, and identified available promising groundwork for the purpose of their further testing. The shortcomings in the current state of the websites of the Siberian and Far Eastern scientific libraries were noted. Based on the obtained webometric traffic indicators, the ranking of the Siberian and Far Eastern scientific libraries was made.

• Proceeding of Spring/Autumn Annual Conference of KHA
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• 2005.11a
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• pp.139-142
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• 2005

This study aimed not only to analyze the trend of housing environment design through the advertisements for sale of apartments to be completed after 2006 but also to discuss the future trend of housing environment on the basis of the results of analysis. Building companies used to collect data were limited to those that ranked within the 30th place in the Construction Association of Korea's Contract Ranking from 2001 to 2004. The contens of advertisements appeared on their websites were used. The contents analyzed were also limited to 1) concept and method of design and 2) main advanced systems.