This document proposes an aspect-based resource recommendation system for smart hotels. It describes resources as physical services, virtual services, multimedia content or other information. It defines aspects to describe resources, including predictability, accessibility, relevancy and offensiveness. The system calculates a suitability value for each resource based on aspect values and user-defined weights. Two use cases demonstrate how the system recommends different resources to users based on their profiles and context. The system has advantages of being applicable across resource types and configurable, but limitations around predictive modeling and needing additional aspects.
Adaptive and Plastic User Interfaces: A review of the State of the Art.Eduardo Castillejo Gil
The document reviews the state of the art in adaptive user interfaces. It discusses several approaches to adapting user interfaces for different contexts, including mobile devices, web interfaces, and services. It analyzes solutions that use middleware platforms, context-aware adaptation, and substituting semantically equivalent interface elements to enable adaptation. The document structures the discussion around adaptation of general user interfaces, web interfaces, and services.
Este documento presenta un proyecto de fin de carrera sobre el diseño e implementación de un sistema de monitorización de infracciones de tráfico (SMIT) que consta de tres subsistemas: reconocimiento óptico de señales, una aplicación móvil y un sistema experto. El objetivo principal es reducir el número de víctimas en la carretera mediante la detección y gestión de excesos de velocidad. Se describen los componentes técnicos del sistema y cómo funcionan, incluyendo el reconocimiento de señales mediante redes neuronales,
Easing the Mobility of Disabled People in Supermarket Using a Distributed Sol...Eduardo Castillejo Gil
1. The document proposes a distributed system to help mobility impaired people shop more easily in supermarkets by getting their shopping lists from their devices and displaying product locations on a supermarket map.
2. The main challenges in building such a distributed system are coordination, authentication, and authorization, which can be addressed using a coordination paradigm called Triple Spaces that allows different nodes to securely share information.
3. The presented system architecture includes mobile and tablet applications, supermarket servers, and a Triple Spaces ontology to coordinate the different components.
Este documento describe el análisis de datos de logs web de una empresa de contenido multimedia para mejorar su servicio de recomendaciones personalizadas. Se exploran los datos para entender su estructura y contenido. Luego, se limpian y normalizan los datos para prepararlos para el análisis. Finalmente, se clasifican los usuarios en base a su comportamiento y contenido consumido para aplicar un algoritmo de recomendaciones personalizadas.
This document outlines the research activities of Eduardo Castillejo and the DeustoTech-INTERNET research group at the University of Deusto. It provides details on the group's research areas such as adaptive user interfaces, context-aware mobile computing, smart environments, and the Internet of Things. It also summarizes several of the group's current and past projects, publications, and other achievements.
Dynamic User Interface Adaptation Engine Through Semantic Modelling and Reaso...Eduardo Castillejo Gil
This Power Point presentation resumes the most significant work from my PhD thesis, which is public for download in the following link: https://github.com/edlectrico/dissertation/
Este documento presenta una introducción al uso de la librería NLTK en Python para realizar análisis de sentimientos. Explica cómo instalar NLTK y descargar conjuntos de datos de entrenamiento como las opiniones de películas etiquetadas. Luego muestra un ejemplo de cómo clasificar estas opiniones usando un clasificador bayesiano naive, obteniendo una precisión del 73%. Finalmente, indica cómo aplicar este análisis a nuestros propios datos respetando el formato requerido.
The document discusses testing system qualities when developing software. It introduces Rebecca Wirfs-Brock and Joseph Yoder, the authors, and their backgrounds. It then discusses some myths around system qualities testing. The rest of the document focuses on how to test various system qualities like performance, security, modifiability, and usability through the use of quality scenarios. It provides templates and examples for writing different types of quality scenarios.
Adaptive and Plastic User Interfaces: A review of the State of the Art.Eduardo Castillejo Gil
The document reviews the state of the art in adaptive user interfaces. It discusses several approaches to adapting user interfaces for different contexts, including mobile devices, web interfaces, and services. It analyzes solutions that use middleware platforms, context-aware adaptation, and substituting semantically equivalent interface elements to enable adaptation. The document structures the discussion around adaptation of general user interfaces, web interfaces, and services.
