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

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.

2009 ◽  
Vol 2009 ◽  
pp. 1-19 ◽  
Author(s):  
Xiaoyuan Su ◽  
Taghi M. Khoshgoftaar

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.


2020 ◽  
Vol 27 (12) ◽  
pp. 1276-1287
Author(s):  
Brigida Anna Maiorano ◽  
Giovanni Schinzari ◽  
Sabrina Chiloiro ◽  
Felicia Visconti ◽  
Domenico Milardi ◽  
...  

Pancreatic neuroendocrine tumors (PanNETs) are rare tumors having usually an indolent behavior, but sometimes with unpredictable aggressiveness. PanNETs are more often non-functioning (NF), unable to produce functioning hormones, while 10-30% present as functioning (F) - PanNETs, such as insulinomas , gastrinomas , and other rare tumors. Diagnostic and prognostic markers, but also new therapeutic targets, are still lacking. Proteomics techniques represent therefore promising approaches for the future management of PanNETs. We conducted a systematic review to summarize the state of the art of proteomics in PanNETs. A total of 9 studies were included, focusing both on NF- and F-PanNETs. Indeed, proteomics is useful for the diagnosis, the prognosis and the detection of therapeutic targets. However, further studies are required. It is also warranted to standardize the analysis methods and the collection techniques, in order to validate proteins with a relevance in the personalized approach to PanNETs management.


2012 ◽  
Vol 25 (3) ◽  
pp. 371-392 ◽  
Author(s):  
Leyla Demir ◽  
Semra Tunali ◽  
Deniz Tursel Eliiyi

This paper provides a general note on the state of the art in the application of nondestructive testing techniques (NDT) for the detection of defects or deteriorations in metallic and nonmetallic oil and gas pipes. The advantages and disadvantages of each technique will be pointed out.


2020 ◽  
Author(s):  
Claire Perillaud Dubois ◽  
Drifa Belhadi ◽  
Cédric Laouénan ◽  
Laurent Mandelbrot ◽  
Christelle Vauloup-Fellous ◽  
...  

Abstract Background: Congenital CMV infection is the first worldwide cause of congenital viral infection and a major cause of sensorineural hearing loss and mental retardation. As systematic screening of pregnant women and newborns is still debated in many countries, this systematic review aims to provide the state of the art on current practices concerning management of congenital CMV infection.Methods: We will perform electronically searches on MEDLINE, EMBASE, Cochrane Library (CENTRAL), ClinicalTrials.gov, Web of Science and hand searches in grey literature. Interventions regarding biological, imaging, and therapeutic management of infected pregnant women, fetuses and neonates/children (from birth to 6 years old) will be studied in this systematic review. Study screening will be performed in duplicate by two independent reviewers and risk of bias will be evaluated with the ROBINS-I tool. Discussion: This review will provide the state of the art of current management of congenital CMV infection in pregnant women, fetuses, neonates and children until 6 years old, in order to have an overview of current practices of congenital CMV infection.Systematic review registration: PROSPERO CRD42019124342


Author(s):  
Yongzhi Wang

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.


2012 ◽  
Vol 4 (1) ◽  
pp. 17-36 ◽  
Author(s):  
Pedram Hayati ◽  
Vidyasagar Potdar

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.


Author(s):  
Faiz Maazouzi ◽  
Hafed Zarzour ◽  
Yaser Jararweh

With the enormous amount of information circulating on the Web, it is becoming increasingly difficult to find the necessary and useful information quickly and efficiently. However, with the emergence of recommender systems in the 1990s, reducing information overload became easy. In the last few years, many recommender systems employ the collaborative filtering technology, which has been proven to be one of the most successful techniques in recommender systems. Nowadays, the latest generation of collaborative filtering methods still requires further improvements to make the recommendations more efficient and accurate. Therefore, the objective of this article is to propose a new effective recommender system for TED talks that first groups users according to their preferences, and then provides a powerful mechanism to improve the quality of recommendations for users. In this context, the authors used the Pearson Correlation Coefficient (PCC) method and TED talks to create the TED user-user matrix. Then, they used the k-means clustering method to group the same users in clusters and create a predictive model. Finally, they used this model to make relevant recommendations to other users. The experimental results on real dataset show that their approach significantly outperforms the state-of-the-art methods in terms of RMSE, precision, recall, and F1 scores.


AI Magazine ◽  
2008 ◽  
Vol 29 (4) ◽  
pp. 93 ◽  
Author(s):  
Pearl Pu ◽  
Li Chen

We address user system interaction issues in product search and recommender systems: how to help users select the most preferential item from a large collection of alternatives. As such systems must crucially rely on an accurate and complete model of user preferences, the acquisition of this model becomes the central subject of our paper. Many tools used today do not satisfactorily assist users to establish this model because they do not adequately focus on fundamental decision objectives, help them reveal hidden preferences, revise conflicting preferences, or explicitly reason about tradeoffs. As a result, users fail to find the outcomes that best satisfy their needs and preferences. In this article, we provide some analyses of common areas of design pitfalls and derive a set of design guidelines that assist the user in avoiding these problems in three important areas: user preference elicitation, preference revision, and explanation interfaces. For each area, we describe the state-of-the-art of the developed techniques and discuss concrete scenarios where they have been applied and tested.


1971 ◽  
Vol 25 (4) ◽  
pp. 430-439 ◽  
Author(s):  
Howard J. Sloane

This paper in a tabulated summary format discusses the state-of-the-art of Raman spectroscopy for commercially available instrumentation. A comparison to infrared is made in terms of (I) instrumentation, (II) sample handling, and (III) applications. Although the two techniques yield similar and often complementary information, they are quite different from the point of view of instrumentation and sampling procedures. This leads to various advantages and disadvantages or limitations for each. These are discussed as well as the future outlook.


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