Spam 2.0 State of the Art

2012 ◽  
Vol 4 (1) ◽  
pp. 17-36 ◽  
Author(s):  
Pedram Hayati ◽  
Vidyasagar Potdar
Keyword(s):  
Early Detection ◽  
Web 2.0 ◽  
Social Networking ◽  
State Of The Art ◽  
The State ◽  
Online Forums ◽  
Mass Content ◽  
Social Networking Websites ◽  
Comprehensive Survey

Spam 2.0 is defined as the propagation of unsolicited, anonymous, mass content to infiltrate legitimate Web 2.0 applications. A fake eye-catching profile in social networking websites, a promotional review, a response to a thread in online forums with unsolicited content, or a manipulated Wiki page are examples of Spam 2.0. In this paper, the authors provide a comprehensive survey of the state-of-the-art, detection-based, prevention-based and early-detection-based Spam 2.0 filtering methods.

Spam 2.0 State of the Art

2013 ◽  
pp. 103-121
Author(s):  
Pedram Hayati ◽  
Vidyasagar Potdar
Keyword(s):  
Early Detection ◽  
Web 2.0 ◽  
Social Networking ◽  
State Of The Art ◽  
The State ◽  
Online Forums ◽  
Mass Content ◽  
Social Networking Websites ◽  
Comprehensive Survey

Spam 2.0 is defined as the propagation of unsolicited, anonymous, mass content to infiltrate legitimate Web 2.0 applications. A fake eye-catching profile in social networking websites, a promotional review, a response to a thread in online forums with unsolicited content, or a manipulated Wiki page are examples of Spam 2.0. In this paper, the authors provide a comprehensive survey of the state-of-the-art, detection-based, prevention-based and early-detection-based Spam 2.0 filtering methods.

scholarly journals A Systematic Review of Recommender Systems and Their Applications in Cybersecurity

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5248
Author(s):  
Aleksandra Pawlicka ◽  
Marek Pawlicki ◽  
Rafał Kozik ◽  
Ryszard S. Choraś
Keyword(s):  
Systematic Review ◽  
Recommender Systems ◽  
Recommender System ◽  
State Of The Art ◽  
The State ◽  
Advantages And Disadvantages ◽  
Comprehensive Survey ◽  
Security Concerns ◽  
Valuable Role

This paper discusses the valuable role recommender systems may play in cybersecurity. First, a comprehensive presentation of recommender system types is presented, as well as their advantages and disadvantages, possible applications and security concerns. Then, the paper collects and presents the state of the art concerning the use of recommender systems in cybersecurity; both the existing solutions and future ideas are presented. The contribution of this paper is two-fold: to date, to the best of our knowledge, there has been no work collecting the applications of recommenders for cybersecurity. Moreover, this paper attempts to complete a comprehensive survey of recommender types, after noticing that other works usually mention two–three types at once and neglect the others.

The state of the art on buffer allocation problem: a comprehensive survey

2012 ◽  
Vol 25 (3) ◽  
pp. 371-392 ◽  
Author(s):  
Leyla Demir ◽  
Semra Tunali ◽  
Deniz Tursel Eliiyi
Keyword(s):  
State Of The Art ◽  
The State ◽  
Allocation Problem ◽  
Buffer Allocation ◽  
Comprehensive Survey

Technical Details and Educational Applications for Virtual Reality Technologies

2021 ◽  
pp. 74-95
Author(s):  
Yongzhi Wang
Keyword(s):  
Higher Education ◽  
Virtual Reality ◽  
Learning Process ◽  
State Of The Art ◽  
The State ◽  
High Quality ◽  
Comprehensive Survey ◽  
Technical Details ◽  
Educational Applications ◽  
Teaching Learning

The application of virtual reality (VR) in higher education has drawn attention. Understanding the state of the art for VR technologies helps educators identify appropriate applications and develop a high-quality engaging teaching-learning process. This chapter provides a comprehensive survey of current hardware and software supports on VR. Secondly, important technical metrics in VR technology are considered with comparisons of different VR devices using identified metrics. Third, there is a focus on software tools and an explore of various development frameworks, which facilitate the implementation of VR applications. With this information as a foundation, there is a VR use in higher education. Finally, there is a discussion of VR applications that can be potentially used in education.

scholarly journals A Survey of Collaborative Filtering Techniques

2009 ◽  
Vol 2009 ◽  
pp. 1-19 ◽  
Author(s):  
Xiaoyuan Su ◽  
Taghi M. Khoshgoftaar
Keyword(s):  
Collaborative Filtering ◽  
Recommender Systems ◽  
Privacy Protection ◽  
State Of The Art ◽  
Predictive Performance ◽  
The State ◽  
Data Sparsity ◽  
Research And Practice ◽  
Model Based ◽  
Comprehensive Survey

As one of the most successful approaches to building recommender systems, collaborative filtering (CF) uses the known preferences of a group of users to make recommendations or predictions of the unknown preferences for other users. In this paper, we first introduce CF tasks and their main challenges, such as data sparsity, scalability, synonymy, gray sheep, shilling attacks, privacy protection, etc., and their possible solutions. We then present three main categories of CF techniques: memory-based, model-based, and hybrid CF algorithms (that combine CF with other recommendation techniques), with examples for representative algorithms of each category, and analysis of their predictive performance and their ability to address the challenges. From basic techniques to the state-of-the-art, we attempt to present a comprehensive survey for CF techniques, which can be served as a roadmap for research and practice in this area.