Este documento presenta un proyecto de fin de carrera sobre el diseño e implementación de un sistema de monitorización de infracciones de tráfico (SMIT) que consta de tres subsistemas: reconocimiento óptico de señales, una aplicación móvil y un sistema experto. El objetivo principal es reducir el número de víctimas en la carretera mediante la detección y gestión de excesos de velocidad. Se describen los componentes técnicos del sistema y cómo funcionan, incluyendo el reconocimiento de señales mediante redes neuronales,
Easing the Mobility of Disabled People in Supermarket Using a Distributed Sol...Eduardo Castillejo Gil
1. The document proposes a distributed system to help mobility impaired people shop more easily in supermarkets by getting their shopping lists from their devices and displaying product locations on a supermarket map.
2. The main challenges in building such a distributed system are coordination, authentication, and authorization, which can be addressed using a coordination paradigm called Triple Spaces that allows different nodes to securely share information.
3. The presented system architecture includes mobile and tablet applications, supermarket servers, and a Triple Spaces ontology to coordinate the different components.
Este documento describe el análisis de datos de logs web de una empresa de contenido multimedia para mejorar su servicio de recomendaciones personalizadas. Se exploran los datos para entender su estructura y contenido. Luego, se limpian y normalizan los datos para prepararlos para el análisis. Finalmente, se clasifican los usuarios en base a su comportamiento y contenido consumido para aplicar un algoritmo de recomendaciones personalizadas.
This document outlines the research activities of Eduardo Castillejo and the DeustoTech-INTERNET research group at the University of Deusto. It provides details on the group's research areas such as adaptive user interfaces, context-aware mobile computing, smart environments, and the Internet of Things. It also summarizes several of the group's current and past projects, publications, and other achievements.
Dynamic User Interface Adaptation Engine Through Semantic Modelling and Reaso...Eduardo Castillejo Gil
This Power Point presentation resumes the most significant work from my PhD thesis, which is public for download in the following link: https://github.com/edlectrico/dissertation/
Este documento presenta una introducción al uso de la librería NLTK en Python para realizar análisis de sentimientos. Explica cómo instalar NLTK y descargar conjuntos de datos de entrenamiento como las opiniones de películas etiquetadas. Luego muestra un ejemplo de cómo clasificar estas opiniones usando un clasificador bayesiano naive, obteniendo una precisión del 73%. Finalmente, indica cómo aplicar este análisis a nuestros propios datos respetando el formato requerido.
The document discusses testing system qualities when developing software. It introduces Rebecca Wirfs-Brock and Joseph Yoder, the authors, and their backgrounds. It then discusses some myths around system qualities testing. The rest of the document focuses on how to test various system qualities like performance, security, modifiability, and usability through the use of quality scenarios. It provides templates and examples for writing different types of quality scenarios.
Testing System Qualities Agile2012 by Rebecca Wirfs-Brock and Joseph YoderJoseph Yoder
Agile teams incrementally deliver functionality based on user stories. In the sprint to deliver features, frequently software qualities such as security, scalability, performance, and reliability are overlooked. Often these characteristics cut across many user stories. Trying to deal with certain system qualities late in the game can be difficult, causing major refactoring and upheaval of the system’s architecture. This churn isn’t inevitable. Especially if you adopt a practice of identifying those characteristics key to your system’s success, writing quality scenarios and tests, and delivering on these capabilities at the opportune time. We will show how to write Quality Scenarios that emphasize architecture capabilities such as usability, security, performance, scalability, internationalization, availability, accessibility and the like. This will be hands-on; we present some examples and follow with an exercise that illustrates how you can look at a system, identify, and then write and test quality scenarios.
Adaptive middleware of context aware application in smart homesambitlick
This document proposes an adaptive middleware for context-aware applications in smart homes. The middleware abstracts applications from sensors providing context and chooses context providers to maximize total application satisfaction given multiple alternatives. It also implements autonomic properties like self-configuration and resilience to failures in context provision.
Proactive Intelligent Home System Using Contextual Information and Neural Net...IJERA Editor
Nowadays, cities around the world intend to use information technology to improve the lives of their citizens.
Future smart cities will incorporate digital data and technology to interact differently with their human
inhabitants.
Among the key component of a smart city, we find the smart home component. It is an autonomic environment
that can provide various smart services by considering the user’s context information. Several methods are used
in context-aware system to provide such services. In this paper, we propose an approach to offer the most
relevant services to the user according to any significant change of his context environment. The proposed
approach is based on the use of context history information together with user profiling and machine learning
techniques. Experimentations show that the proposed solution can efficiently provide the most useful services to
the user in an intelligent home environment.
