Clustering Document based Semantic Similarity System using TFIDF and K-Mean

Ibrahim, Rowaida Khalil; Zeebaree, Subhi R. M.; Jacksi, Karwan; Sadeeq, Mohammed A. M.; Shukur, Hanan M.; Alkhayyat, Ahmed

doi:10.1109/aca52198.2021.9626822

Cited by 10 publications

(10 citation statements)

References 27 publications

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“…Because virtualization technologies are used in fog networks, this deployment has a significant amount of potential for success. This deployment has a significant amount of potential that has not yet been used [50].…”

Section: Background Theorymentioning

confidence: 99%

See 1 more Smart Citation

Web Phishing Detection Using Web Crawling, Cloud Infrastructure and Deep Learning Framework

Abdulrahman¹,

Ahmed²,

Rashid³

et al. 2023

JASTT

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The pandemic of COVID-19 obliges citizens to follow the “work from home “scheme. The Internet is also a powerful channel for social connections. The huge dependency of people on digital media opens doors to fraud. Phishing is a form of cybercrime that is used to rob users of passwords from online banking, e-commerce, online schools, digital markets, and others. Phishers create bogus websites like the original and deliver users spam mails. When an online user visits fake web pages via spam, phishers steal their credentials. As a result, it is important to identify these forms of fraudulent websites until they do any harm to victims. Inspired by the ever-changing existence of phishing websites. This paper reviews the work on Phishing attack detection and aims to examine techniques that mainly detect and help in preventing phishing attacks rather than mitigating them. Here we offered a general overview of the most effective phishing attack detection strategies focused on deep learning.

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Section: Background Theorymentioning

confidence: 99%

“…It is recommended that you begin your investigation of websites that may or may not contain malware by looking through spam emails first since they provide an excellent starting point. On the other side, there is a significant amount of URLs that were acquired via the use of spam emails [53].…”

Section: Background Theorymentioning

confidence: 99%

Web Phishing Detection Using Web Crawling, Cloud Infrastructure and Deep Learning Framework

Abdulrahman¹,

Ahmed²,

Rashid³

et al. 2023

JASTT

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“…Since that time, it has been more popular as a storage provider for several well-known applications, such as SmugMug, Dropbox, and Pinterest. In 2005, the business cloud content management and file sharing service known as Box was first made available [91]. Since cloud storage is built on a similarly virtualized underlying architecture, it is identical to other aspects of cloud computing, including interfaces, almost immediate elasticity and scalability, multi-tenancy, and metered resources.…”

Section: Architecture and Organization Of Cloud And Information Storagementioning

confidence: 99%

Document Clustering in the Age of Big Data: Incorporating Semantic Information for Improved Results

Haji¹,

Al-Zebari²,

Şengür³

et al. 2023

JASTT

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There has been a meteoric rise in the total amount of digital texts as a direct result of the proliferation of internet access. As a direct result of this, document clustering has evolved into a crucial method that must be used in order to successfully extract relevant information from big document collections. When employing the document clustering approach, documents are automatically sorted into groups whose members have a high degree of similarity to one another. These groups are created by applying the document clustering technique. Because they do not take into account the semantic linkages that exist between the texts, traditional clustering approaches are unable to provide an acceptable description of a collection of texts. This is because traditional clustering techniques. Document clusters, in which texts are ordered according to their meaning rather than their use of keywords, have been extensively utilized as a means of overcoming these challenges as a result of the incorporation of semantic information. This has been possible as a result of the fact that document clusters can group together related texts. In this investigation, we looked at a total of 27 distinct papers that were published over the previous five years and categorized the documents based on the semantic similarities that existed between the various pieces. A detailed literature evaluation is included to each and every one of the publications that were selected for further consideration. Comparative research is carried out on a wide variety of evaluation strategies, including as algorithms, similarity metrics, instruments, and processes. Following that, there is a drawn-out discussion that analyzes the similarities and differences between the activities.

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“…It is known as PageRank, and it is the method that is used by the solution in order to deliver a search experience that is more streamlined and better. The distributed [15] web crawler has the capability of continuing to function on a regular basis even in the event that the system experiences a failure or other unanticipated events take place. An advantage that the distributed web crawler has is this particular benefit.…”

Section:  Distributed Crawlermentioning

confidence: 99%

“…Because of the parallelization of the crawling system, the amount of time it takes to download documents is directly related to the amount of time it takes for this service to complete the download. Specifically, this is due to the fact that the length of time required to obtain the contents of the documents is directly influenced by this feature [15].…”

Section:  Parallel Crawlermentioning

confidence: 99%

Distributed Fundamentals based Conducting the Web Crawling Approaches and Types (Focused, Incremental, Distributed, Parallel, Hidden Web, Form Focused and Breadth First) Crawlers

Mehyadin,

Abdulrahman,

Ahmed

et al. 2022

Journal of Smart Internet of Things

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Over the last several years, there has been a significant rise in the number of people getting online and using the internet. Individual hypertext links are available, and any one of them may be used to get access to the resource. There is a variety of hypertext links available. It has been feasible to construct new websites as a result of the growth of crawlers, which has been facilitated by the rise in the number of people who use the internet. Web crawlers are highly evolved search engines that make it simpler for customers to get the information they are searching for on the internet. Web crawlers are also known as web crawlers. In a similar vein, these web crawlers have the potential to be used for more research endeavours in the months and years to come. Furthermore, the information that has been gathered may be used to detect and uncover any connections that are absent, as well as to assess the possibility for expansion inside complicated networks. This can be done by discovering any connections that are missing. The analysis of web crawlers is the primary topic of this study. Topics covered include the architecture of web crawlers, the many types of web crawlers, and the challenges that search engines have while using web crawlers.

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Clustering Document based Semantic Similarity System using TFIDF and K-Mean

Cited by 10 publications

References 27 publications

Web Phishing Detection Using Web Crawling, Cloud Infrastructure and Deep Learning Framework

Web Phishing Detection Using Web Crawling, Cloud Infrastructure and Deep Learning Framework

Document Clustering in the Age of Big Data: Incorporating Semantic Information for Improved Results

Distributed Fundamentals based Conducting the Web Crawling Approaches and Types (Focused, Incremental, Distributed, Parallel, Hidden Web, Form Focused and Breadth First) Crawlers

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