Recent Developments in Recommender Systems

2019 ◽  
pp. 38-51 ◽  
Author(s):  
Jia-Ming Low ◽  
Ian K. T. Tan ◽  
Choo-Yee Ting
Keyword(s):  
Recommender Systems ◽  
Recent Developments

scholarly journals A Comprehensive Survey of Knowledge Graph-Based Recommender Systems: Technologies, Development, and Contributions

Information ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 232
Author(s):  
Janneth Chicaiza ◽  
Priscila Valdiviezo-Diaz
Keyword(s):  
Recommender Systems ◽  
Survey Result ◽  
Knowledge Graph ◽  
Specific Recommendation ◽  
Future Directions ◽  
Recent Developments ◽  
Comprehensive Survey ◽  
System 2 ◽  
And Performance ◽  
Use Of Knowledge

In recent years, the use of recommender systems has become popular on the web. To improve recommendation performance, usage, and scalability, the research has evolved by producing several generations of recommender systems. There is much literature about it, although most proposals focus on traditional methods’ theories and applications. Recently, knowledge graph-based recommendations have attracted attention in academia and the industry because they can alleviate information sparsity and performance problems. We found only two studies that analyze the recommendation system’s role over graphs, but they focus on specific recommendation methods. This survey attempts to cover a broader analysis from a set of selected papers. In summary, the contributions of this paper are as follows: (1) we explore traditional and more recent developments of filtering methods for a recommender system, (2) we identify and analyze proposals related to knowledge graph-based recommender systems, (3) we present the most relevant contributions using an application domain, and (4) we outline future directions of research in the domain of recommender systems. As the main survey result, we found that the use of knowledge graphs for recommendations is an efficient way to leverage and connect a user’s and an item’s knowledge, thus providing more precise results for users.

scholarly journals Impact of sharing full versus averaged social information on social influence and estimation accuracy

2021 ◽  
Vol 18 (180) ◽  
pp. 20210231
Author(s):  
Bertrand Jayles ◽  
Clément Sire ◽  
Ralf H. J. M. Kurvers
Keyword(s):  
Social Networks ◽  
Social Influence ◽  
Recommender Systems ◽  
Social Information ◽  
Estimation Accuracy ◽  
Human Ability ◽  
The Social ◽  
Recent Developments ◽  
Available Information

The recent developments of social networks and recommender systems have dramatically increased the amount of social information shared in human communities, challenging the human ability to process it. As a result, sharing aggregated forms of social information is becoming increasingly popular. However, it is unknown whether sharing aggregated information improves people’s judgments more than sharing the full available information. Here, we compare the performance of groups in estimation tasks when social information is fully shared versus when it is first averaged and then shared. We find that improvements in estimation accuracy are comparable in both cases. However, our results reveal important differences in subjects’ behaviour: (i) subjects follow the social information more when receiving an average than when receiving all estimates, and this effect increases with the number of estimates underlying the average; (ii) subjects follow the social information more when it is higher than their personal estimate than when it is lower. This effect is stronger when receiving all estimates than when receiving an average. We introduce a model that sheds light on these effects, and confirms their importance for explaining improvements in estimation accuracy in all treatments.

Recent developments in affective recommender systems

2016 ◽  
Vol 461 ◽  
pp. 182-190 ◽  
Author(s):  
Rahul Katarya ◽  
Om Prakash Verma
Keyword(s):  
Recommender Systems ◽  
Recent Developments

scholarly journals A Closer-to-Reality Model for Comparing Relevant Dimensions of Recommender Systems, with Application to Novelty

Information ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 500
Author(s):  
François Fouss ◽  
Elora Fernandes
Keyword(s):  
Recommender Systems ◽  
State Of The Art ◽  
Evaluation Procedure ◽  
Recommendation Algorithm ◽  
Test Set ◽  
Ranking Algorithms ◽  
Traditional Training ◽  
Recommendation Algorithms ◽  
Recent Developments