Contextualised Cognitive Perspective for Linked Sensor Data iammyr
This document proposes a contextualized cognitive approach for linking sensor data. It discusses using ontologies to describe sensor concepts and contexts. Current solutions like sensor ontologies and context classification architectures have limitations. The proposal is to use a cognitive approach inspired by human cognition, delimited to the sensor environment. Context would be described using domain-agnostic, event, and upper-level ontologies. Future work includes validating ontology choices and implementing the approach with user feedback. The goal is improving understanding of sensor reality by using the linked open data cloud to enhance classification and emulate human cognition.
David Kaufmann
School of Computing and Mathematical Sciences, Auckland University of Technology
(Friday, 3.00, Science 2)
Support for clinical handover remains a challenge for Health Informatics. Obstetric Handover is an important multi-disciplinary activity that can have important consequences for patient safety. Although IT systems can be used to support handover, the improvement of handover is not a purely IT-based problem. This project took place in the context of a clinical improvement process designed to formalise and improve handover in a busy delivery unit. This study used investigative tools from the usability domain in order to understand the usability requirements of a complete socio-technical system - the handover process. This work demonstrated the feasibility of using such tools and illustrated potential usability problems and solutions in the clinical handover process. Changes were made in IT systems, the organisation of the handover and the physical environment. Evaluation of the modified approach is being conducted, in the light of some usability issues already discovered.
This document proposes a framework to enable flexible access control and cloud-based information sharing during emergency situations. The framework uses complex event processing to detect emergencies and then activates temporary access control policies and obligations to allow authorized users controlled access to resources needed for emergency response. It also explores using encryption and dynamic virtualization techniques to securely share information across multiple organizations' private clouds during emergencies.
This document summarizes key aspects of recommender systems and ranking techniques. It discusses how recommender systems typically focus on accuracy but overlook diversity. The paper explores various recommendation techniques, including content-based, collaborative filtering, knowledge-based, and hybrid approaches. It also examines different ranking methods that can increase aggregate diversity, such as popularity-based, reverse predicted rating, and parameterized ranking. The goal is to improve recommendation diversity while maintaining adequate accuracy.
This document discusses a software usability evaluation method using fuzzy logic. It begins by introducing software usability as an important factor in evaluating software quality. It then provides an overview of common usability evaluation techniques like usability inspections, usability testing, and usability inquiries. The document proposes evaluating various usability metrics related to understandability, learnability, operability, attractiveness, and usability compliance using a questionnaire and fuzzy logic. It argues that usability should be integrated as a distinct phase in the software development life cycle to continuously track user needs. In conclusion, the paper presents a simple method to estimate software usability using fuzzy logic to handle uncertainty in evaluation results.
The document discusses a research project that uses a smartphone app to collect subjective travel experience data from individuals. The app will provide feedback to users about their own experiences as well as those of others. The researchers aim to see if these interventions can change travel behaviors and reduce emissions. They will draw on theories from behavioral economics, psychology, and technology acceptance. An important goal is to pilot and refine the app to make it more usable and understand its impact on travel choices over multiple trials involving both strangers and friends.
Design and implementation of a system for the improved searching and accessin...Cybera Inc.
Presentation by Ben Knoechel during the Sensor Web System and Visualization paper session of the Sensor Web Enablement workshop (held during the 2011 Cybera Summit).
This document provides an overview of intelligent user interfaces and user adaptivity. It discusses how intelligent interfaces can improve human-computer interaction by adapting to individual users based on their characteristics and behaviors. The benefits of adaptive systems include supporting tasks, information finding, and learning. Designing such systems poses usability challenges around transparency and control. Data can be collected explicitly from users or implicitly from their actions. There is a growing need for adaptive systems as technology increases in complexity and scope.
Following the user’s interests in mobile context aware recommender systemsBouneffouf Djallel
The wide development of mobile applications provides a considerable amount of data of all types (images, texts, sounds, videos, etc.). In this sense, Mobile Context-aware Recommender Systems (MCRS) suggest the user suitable information depending on her/his situation and interests. Two key questions have to be considered 1) how to recommend the user information that follows his/her interests evolution? 2) how to model the user’s situation and its related interests? To the best of our knowledge, no existing work proposing a MCRS tries to answer both questions as we do. This paper describes an ongoing work on the implementation of a MCRS based on the hybrid-ε-greedy algorithm we propose, which combines the standard ε-greedy algorithm and both content-based filtering and case-based reasoning techniques.
