Web 1.0 to Web 3.0 - Evolution of the Web and its various challenges

Nath, Keshab; Dhar, Sourish; Basishtha, Subhash

doi:10.1109/icroit.2014.6798297

Cited by 64 publications

(23 citation statements)

References 4 publications

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“…Some of the key aspects that make the SW very crucial in the near future mentioned by [86] are the social Web where people share their feelings, ideas, and thoughts using the Web 3.0. it is considered as an well-organized and attractive way of connecting people around the globe. Also, Web 3D that is virtual worlds have been very popular for several communities including education and gaming to improve the experience and activities.…”

Section: Technologies In Placementioning

confidence: 99%

Web Evolution - The Shift from Information Publishing to Reasoning

Algosaibi¹,

Albahli²,

Khasawneh³

et al. 2017

IJAIA

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Section: Technologies In Placementioning

confidence: 99%

Web Evolution - The Shift from Information Publishing to Reasoning

Algosaibi¹,

Albahli²,

Khasawneh³

et al. 2017

IJAIA

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show abstract

“…This generation of the web was known as Web 1.0 and only provided one-way communication to allow users to read web pages [1]. As technology advanced, the 2nd generation (Web 2.0), enabled the WWW to become more sophisticated and allowed users to communicate with each other through a read-write networking platform [1]. They were able to generate their own content and to become contributors of the web, instead of passive viewers.…”

Section: Introductionmentioning

confidence: 99%

“…In its infancy, the WWW consisted primarily of, read-only, static Hypertext Markup Language (HTML) web pages. This generation of the web was known as Web 1.0 and only provided one-way communication to allow users to read web pages [1]. As technology advanced, the 2nd generation (Web 2.0), enabled the WWW to become more sophisticated and allowed users to communicate with each other through a read-write networking platform [1].…”

Section: Introductionmentioning

confidence: 99%

“…This transformation has redefined the browser as a vehicle for delivering richer media content, and interactivity, through a fusion of existing technologies, most notably Asynchronous JavaScript and XML (AJAX) [3]. Today, the 3rd generation (Web 3.0) is defined as the semantic web and has changed the web into a language that can be read and categorized by the system rather than humans [1]. This development simplifies human-computer interfaces by attaching machine-readable metadata (information about information) to web content to enable computers to 'understand' the actual/intended meaning of this content as it's processed [4].…”

Section: Introductionmentioning

confidence: 99%

“…The World Wide Web (WWW) is the largest globally connected information media outlet in the world, where users can share, read and write data [1]. In its infancy, the WWW consisted primarily of, read-only, static Hypertext Markup Language (HTML) web pages.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Knowledge extraction using probabilistic reasoning: An artificial neural network approach

Dobbins

Fergus

2015

2015 International Joint Conference on Neural Networks (IJCNN)

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Abstract-The World Wide Web (WWW) has radically changed the way in which we access, generate and disseminate information. Its presence is felt daily and with more internetenabled devices being connected the web of knowledge is growing. We are now moving into era where the WWW is capable of 'understanding' the actual/intended meaning of our content. This is being achieved by creating links between distributed data sources using the Resource Description Framework (RDF). In order to find information in this web of interconnected sources, complex query languages are often employed, e.g. SPARQL. However, this approach is limited as exact query matches are often required. In order to overcome this challenge, this paper presents a probabilistic approach to searching RDF documents. The developed algorithm converts RDF data into a matrix of features and treats searching as a machine learning problem. Using a number of artificial neural network algorithms, a successfully developed prototype has been developed that demonstrates the applicability of the approach. The results illustrate that the Voted Perceptron classifier (VPC), perceptron linear classifier (PERLC) and random neural network classifier (RNNC) performed particularly well, with accuracies of 100%, 98% and 93% respectively.

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Rumor, misinformation among web: A contemporary review of rumor detection techniques during different web waves

Rani

Das

Bhardwaj

2021

Concurrency and Computation

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Summary Sometimes, unverified information is disseminated as if it is true information on social media sites. Most of the times, it goes viral and affects the belief of people and their emotions. Rumors and fake news are the most popular form of false and unconfirmed information. Such news must be identified quickly for preventing its negative impact on society. In the last decade, operational procedures for rumors and false news detection came into existence. This paper provides a holistic view of different web waves from web 1.0 to web 5.0 and their usages. Further, taxonomy describes various malicious information contents at different stages. It discusses features used for classification, publicly available datasets, the rumor detection methods proposed during web 1.0, 2.0, 3.0, 4.0, 5.0 periods, and comprehensive analysis related to various methods and techniques. Numerous research gaps and future directions are illustrated to make online information more trustworthy for knowledge sharing and decision‐making purposes.

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Web 1.0 to Web 3.0 - Evolution of the Web and its various challenges

Cited by 64 publications

References 4 publications

Web Evolution - The Shift from Information Publishing to Reasoning

Web Evolution - The Shift from Information Publishing to Reasoning

Knowledge extraction using probabilistic reasoning: An artificial neural network approach

Rumor, misinformation among web: A contemporary review of rumor detection techniques during different web waves

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