Providing fair and convenient comparisons between recommendation algorithms—where algorithms could focus on a traditional dimension (accuracy) and/or less traditional ones (e.g., novelty, diversity, serendipity, etc.)—is a key challenge in the recent developments of recommender systems. This paper focuses on novelty and presents a new, closer-to-reality model for evaluating the quality of a recommendation algorithm by reducing the popularity bias inherent in traditional training/test set evaluation frameworks, which are biased by the dominance of popular items and their inherent features. In the suggested model, each interaction has a probability of being included in the test set that randomly depends on a specific feature related to the focused dimension (novelty in this work). The goal of this paper is to reconcile, in terms of evaluation (and therefore comparison), the accuracy and novelty dimensions of recommendation algorithms, leading to a more realistic comparison of their performance. The results obtained from two well-known datasets show the evolution of the behavior of state-of-the-art ranking algorithms when novelty is progressively, and fairly, given more importance in the evaluation procedure, and could lead to potential changes in the decision processes of organizations involving recommender systems.

Rough Web Intelligent Techniques for Page Recommendation

2013 ◽  
pp. 170-191
Author(s):  
H. Inbarani ◽  
K. Thangavel
Keyword(s):  
Recommender Systems ◽  
Web Applications ◽  
Predictive Accuracy ◽  
Relevant Information ◽  
User Preference ◽  
Data Sets ◽  
Web Page ◽  
Recent Developments ◽  
Access Patterns ◽  
The Web

Recommender systems represent a prominent class of personalized Web applications, which particularly focus on the user-dependent filtering and selection of relevant information. Recommender Systems have been a subject of extensive research in Artificial Intelligence over the last decade, but with today’s increasing number of e-commerce environments on the Web, the demand for new approaches to intelligent product recommendation is higher than ever. There are more online users, more online channels, more vendors, more products, and, most importantly, increasingly complex products and services. These recent developments in the area of recommender systems generated new demands, in particular with respect to interactivity, adaptivity, and user preference elicitation. These challenges, however, are also in the focus of general Web page recommendation research. The goal of this chapter is to develop robust techniques to model noisy data sets containing an unknown number of overlapping categories and apply them for Web personalization and mining. In this chapter, rough set-based clustering approaches are used to discover Web user access patterns, and these techniques compute a number of clusters automatically from the Web log data using statistical techniques. The suitability of rough clustering approaches for Web page recommendation are measured using predictive accuracy metrics.

scholarly journals A Survey of e-Commerce Recommender Systems

2016 ◽  
Vol 12 (34) ◽  
pp. 75 ◽  
Author(s):  
Farida Karimova
Keyword(s):  
Recommender Systems ◽  
Recommender System ◽  
Recommendation Systems ◽  
Recent Developments ◽  
Online Environments

Due to their powerful personalization and efficiency features, recommendation systems are being used extensively in many online environments. Recommender systems provide great opportunities to businesses, therefore research on developing new recommender system techniques and methods have been receiving increasing attention. This paper reviews recent developments in recommender systems in the domain of ecommerce. The main purpose of the paper is to summarize and compare the latest improvements of e-commerce recommender systems from the perspective of e-vendors. By examining the recent publications in the field, our research provides thorough analysis of current advancements and attempts to identify the existing issues in recommender systems. Final outcomes give practitioners and researchers the necessary insights and directions on recommender systems.

Trends in Electron Energy Loss Spectroscopy

1977 ◽  
Vol 35 ◽  
pp. 228-229
Author(s):  
C. Colliex ◽  
P. Trebbia
Keyword(s):  
Energy Loss ◽  
Electron Energy ◽  
Electron Energy Loss Spectroscopy ◽  
Materials Science ◽  
Analytical Technique ◽  
Recent Developments ◽  
Quantitative Results ◽  
Electron Microscopes ◽  
Electron Energy Loss ◽  
Primary Electrons

The physical foundations for the use of electron energy loss spectroscopy towards analytical purposes, seem now rather well established and have been extensively discussed through recent publications. In this brief review we intend only to mention most recent developments in this field, which became available to our knowledge. We derive also some lines of discussion to define more clearly the limits of this analytical technique in materials science problems.The spectral information carried in both low ( 0<ΔE<100eV ) and high ( >100eV ) energy regions of the loss spectrum, is capable to provide quantitative results. Spectrometers have therefore been designed to work with all kinds of electron microscopes and to cover large energy ranges for the detection of inelastically scattered electrons (for instance the L-edge of molybdenum at 2500eV has been measured by van Zuylen with primary electrons of 80 kV). It is rather easy to fix a post-specimen magnetic optics on a STEM, but Crewe has recently underlined that great care should be devoted to optimize the collecting power and the energy resolution of the whole system.