Extending Recommendation Systems With Semantics And Context AwarenessVictor Codina
This document proposes extending recommendation systems with semantics and context-awareness. It discusses limitations of traditional recommendation models and how semantics and context could help overcome those limitations. The authors propose a model that uses domain concepts with implicit semantics relationships and contextual concepts without semantics. An offline experiment on a pruned MovieLens dataset compares the proposed model to baselines. Results show the proposed contextual-semantic model improves prediction accuracy overall and for cold-start users compared to static and non-semantic models.
Deep Reinforcement Learning based Recommendation with Explicit User-ItemInter...Kishor Datta Gupta
—Recommendation is crucial in both academia andindustry, and various techniques are proposed such as content-based collaborative filtering, matrix factorization, logistic re-gression, factorization machines, neural networks and multi-armed bandits. However, most of the previous studies sufferfrom two limitations: (1) considering the recommendation asa static procedure and ignoring the dynamic interactive naturebetween users and the recommender systems; (2) focusing on theimmediate feedback of recommended items and neglecting thelong-term rewards. To address the two limitations, in this paperwe propose a novel recommendation framework based on deepreinforcement learning, called DRR. The DRR framework treatsrecommendation as a sequential decision making procedure andadopts an “Actor-Critic” reinforcement learning scheme to modelthe interactions between the users and recommender systems,which can consider both the dynamic adaptation and long-term rewards. Further more, a state representation module isincorporated into DRR, which can explicitly capture the interac-tions between items and users. Three instantiation structures aredeveloped. Extensive experiments on four real-world datasets areconducted under both the offline and online evaluation settings.The experimental results demonstrate the proposed DRR methodindeed outperforms the state-of-the-art competitors
This course revision presents a rapid recap of all the tools covered in the KeepIt course. It reproduces selected slides from each of the presentations given during the course to illustrate three aspects of each of the tools encountered: what they do, what they look like, what we did with them. The presentation was given as part of the final module of a 5-module course on digital preservation tools for repository managers, presented by the JISC KeepIt project. For more on this and other presentations in this course look for the tag ’KeepIt course’ in the project blog http://blogs.ecs.soton.ac.uk/keepit/
This document provides an overview of intelligent user interfaces and adaptive systems. It discusses key concepts like agents and intelligent agents. It also describes different types of agent models and environments. The benefits of user adaptivity are outlined as supporting tasks, information acquisition, and tailoring. Challenges to usability are discussed along with strategies to address tradeoffs. Methods for collecting user data both explicitly and implicitly are covered. The document concludes with the growing need for adaptivity given diverse users, contexts and information.
Perception.JS - A Framework for Context Acquisition Processing and PresentationSupun Dissanayake
Perception.js is a framework I have developed for my final research project for my Masters in Computer Science at University of Moratuwa. My research focused on developing a framework that will enable JavaScript developers to write context-awareness applications by enabling them to integrate various devices, gather data from those devices, specify rules for inferencing, and to respond to contextual changes.
The document discusses methods for evaluating ontologies. It proposes developing objective metrics to evaluate ontologies based on three criteria: correctness, completeness, and utility. Correctness evaluates how well an ontology expresses its design objectives. Completeness evaluates how fully an ontology captures required semantic components. Utility combines correctness and completeness and evaluates an ontology's usefulness for its intended use case. Examples are provided to illustrate evaluating ontologies based on the proposed metrics. The goal is to develop standardized evaluation methods to facilitate ontology development and reuse across different domains.
Exploration exploitation trade off in mobile context-aware recommender systemsBouneffouf Djallel
Most existing approaches in Context-Aware Recommender Systems (CRS) focus on recommending relevant items to users taking into account contextual information, such as time, loca-tion, or social aspects. However, none of them have considered the problem of user’s content dynamicity. This problem has been studied in the reinforcement learning community, but without paying much attention to the contextual aspect of the recommendation. We introduce in this paper an algorithm that tackles the user’s content dynamicity by modeling the CRS as a contextual bandit algorithm. It is based on dynamic explora-tion/exploitation and it includes a metric to decide which user’s situation is the most relevant to exploration or exploitation. Within a deliberately designed offline simulation framework, we conduct extensive evaluations with real online event log data. The experimental results and detailed analysis demon-strate that our algorithm outperforms surveyed algorithms.
This document summarizes mathematical methods of tensor factorization applied to recommender systems. It discusses motivations and contributions, information overload and recommender systems, matrix and tensor factorization techniques in recommender system literature such as matrix factorization, singular value decomposition, high-order singular value decomposition, and parallel factor analysis. It also covers challenges in context-aware recommender systems and proposed solutions to incorporate contextual information.
