Search results for "Recommendation"
showing 10 items of 136 documents
Convolutional Matrix Factorization for Recommendation Explanation
2018
In this paper, we introduce a novel recommendation model, which harnesses a convolutional neural network to mine meaningful information from customer reviews, and integrates it with matrix factorization algorithm seamlessly. It is a valid method to improve the transparency of CF algorithms.
Colectomie droite par abord robotique. Recommandations formalisées d’experts sous l’égide de l’Association française de chirurgie (AFC)
2022
Twenty-seven experts under the aegis of the French Association of Surgery (AFC) offer this reference system with formalized recommendations concerning the performance of right colectomy by robotic approach (RRC). For RRC, experts suggest patient installation in the so-called “classic” or “suprapubic” setup. For patients undergoing right colectomy for a benign pathology or cancer, RRC provides no significant benefit in terms of intra-operative blood loss, intra-operative complications or conversion rate to open laparotomy compared to laparoscopy. At the same time, RRC is associated with significantly longer operating times. Data from the literature are insufficient to define whether the robo…
New Directions for Use of Systemic Drug Delivery in Anti-aging Medicine
2020
Abstract Anti-aging medicine has become a popular topic in recent years. It considers biological aging a revertible process that physiologically serves no posi tive function. Different technologies in systemic delivery and various strategies that characterize and optimize the performance of systemic delivery have been covered in this book. These technologies are essential for the establishment of a technical platform for interventive biogerontology. As the last chapter of this book, we would like to highlight some directions for future applications of systemic drug delivery in anti-aging medicine. We believe that biological aging and aging-related diseases are strongly associated with genet…
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…
Combining intelligent recommendation and mixed reality in itineraries for urban exploration
2017
Exploration of points of interest (POI) in urban environments is challenging for the large amount of items near or reachable by the user and for the modality hindrances due to reduced manual flexibility and competing visual attention. We propose to combine different modalities, VR, AR, haptics-audio interfaces, with intelligent recommendation based on a computational method combining different data graph overlays: social, personal and search-time user input. We integrate such features in flexible itineraries that aid different phases and aspects of exploration.
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…
The laparoscopic approach to Acute Mesenteric Ischemia is today unclear and less debated (AMI). There are in fact no clinical evidences on this parti…
2016
The laparoscopic approach to Acute Mesenteric Ischemia is today unclear and less debated (AMI). There are in fact no clinical evidences on this particular focus and only few articles can be found in several databases (pubmed, cochrane library, etc.), and the problem concerns both diagnostic and therapeutic utilization of the procedure. These considerations were already taken into account in 2012 EAES guidelines where the Grade of Recommendation (GoR) of laparoscopy in AMI was low in both diagnostic and therapeutic aspects. According to the new Oxford Classification [1], the use of laparoscopy in patients with suspicious or diagnosed AMI presents a weak GoR.
WhoSNext: Recommending Twitter Users to Follow Using a Spreading Activation Network Based Approach
2020
The huge number of modern social network users has made the web a fertile ground for the growth and development of a plethora of recommender systems. To date, recommending a new user profile X to a given user U that could be interested in creating a relationship with X has been tackled using techniques based on content analysis, existing friendship relationships and other pieces of information coming from different social networks or websites. In this paper we propose a recommending architecture - called WhoSNext (WSN) - tested on Twitter and which aim is promoting the creation of new relationships among users. As recent researches show, this is an interesting recommendation problem: for a …
Emergsem : an approach of collaborative annotation and retrieval of images based on semantics emergent
2015
The extraction of images semantic is a process that requires deep analysis of the image content. It refers to their interpretation from a human point of view. In this lastest case, the image semantic may be generic (e.g., a vehicle) or specific (e.g., a bicycle). It consists in extracting single or multiple images semantic in order to facilitate its retrieval. These objectives clearly show that the extraction of semantic is not a new research field. This thesis deals with the semantic collaborative annotation of images and their retrieval. Firstly, it discusses how annotators could describe and represent images content based on visual information, and secondly how images retrieval could be …