Guilherme Medeiros Machado

Context-aware adaptive recommendation of resources for mobile users in a university campus

The selection of resources within a university campus is not an easy task, due the multitude of physical and virtual resources available. By this fact, a person can easily select a set of resources that cannot attend their needs and interests in the best way. Such multitude of resources can leads to the problem of the person cognitive overload, which happens during the resources selection. This paper presents a novel recommender approach as an alternative to select such best set of resources and avoid the person cognitive overload during it. Due to specificities for recommending learning resources, a knowledge-based approach seems to be more effective to this task and take the context in consideration can help in selecting the best resources to the current user situation. Take in consideration an adaptive interface makes the recommendations non-intrusive and help the user to see the location of the resources in the environment. To validate our approach we are developing a system to be used in an application scenario presented in this paper.

Business Process Modeling and Instantiation in Home Care Environments

There are many studies currently being conducted within the field of Home Care, where houses fulfilled with devices and sensors can help users in their daily lives, even the ones with chronicle diseases and disabilities. One important challenge in this area refers to the selection of the device and functionalities that best meets users� needs based on their context, location and disabilities. In this sense, this paper presents a novel approach for selecting the most appropriate device for the current user context. In our approach, devices and their functionalities are described and represented by Web services, and business processes are used as guidelines that specify procedures that should be taken in the treatment of a home care patient. Therefore, the issue of what device and which of its corresponding functionalities should be selected is treated as an approach to discover and select Web services based on its syntactic and semantic aspects as well as the user context.

UPCaD: A Methodology of Integration Between Ontology-Based Context-Awareness Modeling and Relational Domain Data

Context-awareness is a key feature for ubiquitous computing scenarios applications. Currently, technologies and methodologies have been proposed for the integration of context-awareness concepts in intelligent information systems to adapt them to the execution of services, user interfaces and data retrieval. Recent research proposed conceptual modeling alternatives to the integration of the domain modeling in RDBMS and context-awareness modeling. The research described using highly expressiveness ontologies. The present work describes the UPCaD (Unified Process for Integration between Context-Awareness and Domain) methodology, which is composed of formalisms and processes to guide the data integration considering RDBMS and context modeling. The methodology was evaluated in a virtual learning environment application. The evaluation shows the possibility to use a highly expressive context ontology to filter the relational data query and discusses the main contributions of the methodology compared with recent approaches.

A systematic mapping on adaptive recommender approaches for ubiquitous environments

Recommender systems were first conceived to provide suggestions of interesting items to users. The evolution of such systems provided an understanding that a recommender system is currently used to diverse objectives. One of the current challenges in the field is to have approaches of recommendation that go beyond accuracy metrics. Since it is a very recent interest of the community, this review, also characterized as an exploratory search, provides an overview of the techniques in the area that tries to look beyond accuracy. More specifically, one of the characteristics that would provide such evolution to these systems is the adaptation. This review is then performed to find the existence and characteristics of such approaches. Of the total 438 papers returned in the submission of the search string, 57 papers were analyzed after two filtering processes. The papers have shown that the area is little explored and one of the reasons is the challenge to validate non-accuracy characteristics in such approaches.

Domain content querying using ontology-based context-awareness in information systems

Abstract Ubiquitous computing technologies have been applied in several areas. However, it still presents a number of challenges, both for the full implementation of technologies and for the integration with existing information systems. One of the main mismatches evidenced by recent works is how context-awareness, a widely used capability in ubiquitous computing and actual information systems with relational databases may be integrated to allow ubiquitous and traditional systems to query relational data sources without the necessity to modify the schema of the database. This paper presents an integration model relating context and domain information allowing relational data to be retrieved in context without the necessity to change the originally used relational queries. A set of linking rules and algorithms are formalized in a model and this model is implemented in a prototype. The evaluation of the model is performed by applying it in a case study in a Massive Open Online Course (MOOC) platform. The evaluation of the model by the application of it in a case study in a MOOC platform demonstrated the possibility to use an ontology frequently used in ubiquitous middleware as an extra filtering layer for information systems without the necessity to recreate queries or make a re-engineering in the relational database schema. The results of the queries after the application of the model showed an average decrease of 21% in returned tuples, which was evaluated as a significant reduce in tuple results.

Database Ontology-Supported Query for Ubiquitous Environments

One of the main research opportunities regarding the use of contextual information is the context and relational databases integration. This integration allows the better contextualized retrieval of data. This paper presents a set of rules, which used with an ontological model, allows the integration of context and domain data. This approach enables the data retrieved through SQL queries to be returned in a contextualized manner, without the need to change the database schema originally used. Another advantage is the use of queries originally defined in systems, thus, it is not necessary to perform a re-engineering of the system. The model evaluation was carried out through the development of a case study applied to a virtual learning environment. The results show that the rules allow a filtering using the context of interest, resulting in a more meaningful data recovery.