The Microsoft 365 Migration Tutorial For Beginner.pptxoperationspcvita
This presentation will help you understand the power of Microsoft 365. However, we have mentioned every productivity app included in Office 365. Additionally, we have suggested the migration situation related to Office 365 and how we can help you.
You can also read: https://www.systoolsgroup.com/updates/office-365-tenant-to-tenant-migration-step-by-step-complete-guide/
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Testing System Qualities Agile2012 by Rebecca Wirfs-Brock and Joseph YoderJoseph Yoder
Agile teams incrementally deliver functionality based on user stories. In the sprint to deliver features, frequently software qualities such as security, scalability, performance, and reliability are overlooked. Often these characteristics cut across many user stories. Trying to deal with certain system qualities late in the game can be difficult, causing major refactoring and upheaval of the system’s architecture. This churn isn’t inevitable. Especially if you adopt a practice of identifying those characteristics key to your system’s success, writing quality scenarios and tests, and delivering on these capabilities at the opportune time. We will show how to write Quality Scenarios that emphasize architecture capabilities such as usability, security, performance, scalability, internationalization, availability, accessibility and the like. This will be hands-on; we present some examples and follow with an exercise that illustrates how you can look at a system, identify, and then write and test quality scenarios.
Adaptive middleware of context aware application in smart homesambitlick
This document proposes an adaptive middleware for context-aware applications in smart homes. The middleware abstracts applications from sensors providing context and chooses context providers to maximize total application satisfaction given multiple alternatives. It also implements autonomic properties like self-configuration and resilience to failures in context provision.
Proactive Intelligent Home System Using Contextual Information and Neural Net...IJERA Editor
Nowadays, cities around the world intend to use information technology to improve the lives of their citizens.
Future smart cities will incorporate digital data and technology to interact differently with their human
inhabitants.
Among the key component of a smart city, we find the smart home component. It is an autonomic environment
that can provide various smart services by considering the user’s context information. Several methods are used
in context-aware system to provide such services. In this paper, we propose an approach to offer the most
relevant services to the user according to any significant change of his context environment. The proposed
approach is based on the use of context history information together with user profiling and machine learning
techniques. Experimentations show that the proposed solution can efficiently provide the most useful services to
the user in an intelligent home environment.
Contextualised Cognitive Perspective for Linked Sensor Data iammyr
This document proposes a contextualized cognitive approach for linking sensor data. It discusses using ontologies to describe sensor concepts and contexts. Current solutions like sensor ontologies and context classification architectures have limitations. The proposal is to use a cognitive approach inspired by human cognition, delimited to the sensor environment. Context would be described using domain-agnostic, event, and upper-level ontologies. Future work includes validating ontology choices and implementing the approach with user feedback. The goal is improving understanding of sensor reality by using the linked open data cloud to enhance classification and emulate human cognition.
David Kaufmann
School of Computing and Mathematical Sciences, Auckland University of Technology
(Friday, 3.00, Science 2)
Support for clinical handover remains a challenge for Health Informatics. Obstetric Handover is an important multi-disciplinary activity that can have important consequences for patient safety. Although IT systems can be used to support handover, the improvement of handover is not a purely IT-based problem. This project took place in the context of a clinical improvement process designed to formalise and improve handover in a busy delivery unit. This study used investigative tools from the usability domain in order to understand the usability requirements of a complete socio-technical system - the handover process. This work demonstrated the feasibility of using such tools and illustrated potential usability problems and solutions in the clinical handover process. Changes were made in IT systems, the organisation of the handover and the physical environment. Evaluation of the modified approach is being conducted, in the light of some usability issues already discovered.
This document proposes a framework to enable flexible access control and cloud-based information sharing during emergency situations. The framework uses complex event processing to detect emergencies and then activates temporary access control policies and obligations to allow authorized users controlled access to resources needed for emergency response. It also explores using encryption and dynamic virtualization techniques to securely share information across multiple organizations' private clouds during emergencies.
This document summarizes key aspects of recommender systems and ranking techniques. It discusses how recommender systems typically focus on accuracy but overlook diversity. The paper explores various recommendation techniques, including content-based, collaborative filtering, knowledge-based, and hybrid approaches. It also examines different ranking methods that can increase aggregate diversity, such as popularity-based, reverse predicted rating, and parameterized ranking. The goal is to improve recommendation diversity while maintaining adequate accuracy.
