Search results for "recommendation system"

Customer recommendation based on profile matching and customized campaigns in on-line social networks

2019

We propose a general framework for the recommendation of possible customers (users) to advertisers (e.g., brands) based on the comparison between On-Line Social Network profiles. In particular, we associate suitable categories and subcategories to both user and brand profiles in the considered On-line Social Network. When categories involve posts and comments, the comparison is based on word embedding, and this allows to take into account the similarity between the topics of particular interest for a brand and the user preferences. Furthermore, user personal information, such as age, job or genre, are used for targeting specific advertising campaigns. Results on real Facebook dataset show t…

Exploiting community detection to recommend privacy policies in decentralized online social networks

2018

The usage of Online Social Networks (OSNs) has become a daily activity for billions of people that share their contents and personal information with the other users. Regardless of the platform exploited to provide the OSNs’ services, these contents’ sharing could expose the OSNs’ users to a number of privacy risks if proper privacy-preserving mechanisms are not provided. Indeed, users must be able to define its own privacy policies that are exploited by the OSN to regulate access to the shared contents. To reduce such users’ privacy risks, we propose a Privacy Policies Recommended System (PPRS) that assists the users in defining their own privacy policies. Besides suggesting the most appro…

I-MALL An Effective Framework for Personalized Visits. Improving the Customer Experience in Stores

2022

In this paper we present I-MALL, an ICT hardware and software infrastructure that enables the management of services related to places such as shopping malls, showrooms, and conferences held in dedicated facilities. I-MALL offers a network of services that perform customer behavior analysis through computer vision and provide personalized recommendations made available on digital signage terminals. The user can also interact with a social robot. Recommendations are inferred on the basis of the profile of interests computed by the system analysing the history of the customer visit and his/her behavior including information from his/her appearance, the route taken inside the facility, as well…

Multicriteria decision making taxonomy of code recommendation system challenges: a fuzzy-AHP analysis

2022

AbstractThe recommendation systems plays an important role in today’s life as it assist in reliable selection of common utilities. The code recommendation system is being used by the code databases (GitHub, source frog etc.) aiming to recommend the more appropriate code to the users. There are several factors that could negatively impact the performance of code recommendation systems (CRS). This study aims to empirically explore the challenges that could have critical impact on the performance of the CRS. Using systematic literature review and questionnaire survey approaches, 19 challenges were identified. Secondly, the investigated challenges were further prioritized using fuzzy-AHP analys…

On personalized adaptation of learning environments

2017

This work is devoted to the development of personalized training systems. A major problem in learning environments is applying the same approach to all students: i.e., teaching materials, time for their mastering, and a training program that is designed in the same way for everyone. Although, each student is individual, has his own skills, ability to assimilate the material, his preferences and other. Recently, recommendation systems, of which the system of personalized learning is a part, have become widespread in the learning environments. On the one hand, this shift is due to mathematical approaches, such as machine learning and data mining, that are used in such systems while, on the ot…

Emotion Based Music Recommendation System

2020

Nowadays, music platforms provide easy access to large amounts of music. They are working continuously to improve music organization and search management thereby addressing the problem of choice and simplify exploring new music pieces. Recommendation systems gain more and more popularity and help people to select appropriate music for all occasions. However, there is still a gap in personalization and emotions driven recommendations. Music has a great influence on humans and is widely used for relaxing, mood regulation, destruction from stress and diseases, to maintain mental and physical work. There is a wide range of clinical settings and practices in music therapy for wellbeing support.…

Content Aware Playlist Generation with Multi-Dimensional Similarity Measure

2016

Brand Alliances: a Network Perspective with application to the fashion industry

2021

Music adviser : emotion-driven music recommendation ecosystem

2017

In respect of the big amounts of music available in the web, people met the problem of choice. From another side, practically unlimited resources can bring us new opportunities in the music context. Efficient data management engines which are smart and self managed are in demand nowadays in the music industry to handle music sources amounts of which are coming towards to infinity continuously. This study demonstrates feasibility of the emotional based personalization of music recommendation system. There is still gap between human and artificial intelligence, robotics do not have intuition and emotions which represent critical point of recommendations. Taking into account significant influe…