Answering user queries from hotel ontology for decision making

Semantic web comes out with the vision of making human readable information to be machine processable. Ontology, the core of semantic web, with concept instantiations serves as a domain knowledge base while semantic web query language provides retrieval of that information. In this paper, we presented a system that populates hotel related information in the ontology and a natural language querying platform to retrieve the information from a common interface for decision making. A simple user experiment shows that the system is time effective and helpful in making decisions with minimum queries as compared to browsing even with selected sites

Negative Statements Considered Useful

Knowledge bases (KBs), pragmatic collections of knowledge about notable entities, are an important asset in applications such as search, question answering and dialogue. Rooted in a long tradition in knowledge representation, all popular KBs only store positive information, while they abstain from taking any stance towards statements not contained in them. In this paper, we make the case for explicitly stating interesting statements which are not true. Negative statements would be important to overcome current limitations of question answering, yet due to their potential abundance, any effort towards compiling them needs a tight coupling with ranking. We introduce two approaches towards compiling negative statements. (i) In peer-based statistical inferences, we compare entities with highly related entities in order to derive potential negative statements, which we then rank using supervised and unsupervised features. (ii) In query-log-based text extraction, we use a pattern-based approach for harvesting search engine query logs. Experimental results show that both approaches hold promising and complementary potential. Along with this paper, we publish the first datasets on interesting negative information, containing over 1.1M statements for 100K popular Wikidata entities

Feasibility report: Delivering case-study based learning using artificial intelligence and gaming technologies

This document describes an investigation into the technical feasibility of a game to support learning based on case studies. Information systems students using the game will conduct fact-finding interviews with virtual characters. We survey relevant technologies in computational linguistics and games. We assess the applicability of the various approaches and propose an architecture for the game based on existing techniques. We propose a phased development plan for the development of the game

State-of-the-art on evolution and reactivity

This report starts by, in Chapter 1, outlining aspects of querying and updating resources on the Web and on the Semantic Web, including the development of query and update languages to be carried out within the Rewerse project. From this outline, it becomes clear that several existing research areas and topics are of interest for this work in Rewerse. In the remainder of this report we further present state of the art surveys in a selection of such areas and topics. More precisely: in Chapter 2 we give an overview of logics for reasoning about state change and updates; Chapter 3 is devoted to briefly describing existing update languages for the Web, and also for updating logic programs; in Chapter 4 event-condition-action rules, both in the context of active database systems and in the context of semistructured data, are surveyed; in Chapter 5 we give an overview of some relevant rule-based agents frameworks

On Repairing Reasoning Reversals via Representational Refinements

Representation is a fluent. A mismatch between the real world and an agent’s representation of it can be signalled by unexpected failures (or successes) of the agent’s reasoning. The ‘real world ’ may include the ontologies of other agents. Such mismatches can be repaired by refining or abstracting an agent’s ontology. These refinements or abstractions may not be limited to changes of belief, but may also change the signature of the agent’s ontology. We describe the implementation and successful evaluation of these ideas in the ORS system. ORS diagnoses failures in plan execution and then repairs the faulty ontologies. Our automated approach to dynamic ontology repair has been designed specifically to address real issues in multi-agent systems, for instance, as envisaged in the Semantic Web

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

Contributos para suportar o desenvolvimento de sistemas de diálogo

With the increase of technology present in our daily routine, a specific area rose exponentially. Spoken dialogue systems are increasingly popular and useful: they provide an easier and more versatile access to large and diverse sets of information. Nowadays there is a vast knowledge base regarding this topic, as well as different systems capable of performing numerous tasks just by simply processing voice input. There are also an increasing set of tools for their development. Despite recent advances, development of dialog systems continues to be challenging. The main objective of this thesis is to contribute and make possible and simple the development of new dialogue systems for Portuguese: by selecting, adapting and combining existing tools/frameworks. Supported by the enhancements made to the selected basis framework, two different dialog systems were developed: the first is an assistant aimed at a Smart Home environment - one of areas that benefited the most with the development of dialog systems - and the second targeting accessible tourism. The first assistant was developed aligned with the Smart Green Homes project. It implied the definition of scenarios and requirements that later helped defining the ontology and the system. Another requirement for this system was the inclusion of the back-end system developed previously as part of the Smart Green Homes project. The second was aligned with the project ACTION in the area of Tourism. It was developed for users with accessibility needs, e.g., impaired movement or vision.Com o aumento da tecnologia presente na nossa rotina diária, uma área específica subiu exponencialmente. Os sistemas de diálogo são cada vez mais populares e úteis: proporcionam um acesso mais fácil e versátil a grandes e diversificados conjuntos de informação. Hoje em dia existe uma vasta base de conhecimento sobre este tema, bem como diferentes sistemas capazes de executar inúmeras tarefas através do processamento de uma entrada de voz. Há também um conjunto crescente de ferramentas para o seu desenvolvimento. Apesar dos avanços recentes, o desenvolvimento de sistemas de diálogo continua a ser um desafio. O principal objetivo desta tese é contribuir e tornar possível e simples o desenvolvimento de novos sistemas de diálogo que suportem português: selecionando, adaptando e combinando ferramentas existentes. Baseado nas melhorias feitas nas ferramentas bases selecionadas, foram desenvolvidos dois sistemas de diálogo diferentes: o primeiro é um assistente dirigido a um ambiente Smart Home - uma das áreas que mais beneficiou com o desenvolvimento de sistemas de diálogo - e o segundo visando o turismo acessível. O primeiro assistente foi desenvolvido alinhado com o projeto Smart Green Homes. Implicou a definição de cenários e requisitos que mais tarde ajudaram a definir a ontologia e o sistema. Outro requisito para este sistema foi a inclusão do sistema back-end desenvolvido anteriormente como parte do projeto Smart Green Homes. O segundo assistente foi alinhado com o projeto ACTION na área do Turismo. Foi desenvolvido para utilizadores com necessidades de acessibilidade, por exemplo, deficiência motora ou invisualidade.Mestrado em Engenharia de Computadores e Telemátic