This document discusses a software usability evaluation method using fuzzy logic. It begins by introducing software usability as an important factor in evaluating software quality. It then provides an overview of common usability evaluation techniques like usability inspections, usability testing, and usability inquiries. The document proposes evaluating various usability metrics related to understandability, learnability, operability, attractiveness, and usability compliance using a questionnaire and fuzzy logic. It argues that usability should be integrated as a distinct phase in the software development life cycle to continuously track user needs. In conclusion, the paper presents a simple method to estimate software usability using fuzzy logic to handle uncertainty in evaluation results.
The document discusses a research project that uses a smartphone app to collect subjective travel experience data from individuals. The app will provide feedback to users about their own experiences as well as those of others. The researchers aim to see if these interventions can change travel behaviors and reduce emissions. They will draw on theories from behavioral economics, psychology, and technology acceptance. An important goal is to pilot and refine the app to make it more usable and understand its impact on travel choices over multiple trials involving both strangers and friends.
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Presentation by Ben Knoechel during the Sensor Web System and Visualization paper session of the Sensor Web Enablement workshop (held during the 2011 Cybera Summit).
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Following the user’s interests in mobile context aware recommender systemsBouneffouf Djallel
The wide development of mobile applications provides a considerable amount of data of all types (images, texts, sounds, videos, etc.). In this sense, Mobile Context-aware Recommender Systems (MCRS) suggest the user suitable information depending on her/his situation and interests. Two key questions have to be considered 1) how to recommend the user information that follows his/her interests evolution? 2) how to model the user’s situation and its related interests? To the best of our knowledge, no existing work proposing a MCRS tries to answer both questions as we do. This paper describes an ongoing work on the implementation of a MCRS based on the hybrid-ε-greedy algorithm we propose, which combines the standard ε-greedy algorithm and both content-based filtering and case-based reasoning techniques.
Extending Recommendation Systems With Semantics And Context AwarenessVictor Codina
This document proposes extending recommendation systems with semantics and context-awareness. It discusses limitations of traditional recommendation models and how semantics and context could help overcome those limitations. The authors propose a model that uses domain concepts with implicit semantics relationships and contextual concepts without semantics. An offline experiment on a pruned MovieLens dataset compares the proposed model to baselines. Results show the proposed contextual-semantic model improves prediction accuracy overall and for cold-start users compared to static and non-semantic models.
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—Recommendation is crucial in both academia andindustry, and various techniques are proposed such as content-based collaborative filtering, matrix factorization, logistic re-gression, factorization machines, neural networks and multi-armed bandits. However, most of the previous studies sufferfrom two limitations: (1) considering the recommendation asa static procedure and ignoring the dynamic interactive naturebetween users and the recommender systems; (2) focusing on theimmediate feedback of recommended items and neglecting thelong-term rewards. To address the two limitations, in this paperwe propose a novel recommendation framework based on deepreinforcement learning, called DRR. The DRR framework treatsrecommendation as a sequential decision making procedure andadopts an “Actor-Critic” reinforcement learning scheme to modelthe interactions between the users and recommender systems,which can consider both the dynamic adaptation and long-term rewards. Further more, a state representation module isincorporated into DRR, which can explicitly capture the interac-tions between items and users. Three instantiation structures aredeveloped. Extensive experiments on four real-world datasets areconducted under both the offline and online evaluation settings.The experimental results demonstrate the proposed DRR methodindeed outperforms the state-of-the-art competitors
This course revision presents a rapid recap of all the tools covered in the KeepIt course. It reproduces selected slides from each of the presentations given during the course to illustrate three aspects of each of the tools encountered: what they do, what they look like, what we did with them. The presentation was given as part of the final module of a 5-module course on digital preservation tools for repository managers, presented by the JISC KeepIt project. For more on this and other presentations in this course look for the tag ’KeepIt course’ in the project blog http://blogs.ecs.soton.ac.uk/keepit/
This document provides an overview of intelligent user interfaces and adaptive systems. It discusses key concepts like agents and intelligent agents. It also describes different types of agent models and environments. The benefits of user adaptivity are outlined as supporting tasks, information acquisition, and tailoring. Challenges to usability are discussed along with strategies to address tradeoffs. Methods for collecting user data both explicitly and implicitly are covered. The document concludes with the growing need for adaptivity given diverse users, contexts and information.
