Search results for "Recommender system"
showing 10 items of 70 documents
Advances in Practical Applications of Agents, Multi-Agent Systems, and Sustainability: The PAAMS Collection
2015
This volume presents the papers that have been accepted for the 2015 special sessions of the 13th International Conference on Practical Applications of Agents and Multi-Agent Systems, held at University of Salamanca, Spain, at 3rd-5th June, 2015: Agents Behaviours and Artificial Markets (ABAM); Agents and Mobile Devices (AM); Multi-Agent Systems and Ambient Intelligence (MASMAI); Web Mining and Recommender systems (WebMiRes); Learning, Agents and Formal Languages (LAFLang); Agent-based Modeling of Sustainable Behavior and Green Economies (AMSBGE); Emotional Software Agents (SSESA) and Intelligent Educational Systems (SSIES). The volume also includes the paper accepted for the Doctoral Conso…
A Smart Contract Based Recommender System
2019
Nowadays information available on the World Wide Web has reached unprecedented growth and it makes difficult for users to find the most relevant for them. In order to alleviate such issue, Recommender Systems (RSs) have been proposed to collect opinions and preferences about a set of items, process such preferences and build a personalized information access. While the most part of current RSs exploit centralized architecture to provide the service, in this manuscript we propose an alternative approach for building a general purpose RSs that provides to users with more transparent and decentralized rating strategy. Indeed, the proposed framework is built on top of a Distributed Ledger techn…
Semantically-enhanced advertisement recommender systems in social networks
2016
El suministro de recomendaciones en los sistemas sociales lleva ya algún tiempo en el punto de mira tanto de los académicos como de la industria. Los gigantes de las redes sociales como Facebook, LinkedIn, Myspace, etc., están ansiosos por encontrar la bala de plata de la recomendación. Estas aplicaciones permiten a los clientes dar forma a unas determinadas redes sociales a través de sus comunicaciones sociales cooperativas cotidianas. Mientras tanto, la experiencia online actual depende progresivamente de la asociación social. Una de las principales preocupaciones en la red social es establecer un plan de negocio exitoso para obtener más beneficios de la red social. Hacer un negocio en ca…
How does serendipity affect diversity in recommender systems? A serendipity-oriented greedy algorithm
2018
Most recommender systems suggest items that are popular among all users and similar to items a user usually consumes. As a result, the user receives recommendations that she/he is already familiar with or would find anyway, leading to low satisfaction. To overcome this problem, a recommender system should suggest novel, relevant and unexpected i.e., serendipitous items. In this paper, we propose a serendipity-oriented, reranking algorithm called a serendipity-oriented greedy (SOG) algorithm, which improves serendipity of recommendations through feature diversification and helps overcome the overspecialization problem. To evaluate our algorithm, we employed the only publicly available datase…
Ranking-Oriented Collaborative Filtering: A Listwise Approach
2016
Collaborative filtering (CF) is one of the most effective techniques in recommender systems, which can be either rating oriented or ranking oriented. Ranking-oriented CF algorithms demonstrated significant performance gains in terms of ranking accuracy, being able to estimate a precise preference ranking of items for each user rather than the absolute ratings (as rating-oriented CF algorithms do). Conventional memory-based ranking-oriented CF can be referred to as pairwise algorithms. They represent each user as a set of preferences on each pair of items for similarity calculations and predictions. In this study, we propose ListCF, a novel listwise CF paradigm that seeks improvement in bot…
SCCF Parameter and Similarity Measure Optimization and Evaluation
2019
Neighborhood-based Collaborative Filtering (CF) is one of the most successful and widely used recommendation approaches; however, it suffers from major flaws especially under sparse environments. Traditional similarity measures used by neighborhood-based CF to find similar users or items are not suitable in sparse datasets. Sparse Subspace Clustering and common liking rate in CF (SCCF), a recently published research, proposed a tunable similarity measure oriented towards sparse datasets; however, its performance can be maximized and requires further analysis and investigation. In this paper, we propose and evaluate the performance of a new tuning mechanism, using the Mean Absolute Error (MA…
An ontology-based recommendation system for people with autism and technology apps
2018
The research about the use of technology for persons with autism spectrum disorders (ASD) has rapidly increased in the last decade. This fact has accompanied with the sharp development and use of apps for mobile devices by these people and their caregivers. The election of the adequate apps for persons with autism is a very difficult task, with many variables involved with the person with ASD, the family, the practitioners and the community where they live. This paper describes a recommendation system that reuse an ontology, which supports the information about the apps and all the variables previously cited. The data about the apps are automatically obtained from recognized web repositorie…
Semantic technologies for industry: From knowledge modeling and integration to intelligent applications
2013
Artificial Intelligence technologies are growingly used within several software systems ranging from Web services to mobile applications. It is by no doubt true that the more AI algorithms and methods are used the more they tend to depart from a pure "AI" spirit and end to refer to the sphere of standard software. In a sense, AI seems strongly connected with ideas, methods and tools that are not (yet) used by the general public. On the contrary, a more realistic view of it would be a rich and pervading set of successful paradigms and approaches. Industry is currently perceiving semantic technologies as a key contribution of AI to innovation. In this paper a survey of current industrial expe…
SMART-ASD, model and ontology definition: a technology recommendation system for people with autism and/or intellectual disabilities
2018
There are many studies that encourage the use of mobile device solutions to improve the skills of people with an Autism Spectrum Disorder (ASD). There are a number of apps that may be useful for people with ASD, some specifically designed for them, and others not. The main goal of the SMART-ASD project is to assist in the selection of adequate technology and all related accessories. In this project, the users' data are maintained into an ontology. This ontology also includes information about devices, apps, and protection. The system is a hybrid recommendation system that guides parents and professionals in the selection of the adequate technology. This paper presents the SMART-ASD model an…
Watch This! The Influence of Recommender Systems and Social Factors on the Content Choices of Streaming Video on Demand Consumers
2021
Streaming Video-on-demand (SVOD) services are getting increasingly popular. Current research, however, lacks knowledge about consumers’ content decision processes and their respective influencing factors. Thus, the work reported on in this paper explores socio-technical interrelations of factors impacting content choices in SVOD, examining the social factors WOM, eWOM and peer mediation, as well as the technological influence of recommender systems. A research model based on the Theory of Reasoned Action and the Technology Acceptance Model was created and tested by an n = 186 study sample. Results show that the quality of a recommender system and not the social mapping functionality is the …