421 research outputs found
Smart Geographic object: Toward a new understanding of GIS Technology in Ubiquitous Computing
One of the fundamental aspects of ubiquitous computing is the instrumentation
of the real world by smart devices. This instrumentation constitutes an
opportunity to rethink the interactions between human beings and their
environment on the one hand, and between the components of this environment on
the other. In this paper we discuss what this understanding of ubiquitous
computing can bring to geographic science and particularly to GIS technology.
Our main idea is the instrumentation of the geographic environment through the
instrumentation of geographic objects composing it. And then investigate how
this instrumentation can meet the current limitations of GIS technology, and
offers a new stage of rapprochement between the earth and its abstraction. As
result, the current research work proposes a new concept we named Smart
Geographic Object SGO. The latter is a convergence point between the smart
objects and geographic objects, two concepts appertaining respectively to
Natural Language based Context Modeling and Reasoning with LLMs: A Tutorial
Large language models (LLMs) have become phenomenally surging, since
2018--two decades after introducing context-awareness into computing systems.
Through taking into account the situations of ubiquitous devices, users and the
societies, context-aware computing has enabled a wide spectrum of innovative
applications, such as assisted living, location-based social network services
and so on. To recognize contexts and make decisions for actions accordingly,
various artificial intelligence technologies, such as Ontology and OWL, have
been adopted as representations for context modeling and reasoning. Recently,
with the rise of LLMs and their improved natural language understanding and
reasoning capabilities, it has become feasible to model contexts using natural
language and perform context reasoning by interacting with LLMs such as ChatGPT
and GPT-4. In this tutorial, we demonstrate the use of texts, prompts, and
autonomous agents (AutoAgents) that enable LLMs to perform context modeling and
reasoning without requiring fine-tuning of the model. We organize and introduce
works in the related field, and name this computing paradigm as the LLM-driven
Context-aware Computing (LCaC). In the LCaC paradigm, users' requests, sensors
reading data, and the command to actuators are supposed to be represented as
texts. Given the text of users' request and sensor data, the AutoAgent models
the context by prompting and sends to the LLM for context reasoning. LLM
generates a plan of actions and responds to the AutoAgent, which later follows
the action plan to foster context-awareness. To prove the concepts, we use two
showcases--(1) operating a mobile z-arm in an apartment for assisted living,
and (2) planning a trip and scheduling the itinerary in a context-aware and
personalized manner.Comment: Under revie
Predicting Your Next Stop-over from Location-based Social Network Data with Recurrent Neural Networks
In the past years, Location-based Social Network (LBSN) data have
strongly fostered a data-driven approach to the recommendation
of Points of Interest (POIs) in the tourism domain. However, an
important aspect that is often not taken into account by current
approaches is the temporal correlations among POI categories in
tourist paths. In this work, we collect data from Foursquare, we
extract timed paths of POI categories from sequences of temporally
neighboring check-ins and we use a Recurrent Neural Network
(RNN) to learn to generate new paths by training it to predict
observed paths. As a further step, we cluster the data considering
users’ demographics and learn separate models for each category
of users. The evaluation shows the eectiveness of the proposed
approach in predicting paths in terms of model perplexity on the
test se
The Advent of Semantic Web in Tourism Information Systems
The tourism industry depends on complex value creation chains involving a large number of participants that change frequently and rapidly. In addition, the products of tourism industry are complex and they will perish if they are not sold in time. For these reasons, the ideal tourism information systems require a lot of flexibility of underlying systems. Moreover, they comprise accurate access to any tourism service that provide, and they are usable by corporate and private customers alike. The management and interoperation of semantically diverse tourism information systems are facilitated by Semantic Web technology that provides methods and standards, which allow accurate access to information as well as flexibility to comply with needs of tourism information system users and administrators. This paper considers state-of-the art issues (ontologies, semantic modelling and querying, semantic portals and semantic-based e-markets) concerning the exploitation of the semantic web technologies and applications in tourism information systems
The Advent of Semantic Web in Tourism Information Systems