Perception.JS - A Framework for Context Acquisition Processing and PresentationSupun Dissanayake
Perception.js is a framework I have developed for my final research project for my Masters in Computer Science at University of Moratuwa. My research focused on developing a framework that will enable JavaScript developers to write context-awareness applications by enabling them to integrate various devices, gather data from those devices, specify rules for inferencing, and to respond to contextual changes.
The document discusses methods for evaluating ontologies. It proposes developing objective metrics to evaluate ontologies based on three criteria: correctness, completeness, and utility. Correctness evaluates how well an ontology expresses its design objectives. Completeness evaluates how fully an ontology captures required semantic components. Utility combines correctness and completeness and evaluates an ontology's usefulness for its intended use case. Examples are provided to illustrate evaluating ontologies based on the proposed metrics. The goal is to develop standardized evaluation methods to facilitate ontology development and reuse across different domains.
Exploration exploitation trade off in mobile context-aware recommender systemsBouneffouf Djallel
Most existing approaches in Context-Aware Recommender Systems (CRS) focus on recommending relevant items to users taking into account contextual information, such as time, loca-tion, or social aspects. However, none of them have considered the problem of user’s content dynamicity. This problem has been studied in the reinforcement learning community, but without paying much attention to the contextual aspect of the recommendation. We introduce in this paper an algorithm that tackles the user’s content dynamicity by modeling the CRS as a contextual bandit algorithm. It is based on dynamic explora-tion/exploitation and it includes a metric to decide which user’s situation is the most relevant to exploration or exploitation. Within a deliberately designed offline simulation framework, we conduct extensive evaluations with real online event log data. The experimental results and detailed analysis demon-strate that our algorithm outperforms surveyed algorithms.
This document summarizes mathematical methods of tensor factorization applied to recommender systems. It discusses motivations and contributions, information overload and recommender systems, matrix and tensor factorization techniques in recommender system literature such as matrix factorization, singular value decomposition, high-order singular value decomposition, and parallel factor analysis. It also covers challenges in context-aware recommender systems and proposed solutions to incorporate contextual information.
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An Aspect Based Resource Recommendation System for Smart Hotels
1. Introduction Proposed System Use case Conclusions Acknowledgements
An Aspect Based Resource Recommendation
System for Smart Hotels
Aitor Almeida1 , Eduardo Castillejo 1 , Diego L´pez-de-Ipi˜a1 ,
o n
Marcos Sacrist´n
a 2 and Javier Diego3
1 DeustoTech - Deusto Institute of Technology, University of Deusto http://www.morelab.deusto.es
2
Treelogic http://www.treelogic.com
3
Logica http://www.logica.com/es
September 24, 2012
2. Introduction Proposed System Use case Conclusions Acknowledgements
Index
1 Introduction
Problem
Proposed solution
2 Proposed System
Resources
Aspects
Suitability
3 Use case
4 Conclusions
Conclusions
Future work
5 Acknowledgements
3. Introduction Proposed System Use case Conclusions Acknowledgements
Problem
Introduction
The number of resources available in a Smart Environment
can be overwhelming.
Using user and resource features with context data can
help in the recommendation filtering process.
Our domain: Smart hotels
A proactive domain which makes recommendations to its users.
It must know about users’ preferences, tastes and limitations
or capabilities.
It must be capable of analysing the different aspects that
define a resource to offer the most appropriate one to the user.
4. Introduction Proposed System Use case Conclusions Acknowledgements
Proposed solution
Introduction
An aspect-based resource recommendation system.
We have identified the aspects of a resource that can be
used to describe it in a Smart Environment.
These aspects take into account both user and resource
features and the current context.
5. Introduction Proposed System Use case Conclusions Acknowledgements
Resources
Proposed System
6. Introduction Proposed System Use case Conclusions Acknowledgements
Resources
Proposed System
Resource type (in our domain):
Pyshical service
Virtual service
Multimedia content
Othe information (maps, news...)
7. Introduction Proposed System Use case Conclusions Acknowledgements
Resources
Proposed System
Resource type (in our domain):
Pyshical service
Virtual service
Multimedia content
Othe information (maps, news...)
Defined aspects must be generic enough to be used to
describe all the available resources. In the current
implementation we have considered:
1. Predictability
2. Accessibility
3. Relevancy
4. Offensiveness
8. Introduction Proposed System Use case Conclusions Acknowledgements
Aspects
Proposed System
1. Predictability
It reflects how likely a resource is to be used based on the
resources previously consumed.