scholarly journals Deep Learning Approach for Automatic Microaneurysms Detection

Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 542
Author(s):  
Muhammad Mateen ◽  
Tauqeer Safdar Malik ◽  
Shaukat Hayat ◽  
Musab Hameed ◽  
Song Sun ◽  
...  
Keyword(s):  
Diabetic Retinopathy ◽  
Deep Learning ◽  
Early Detection ◽  
Sensitivity And Specificity ◽  
Classification Accuracy ◽  
Vision Loss ◽  
State Of The Art ◽  
The State ◽  
Learning Approach ◽  
Manual Analysis

In diabetic retinopathy (DR), the early signs that may lead the eyesight towards complete vision loss are considered as microaneurysms (MAs). The shape of these MAs is almost circular, and they have a darkish color and are tiny in size, which means they may be missed by manual analysis of ophthalmologists. In this case, accurate early detection of microaneurysms is helpful to cure DR before non-reversible blindness. In the proposed method, early detection of MAs is performed using a hybrid feature embedding approach of pre-trained CNN models, named as VGG-19 and Inception-v3. The performance of the proposed approach was evaluated using publicly available datasets, namely “E-Ophtha” and “DIARETDB1”, and achieved 96% and 94% classification accuracy, respectively. Furthermore, the developed approach outperformed the state-of-the-art approaches in terms of sensitivity and specificity for microaneurysms detection.

scholarly journals Assuring the Machine Learning Lifecycle

2021 ◽  
Vol 54 (5) ◽  
pp. 1-39
Author(s):  
Rob Ashmore ◽  
Radu Calinescu ◽  
Colin Paterson
Keyword(s):  
Machine Learning ◽  
Iterative Process ◽  
State Of The Art ◽  
The State ◽  
Enabling Technology ◽  
Safety Critical ◽  
Wide Range ◽  
Comprehensive Survey ◽  
Intended Use

Machine learning has evolved into an enabling technology for a wide range of highly successful applications. The potential for this success to continue and accelerate has placed machine learning (ML) at the top of research, economic, and political agendas. Such unprecedented interest is fuelled by a vision of ML applicability extending to healthcare, transportation, defence, and other domains of great societal importance. Achieving this vision requires the use of ML in safety-critical applications that demand levels of assurance beyond those needed for current ML applications. Our article provides a comprehensive survey of the state of the art in the assurance of ML , i.e., in the generation of evidence that ML is sufficiently safe for its intended use. The survey covers the methods capable of providing such evidence at different stages of the machine learning lifecycle , i.e., of the complex, iterative process that starts with the collection of the data used to train an ML component for a system, and ends with the deployment of that component within the system. The article begins with a systematic presentation of the ML lifecycle and its stages. We then define assurance desiderata for each stage, review existing methods that contribute to achieving these desiderata, and identify open challenges that require further research.

Recent Advances in 3D Human Pose Estimation: From Optimization to Implementation and Beyond

2022 ◽  
Author(s):  
Jielu Yan ◽  
MingLiang Zhou ◽  
Jinli Pan ◽  
Meng Yin ◽  
Bin Fang
Keyword(s):  
Real Time ◽  
Pose Estimation ◽  
Recent Progress ◽  
State Of The Art ◽  
The State ◽  
Human Pose Estimation ◽  
Estimation Techniques ◽  
Comprehensive Survey ◽  
Human Pose ◽  
3D Human Pose Estimation

3D human pose estimation describes estimating 3D articulation structure of a person from an image or a video. The technology has massive potential because it can enable tracking people and analyzing motion in real time. Recently, much research has been conducted to optimize human pose estimation, but few works have focused on reviewing 3D human pose estimation. In this paper, we offer a comprehensive survey of the state-of-the-art methods for 3D human pose estimation, referred to as pose estimation solutions, implementations on images or videos that contain different numbers of people and advanced 3D human pose estimation techniques. Furthermore, different kinds of algorithms are further subdivided into sub-categories and compared in light of different methodologies. To the best of our knowledge, this is the first such comprehensive survey of the recent progress of 3D human pose estimation and will hopefully facilitate the completion, refinement and applications of 3D human pose estimation.

scholarly journals COMPENDIUM: a text summarisation tool for generating summaries of multiple purposes, domains, and genres

2012 ◽  
Vol 19 (2) ◽  
pp. 147-186 ◽  
Author(s):  
ELENA LLORET ◽  
MANUEL PALOMAR
Keyword(s):  
Web 2.0 ◽  
State Of The Art ◽  
The State ◽  
Textual Entailment ◽  
Oriented Approach ◽  
The Web

AbstractIn this paper, we present a Text Summarisation tool, compendium, capable of generating the most common types of summaries. Regarding the input, single- and multi-document summaries can be produced; as the output, the summaries can be extractive or abstractive-oriented; and finally, concerning their purpose, the summaries can be generic, query-focused, or sentiment-based. The proposed architecture for compendium is divided in various stages, making a distinction between core and additional stages. The former constitute the backbone of the tool and are common for the generation of any type of summary, whereas the latter are used for enhancing the capabilities of the tool. The main contributions of compendium with respect to the state-of-the-art summarisation systems are that (i) it specifically deals with the problem of redundancy, by means of textual entailment; (ii) it combines statistical and cognitive-based techniques for determining relevant content; and (iii) it proposes an abstractive-oriented approach for facing the challenge of abstractive summarisation. The evaluation performed in different domains and textual genres, comprising traditional texts, as well as texts extracted from the Web 2.0, shows that compendium is very competitive and appropriate to be used as a tool for generating summaries.

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