Stream-based explainable recommendations via blockchain profiling

2021 ◽  
pp. 1-17
Author(s):  
Fátima Leal ◽  
Bruno Veloso ◽  
Benedita Malheiro ◽  
Juan Carlos Burguillo ◽  
Adriana E. Chis ◽  
...  
Keyword(s):  
Historical Data ◽  
Positive Impact ◽  
Empirical Evaluation ◽  
Recommendation Systems ◽  
Use Cases ◽  
Collaborative Filter ◽  
Model Based ◽  
Collaborative Recommendation ◽  
Smart Contract ◽  
User Trust

Explainable recommendations enable users to understand why certain items are suggested and, ultimately, nurture system transparency, trustworthiness, and confidence. Large crowdsourcing recommendation systems ought to crucially promote authenticity and transparency of recommendations. To address such challenge, this paper proposes the use of stream-based explainable recommendations via blockchain profiling. Our contribution relies on chained historical data to improve the quality and transparency of online collaborative recommendation filters – Memory-based and Model-based – using, as use cases, data streamed from two large tourism crowdsourcing platforms, namely Expedia and TripAdvisor. Building historical trust-based models of raters, our method is implemented as an external module and integrated with the collaborative filter through a post-recommendation component. The inter-user trust profiling history, traceability and authenticity are ensured by blockchain, since these profiles are stored as a smart contract in a private Ethereum network. Our empirical evaluation with HotelExpedia and Tripadvisor has consistently shown the positive impact of blockchain-based profiling on the quality (measured as recall) and transparency (determined via explanations) of recommendations.

scholarly journals A Reference Framework to Combine Model-Based Design and AR to Improve Social Sustainability

2021 ◽  
Vol 13 (4) ◽  
pp. 2031
Author(s):  
Fabio Grandi ◽  
Riccardo Karim Khamaisi ◽  
Margherita Peruzzini ◽  
Roberto Raffaeli ◽  
Marcello Pellicciari
Keyword(s):  
Positive Impact ◽  
Cost Effective ◽  
Digital Models ◽  
Model Based ◽  
Digital Contents ◽  
Recent Developments ◽  
Virtual Simulations ◽  
Product And Process ◽  
The Impact ◽  
Time Information

Product and process digitalization is pervading numerous areas in the industry to improve quality and reduce costs. In particular, digital models enable virtual simulations to predict product and process performances, as well as to generate digital contents to improve the general workflow. Digital models can also contain additional contents (e.g., model-based design (MBD)) to provide online and on-time information about process operations and management, as well as to support operator activities. The recent developments in augmented reality (AR) offer new specific interfaces to promote the great diffusion of digital contents into industrial processes, thanks to flexible and robust applications, as well as cost-effective devices. However, the impact of AR applications on sustainability is still poorly explored in research. In this direction, this paper proposed an innovative approach to exploit MBD and introduce AR interfaces in the industry to support human intensive processes. Indeed, in those processes, the human contribution is still crucial to guaranteeing the expected product quality (e.g., quality inspection). The paper also analyzed how this new concept can benefit sustainability and define a set of metrics to assess the positive impact on sustainability, focusing on social aspects.

scholarly journals Cluster searching strategies for collaborative recommendation systems

2013 ◽  
Vol 49 (3) ◽  
pp. 688-697 ◽  
Author(s):  
Ismail Sengor Altingovde ◽  
Özlem Nurcan Subakan ◽  
Özgür Ulusoy
Keyword(s):  
Recommendation Systems ◽  
Collaborative Recommendation

WEATHER AND THE ECOLOGY OF APANTELES FUMIFERANAE VIER. (HYMENOPTERA: BRACONIDAE)

1988 ◽  
Vol 120 (S146) ◽  
pp. 57-70 ◽  
Author(s):  
Vincent G. Nealis
Keyword(s):  
Field Data ◽  
Historical Data ◽  
Spruce Budworm ◽  
Temperature Dependent ◽  
Maturation Period ◽  
Phenological Model ◽  
Model Based ◽  
Egg Maturation ◽  
Adult Parasitoid ◽  
Specific Mortality

AbstractThe effects of weather on the spruce budworm parasitoid, Apanteles fumiferanae Vier., are examined. A phenological model based on temperature-dependent rates of development and longevity is developed and validated with field data. The model is then used to explore the effects of age-specific mortality on phenological behaviour of the parasitoid and the seasonal synchrony between the parasitoid and its host over several years. The results show that the parasitoid adult ecloses well before the host reaches an age susceptible to parasitism but that the egg maturation period and the longevity of the parasitoid diminish the consequences of the apparent asynchrony. The historical data reveal that the relative phenological characteristics of A. fumiferanae and its host vary little from year to year. In the second part of the study, temperature is shown to have a strong effect on adult parasitoid activity and on the rate of oviposition.

A Movie E-Shop Recommendation Model Based on Web Usage and Ontological Data

2011 ◽  
pp. 51-68
Author(s):  
Andreas Aresti ◽  
Penelope Markellou ◽  
Ioanna Mousourouli ◽  
Spiros Sirmakessis ◽  
Athanasios Tsakalidis
Keyword(s):  
Artificial Intelligence ◽  
User Modeling ◽  
Web Mining ◽  
Recommendation System ◽  
Recommendation Systems ◽  
Model Based ◽  
Web Usage ◽  
One To One ◽  
Online Shops

Recommendation systems are special personalization tools that help users to find interesting information and services in complex online shops. Even though today’s e-commerce environments have drastically evolved and now incorporate techniques from other domains and application areas such as Web mining, semantics, artificial intelligence, user modeling, and profiling setting up a successful recommendation system is not a trivial or straightforward task. This chapter argues that by monitoring, analyzing, and understanding the behavior of customers, their demographics, opinions, preferences, and history, as well as taking into consideration the specific e-shop ontology and by applying Web mining techniques, the effectiveness of produced recommendations can be significantly improved. In this way, the e-shop may upgrade users’ interaction, increase its usability, convert users to buyers, retain current customers, and establish long-term and loyal one-to-one relationships.

A Study of Use Cases for Smart Contracts Using Blockchain Technology

2021 ◽  
pp. 1823-1844
Author(s):  
S R Mani Sekhar ◽  
Siddesh G M ◽  
Swapnil Kalra ◽  
Shaswat Anand
Keyword(s):  
Natural Disaster ◽  
Vital Role ◽  
Use Cases ◽  
Use Case ◽  
Smart Contracts ◽  
Digital Identity ◽  
Blockchain Technology ◽  
Smart Contract ◽  
Healthcare Finance ◽  
Natural Disaster Management

Blockchain technology is an emerging and rapidly growing technology in the current world scenario. It is a collection of records connected through cryptography. They play a vital role in smart contracts. Smart contracts are present in blockchains which are self-controlled and trustable. It can be integrated across various domains like healthcare, finance, self-sovereign identity, governance, logistics management and home care, etc. The purpose of this article is to analyze the various use cases of smart contracts in different domains and come up with a model which may be used in the future. Subsequently, a detailed description of a smart contract and blockchain is provided. Next, different case-studies related to five different domains is discussed with the help of use case diagrams. Finally, a solution for natural disaster management has been proposed by integrating smart contract, digital identity, policies and blockchain technologies, which can be used effectively for providing relief to victims during times of natural disaster.

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