Perception of a new framework for detecting phishing web pages

A New Framework for Intelligent Semantic Web Services Based on GAIVAs

Web Engineering Advancements and Trends ◽

10.4018/978-1-60566-719-5.ch003 ◽

2010 ◽

pp. 38-62

Author(s):

Iglesias Andrés

Keyword(s):

Artificial Intelligence ◽

User Interface ◽

Web Services ◽

Semantic Web ◽

Semantic Web Services ◽

Virtual Agents ◽

Web Pages ◽

Artificial Intelligence Techniques ◽

Intelligent Virtual Agents ◽

New Framework

The Semantic Web has been recently developed to provide end users with suitable tools and strategies to process information from their Web pages. The Intelligent Semantic Web Services is a new approach aimed at extending Semantic Web capabilities for Services by applying Artificial Intelligence techniques while maintaining the good properties of the standard Semantic Web schemes. However, many current Web services neither consider this approach nor include a powerful user-interface and, consequently, are very limited and difficult to use. This paper introduces a new framework for Intelligent Semantic Web Services that overcomes these drawbacks. Our approach is based on the Graphical Autonomous Intelligent Virtual Agents (GAIVAs), virtual agents that exhibit a human-like appearance and behaviour and are able to take intelligent decisions and perform actions without human intervention. To this purpose, the framework comprises a collection of powerful Artificial Intelligence techniques along with a natural and intuitive Graphical User Interface.

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A Study of University Website Content Classification Using Machine Learning

Journal of Physics Conference Series ◽

10.1088/1742-6596/2129/1/012043 ◽

2021 ◽

Vol 2129 (1) ◽

pp. 012043

Author(s):

H R Mohd Sharul ◽

I Nor Azman ◽

M Mohd Su Elya

Keyword(s):

Machine Learning ◽

Machine Learning Techniques ◽

Web Pages ◽

Web Content ◽

Web Based ◽

Content Classification ◽

Learning Techniques ◽

Information Products ◽

Website Content ◽

New Framework

Abstract A university website is a gateway to the institution’s information, products, and services. As websites grow into millions in numbers, it is essential to ensure that the content reflects the needs of its students, staff, and other academic institution as their primary users. This research investigates the development of a new framework that uses machine learning techniques based on webometrics and web usability to classify the web pages of academic websites automatically. The framework briefly introduced how it can help classify web content and eliminate unrelated content and reduce storage space. The findings can also be used to analyse other web-based data to give additional insights that may be beneficial for webometrics studies and identify university website’ characteristics.

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Eccentric Methodology with Optimization to Unearth Hidden Facts of Search Engine Result Pages

Recent Patents on Computer Science ◽

10.2174/2213275911666181115093050 ◽

2019 ◽

Vol 12 (2) ◽

pp. 110-119 ◽

Cited By ~ 3

Author(s):

Jayaraman Sethuraman ◽

Jafar A. Alzubi ◽

Ramachandran Manikandan ◽

Mehdi Gheisari ◽

Ambeshwar Kumar

Keyword(s):

Search Engine ◽

World Wide ◽

Optimization Techniques ◽

Web Pages ◽

Web Page ◽

Search Engine Optimization ◽

The World ◽

Search Engine Result ◽

The Web ◽

New Framework

Background: The World Wide Web houses an abundance of information that is used every day by billions of users across the world to find relevant data. Website owners employ webmasters to ensure their pages are ranked top in search engine result pages. However, understanding how the search engine ranks a website, which comprises numerous web pages, as the top ten or twenty websites is a major challenge. Although systems have been developed to understand the ranking process, a specialized tool based approach has not been tried. Objective: This paper develops a new framework and system that process website contents to determine search engine optimization factors. Methods: To analyze the web page dynamically by assessing the web site content based on specific keywords, elimination method was used in an attempt to reveal various search engine optimization techniques. Conclusion: Our results lead to conclude that the developed system is able to perform a deeper analysis and find factors which play a role in bringing the site on the top of the list.

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ASHA News: New Web Pages for State Telepractice and Ethics Regulations

ASHA Leader ◽

10.1044/leader.an7.18112013.63 ◽

2013 ◽

Vol 18 (11) ◽

pp. 63

Keyword(s):

Web Pages

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Appropriate Targets for Search Advertising as Part of Online Gatekeeping for Suicide Prevention

Crisis ◽

10.1027/0227-5910/a000486 ◽

2018 ◽

Vol 39 (3) ◽

pp. 197-204 ◽

Cited By ~ 1

Author(s):

Hajime Sueki ◽

Jiro Ito

Keyword(s):

Suicide Prevention ◽

Daily Life ◽

Web Pages ◽

Service Users ◽

Online Questionnaire ◽

Consultation Service ◽

Self Disclosure ◽

Search Advertising ◽

Consultation Services ◽

Age Range

Abstract. Background: Gatekeeper training is an effective suicide prevention strategy. However, the appropriate targets of online gatekeeping have not yet been clarified. Aim: We examined the association between the outcomes of online gatekeeping using the Internet and the characteristics of consultation service users. Method: An advertisement to encourage the use of e-mail-based psychological consultation services among viewers was placed on web pages that showed the results of searches using suicide-related keywords. All e-mails received between October 2014 and December 2015 were replied to as part of gatekeeping, and the obtained data (responses to an online questionnaire and the content of the received e-mails) were analyzed. Results: A total of 154 consultation service users were analyzed, 35.7% of whom were male. The median age range was 20–29 years. Online gatekeeping was significantly more likely to be successful when such users faced financial/daily life or workplace problems, or revealed their names (including online names). By contrast, the activity was more likely to be unsuccessful when it was impossible to assess the problems faced by consultation service users. Conclusion: It may be possible to increase the success rate of online gatekeeping by targeting individuals facing financial/daily life or workplace problems with marked tendencies for self-disclosure.

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