The likeliness is expressed as a probability value 0..1
Markov Chains to create the model of the user’s resource
usage → ascertain patterns in the user behaviour
One of the Markov Chains created with the
resource consumption data for the
predictability aspect. Using the created model
the recommender system can predict the
likeness of one resource to be the next to be
consumed
9. Introduction Proposed System Use case Conclusions Acknowledgements
Aspects
Proposed System
2. Accessibility
Users possess a wide variety of abilities (sensorial, cognitive
and so on) that must be taken into account to asses the
suitability of the resources.
Taxonomy of the user abilities taken into account in the accessibility aspect. Disabilities are
classified in three categories.
Users must be able of consuming every resource.
10. Introduction Proposed System Use case Conclusions Acknowledgements
Aspects
Proposed System
Each resource has:
required user abilities
recommended user abilities
We penalize resources that can not be consumed by the user:
Aacc = 1 − ω|Recnot |
Aacc is the value of the accessibility for the resource.
ω is the penalization weight.
|Recnot | is the number of recommended abilities not met by
the user.
11. Introduction Proposed System Use case Conclusions Acknowledgements
Aspects
Proposed System
3. Relevancy
It measures the importance of a resource to the user’s
current context.
Context variables:
User location
Time of the day
Current activity: sleeping, hygiene routine, eating, exercising,
working, shopping and visiting tourist attractions.
For the classifier we have used KNN (k-nearest neighbor)
supervised classification method.
12. Introduction Proposed System Use case Conclusions Acknowledgements
Aspects
Proposed System
4. Offensiveness
It measures the suitability of a resource based on a rating
system.
We use the age categories and content descriptions by PEGI
(Pan European Game Information) rating system.
To evaluate it, we use the same Accessibility formula, taking
the age categories as required constraints and the content
descriptions as the recommended ones.
13. Introduction Proposed System Use case Conclusions Acknowledgements
Suitability
Proposed System
Suitability: It is a dynamic and personalized value for an
aspect to a specific user:
Mtot = Σwi fi
Mtot is the value of the suitability of each resource.
wi is the weight for an aspect.
fi is the value of the aspect of a resource. These values are
normalized.
14. Introduction Proposed System Use case Conclusions Acknowledgements
Use case
Two different users (in their rooms, the service R1 has just
been activated):
User 1: a 27 years old male with a hearing impairment.
User 2: a 6 years old child.
Available resources:
R1: Wake up service.
R2: Room service.
R3: Press digest.
R4: Multimedia system.
R5: Transport service.
Weigths:
Predictability and Relevancy = 1
Accessibility and Offensiveness = 0.5
15. Introduction Proposed System Use case Conclusions Acknowledgements
User 1
No content restriction.
Hearing impairment.
R1 and R4 offer alternative means to use them.
Using the suitability formula:
Mtot = 1 × 0.6 + 0.5 × 1 + 0.5 × 1 + 1 × 0.7
Recommended resource: R2
16. Introduction Proposed System Use case Conclusions Acknowledgements
User 2
Content restriction (Press digest has a minimun age category
of 7) → scoring 0 in Offensiveness
No disability.
Using the suitability formula:
Mtot = 1 × 0.5 + 0.5 × 1 + 0.5 × 1 + 1 × 0.9
Recommended resource: R4
17. Introduction Proposed System Use case Conclusions Acknowledgements
Conclusions
Conclusions
Advantages
Applicable to all the resource types identified in an intelligent
hotel domain: digital and physical services, multimedia content
and data.
Configurable process (weights).
Creation of a comprehensive picture of the current situation to
recommend the most suitable resource.
Anticipation of future user needs.
Limitations
With Markov Chains we evaluate Predictability, but we don’t
evaluate the previous events that preceded the current one...
(Time Series?)
More aspects are needed.
18. Introduction Proposed System Use case Conclusions Acknowledgements
Future work
Conclusions
Aspect we are working on:
Timeliness: it evaluates how up to date is the information
about a resource.
Satisfaction: measures the opinion of the users about a
resource.
Attention: The average number of interactions per time unit
with a consumed resource.
Closeness: Evaluates what resources are consumed by similar
users.
We aim to include vagueness and uncertainty in the context
data information by ambiguity assessing techniques.
19. Introduction Proposed System Use case Conclusions Acknowledgements
Acknowledgements
This work has been supported by project grant CEN-20101019
(THOFU), funded by the Spanish Centro para el Desarrollo
Tecnol´gico Industrial (CDTI) and supported by the Spanish
o
Ministerio de Ciencia e Innovaci´n.
o