The tourism industry depends on complex value creation chains involving a large number of participants that change frequently and rapidly. In addition, the products of tourism industry are complex and they will perish if they are not sold in time. For these reasons, the ideal tourism information systems require a lot of flexibility of underlying systems. Moreover, they comprise accurate access to any tourism service that provide, and they are usable by corporate and private customers alike. The management and interoperation of semantically diverse tourism information systems are facilitated by Semantic Web technology that provides methods and standards, which allow accurate access to information as well as flexibility to comply with needs of tourism information system users and administrators. This paper considers state-of-the art issues (ontologies, semantic modelling and querying, semantic portals and semantic-based e-markets) concerning the exploitation of the semantic web technologies and applications in tourism information systems
OntoTouTra: tourist traceability ontology based on big data analytics
Tourist traceability is the analysis of the set of actions, procedures, and technical measures that allows us to identify and record the space–time causality of the tourist’s touring, from the beginning to the end of the chain of the tourist product. Besides, the traceability of tourists has implications for infrastructure, transport, products, marketing, the commercial viability of the industry, and the management of the destination’s social, environmental, and cultural impact. To this end, a tourist traceability system requires a knowledge base for processing elements, such as functions, objects, events, and logical connectors among them. A knowledge base provides us with information on the preparation, planning, and implementation or operation stages. In this regard, unifying tourism terminology in a traceability system is a challenge because we need a central repository that promotes standards for tourists and suppliers in forming a formal body of knowledge representation. Some studies are related to the construction of ontologies in tourism, but none focus on tourist traceability systems. For the above, we propose OntoTouTra, an ontology that uses formal specifications to represent knowledge of tourist traceability systems. This paper outlines the development of the OntoTouTra ontology and how we gathered and processed data from ubiquitous computing using Big Data analysis techniquesThis research was financially supported by the Ministry of Science, Technology, and Innovation of Colombia (733-2015) and by the Universidad Santo Tomás Seccional Tunja
30th International Conference on Information Modelling and Knowledge Bases
Information modelling is becoming more and more important topic for researchers, designers, and users of information systems. The amount and complexity of information itself, the number of abstraction levels of information, and the size of databases and knowledge bases are continuously growing. Conceptual modelling is one of the sub-areas of information modelling. The aim of this conference is to bring together experts from different areas of computer science and other disciplines, who have a common interest in understanding and solving problems on information modelling and knowledge bases, as well as applying the results of research to practice. We also aim to recognize and study new areas on modelling and knowledge bases to which more attention should be paid. Therefore philosophy and logic, cognitive science, knowledge management, linguistics and management science are relevant areas, too. In the conference, there will be three categories of presentations, i.e. full papers, short papers and position papers
Electronic Imaging & the Visual Arts. EVA 2012 Florence
The key aim of this Event is to provide a forum for the user, supplier and scientific research communities to meet and exchange experiences, ideas and plans in the wide area of Culture & Technology. Participants receive up to date news on new EC and international arts computing & telecommunications initiatives as well as on Projects in the visual arts field, in archaeology and history. Working Groups and new Projects are promoted. Scientific and technical demonstrations are presented
From Data Disclosure to Privacy Nudges: A Privacy-aware and User-centric Personal Data Management Framework
Although there are privacy-enhancing tools designed to protect users' online privacy, it is surprising to see a lack of user-centric solutions allowing privacy control based on the joint assessment of privacy risks and benefits, due to data disclosure to \emph{multiple} platforms. In this paper, we propose a conceptual framework to fill the gap: aiming at the user-centric privacy protection, we show the framework can not only assess privacy risks in using online services but also the added values earned from data disclosure. Through following a human-in-the-loop approach, it is expected the framework provides a personalized solution via preference learning, continuous privacy assessment, behavior monitoring and nudging. Finally, we describe a case study towards "leisure travelers" and several future areas to be studied in the ongoing project
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