Filaments and membranes in the mitotic apparatus

1983 ◽  
Vol 41 ◽  
pp. 544-547
Author(s):  
Kent McDonald
Keyword(s):  
Intermediate Filaments ◽  
Mitotic Spindle ◽  
Mitotic Apparatus ◽  
Light Microscope Level ◽  
Microtubule Associated Proteins ◽  
Recent Developments ◽  
Associated Proteins ◽  
Force Generator ◽  
Spindle Function ◽  
Antibody Technology

At the light microscope level the recent developments and interest in antibody technology have permitted the localization of certain non-microtubule proteins within the mitotic spindle, e.g., calmodulin, actin, intermediate filaments, protein kinases and various microtubule associated proteins. Also, the use of fluorescent probes like chlorotetracycline suggest the presence of membranes in the spindle. Localization of non-microtubule structures in the spindle at the EM level has been less rewarding. Some mitosis researchers, e.g., Rarer, have maintained that actin is involved in mitosis movements though the bulk of evidence argues against this interpretation. Others suggest that a microtrabecular network such as found in chromatophore granule movement might be a possible force generator but there is little evidence for or against this view. At the level of regulation of spindle function, Harris and more recently Hepler have argued for the importance of studying spindle membranes. Hepler also believes that membranes might play a structural or mechanical role in moving chromosomes.

Software pattern recognition applied to nanodiffraction patterns from a STEM instrument

1986 ◽  
Vol 44 ◽  
pp. 694-695
Author(s):  
G.Y. Fan ◽  
J.M. Cowley
Keyword(s):  
Image Processing ◽  
Pattern Recognition ◽  
Computer Software ◽  
Processing System ◽  
Light Level ◽  
Host Computer ◽  
Low Light ◽  
Image Processing System ◽  
Recent Developments ◽  
On Line

In recent developments, the ASU HB5 has been modified so that the timing, positioning, and scanning of the finely focused electron probe can be entirely controlled by a host computer. This made the asynchronized handshake possible between the HB5 STEM and the image processing system which consists of host computer (PDP 11/34), DeAnza image processor (IP 5000) which is interfaced with a low-light level TV camera, array processor (AP 400) and various peripheral devices. This greatly facilitates the pattern recognition technique initiated by Monosmith and Cowley. Software called NANHB5 is under development which, instead of employing a set of photo-diodes to detect strong spots on a TV screen, uses various software techniques including on-line fast Fourier transform (FFT) to recognize patterns of greater complexity, taking advantage of the sophistication of our image processing system and the flexibility of computer software.

High-resolution microscopy of twin boundaries in gold

1987 ◽  
Vol 45 ◽  
pp. 260-261
Author(s):  
William Krakow ◽  
David A. Smith
Keyword(s):  
High Resolution ◽  
Specimen Preparation ◽  
Gold Films ◽  
Boundary Area ◽  
Transmission Electron ◽  
Recent Developments ◽  
Tilt Boundaries ◽  
High Resolution Microscopy ◽  
Twist Boundaries

Recent developments in specimen preparation, imaging and image analysis together permit the experimental determination of the atomic structure of certain, simple grain boundaries in metals such as gold. Single crystal, ∼125Å thick, (110) oriented gold films are vapor deposited onto ∼3000Å of epitaxial silver on (110) oriented cut and polished rock salt substrates. Bicrystal gold films are then made by first removing the silver coated substrate and placing in contact two suitably misoriented pieces of the gold film on a gold grid. Controlled heating in a hot stage first produces twist boundaries which then migrate, so reducing the grain boundary area, to give mixed boundaries and finally tilt boundaries perpendicular to the foil. These specimens are well suited to investigation by high resolution transmission electron microscopy.

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