Concept discovery and argument bundles in the web of experiences

Milions de persones interactuen i comparteixen informació cada dia a la Web. Des de converses intranscendents fins a comentaris sobre productes en tendes online, el contingut generat per les persones a la Web és enorme i divers. I entre aquests continguts n’hi ha un particularment interessant: les experiències. La gent escolta, llegeix i considera les experiències d’altri abans de prendre decisions, com per exemple comprar-se una càmera digital o anar de viatge a algun lloc exòtic. I quan aquestes experiències estan guardades a la Web, són accessibles per un gran nombre de persones. Malauradament, aquest contingut no és fàcilment accessible: Una persona interessada en anar-se’n de vacances a un hotel probablement llegirà unes quantes experiències d’altra gent que ha anat prèviament a aquest hotel per descobrir que n’opinen, però segurament no podrà llegir-les totes. D’aquesta manera ignorarà informació i experiències d’altra gent que li haurien estat profitoses de cara al seu viatge. Així doncs, considerem que hi ha una clara necessitat d’un anàlisis més profund d’aquesta informació continguda en les experiències de persones, per facilitar-ne el seu ús. El nostre enfocament es troba en el context de la Web de les Experiències, i es basa en extreure i adquirir coneixement pràctic d’experiències individuals respecte entitats del món real expressades en forma textual. A més a més, aquest coneixement han de ser tractat i representat de manera que permeti la seva reutilització per altres persones amb diferents interessos i preferències. Aquest procés està dividit en tres parts: Primer, extraiem les paraules més important utilitzades en les experiències de les diferents persones per descriure opinions sobre entitats. Seguidament, utilitzant el conjunt de paraules extretes, les agrupem en conceptes i creem un vocabulari de conceptes, que ens ajuda a descobrir els aspectes més importants de cada entitat segons les experiències viscudes per cada individu. Finalment, utilitzant el vocabulari de conceptes, creem els aplecs d’arguments de cada entitat. Els aplecs d’arguments caracteritzen els pros i els cons de cada entitat, i agreguen el coneixement pràctic extret de les experiències escrites per cada individu. A més amés, demostrem que els aplecs d’arguments, a part de ser útils per a representar el coneixement pràctic de les experiències, permeten fer inferència sobre quina entitat és la més adequada per cada individual, considerant el conjunt de preferències de cada individu. En aquesta tesi avaluem els aplecs d’arguments amb les puntuacions dels productes d’Amazon i les caracteritzacions de les càmeres de Dpreview, una web especialitzada en càmeres digitals. Demostrem com els arguments pro i con dels nostres aplecs d’arguments són molt semblants als presentats a Dpreview, fet que demostra la qualitat dels aplecs creats. Finalment, demostrem que les classificacions (rankings) de productes obtinguts amb la nostra implementació i els de Dpreview són molt semblants, mentre que la classificació donada per Amazon no s’assembla a cap de les altres dues.Millions of people interact and share interesting information every day in the Social Web. From daily conversations to comments about products in e-commerce sites, the content generated by people in these sites is huge and diverse. Among the wide diversity of user-contributed content on the web, there is a particular kind that has the potential of being put to good use by intelligent systems: human experiences. People very often use other people's experiences before making decisions, and when these kind of human experiences are expressed and recorded on the web, they can be shared with by large number of people. Nevertheless sometimes this content is not easily accessible, so a person trying to book a hotel may read a few reviews over a few hotels - but cannot possibly read them all. There is a clear need for an in-depth analysis of this kind of information, based on textual expressions of human particular experiences. Our approach, in the framework of the Web of Experiences, aims at acquiring practical knowledge from individual experiences with entities in the real world expressed in textual form. Moreover, this knowledge has to be represented in a way that facilitates the reuse of the experiential knowledge by other individuals with different preferences. Our approach has three stages: First, we extract the most salient set of aspects used by the individuals to describe their experiences with the entities in a domain. Second, using the set of extracted aspects, we group them in concepts to create a concept vocabulary that models the set of issues addressed in the reviews. Third, using the vocabulary of concepts, we create a bundle of arguments for each entity. An argument bundle characterizes the pros and cons of an entity, aggregating practical knowledge from judgments written by individuals with different biases and preferences. Moreover, we show how argument bundles allow us to define the notions of user query and the satisfaction degree of a bundle by a user query, proving that argument bundles are not only capable of representing practical knowledge but they are also useful to perform inference given a set of user preferences specified in a query. We evaluate the argument bundles of our approach with the Amazon score ratings and the camera characterizations of Dpreview. We show that pro and con arguments are very close to those listed in Dpreview. Evaluating entity rankings, we show that Dpreview and our approach give congruent rankings, while Amazon's is not congruent neither with Dpreview's or ours

Concept discovery and argument bundles in the web of experiences /

Milions de persones interactuen i comparteixen informació cada dia a la Web. Des de converses intranscendents fins a comentaris sobre productes en tendes online, el contingut generat per les persones a la Web és enorme i divers. I entre aquests continguts n'hi ha un particularment interessant: les experiències. La gent escolta, llegeix i considera les experiències d'altri abans de prendre decisions, com per exemple comprar-se una càmera digital o anar de viatge a algun lloc exòtic. I quan aquestes experiències estan guardades a la Web, són accessibles per un gran nombre de persones. Malauradament, aquest contingut no és fàcilment accessible: Una persona interessada en anar-se'n de vacances a un hotel probablement llegirà unes quantes experiències d'altra gent que ha anat prèviament a aquest hotel per descobrir que n'opinen, però segurament no podrà llegir-les totes. D'aquesta manera ignorarà informació i experiències d'altra gent que li haurien estat profitoses de cara al seu viatge. Així doncs, considerem que hi ha una clara necessitat d'un anàlisis més profund d'aquesta informació continguda en les experiències de persones, per facilitar-ne el seu ús. El nostre enfocament es troba en el context de la Web de les Experiències, i es basa en extreure i adquirir coneixement pràctic d'experiències individuals respecte entitats del món real expressades en forma textual. A més a més, aquest coneixement han de ser tractat i representat de manera que permeti la seva reutilització per altres persones amb diferents interessos i preferències. Aquest procés està dividit en tres parts: Primer, extraiem les paraules més important utilitzades en les experiències de les diferents persones per descriure opinions sobre entitats. Seguidament, utilitzant el conjunt de paraules extretes, les agrupem en conceptes i creem un vocabulari de conceptes, que ens ajuda a descobrir els aspectes més importants de cada entitat segons les experiències viscudes per cada individu. Finalment, utilitzant el vocabulari de conceptes, creem els aplecs d'arguments de cada entitat. Els aplecs d'arguments caracteritzen els pros i els cons de cada entitat, i agreguen el coneixement pràctic extret de les experiències escrites per cada individu. A més amés, demostrem que els aplecs d'arguments, a part de ser útils per a representar el coneixement pràctic de les experiències, permeten fer inferència sobre quina entitat és la més adequada per cada individual, considerant el conjunt de preferències de cada individu. En aquesta tesi avaluem els aplecs d'arguments amb les puntuacions dels productes d'Amazon i les caracteritzacions de les càmeres de Dpreview, una web especialitzada en càmeres digitals. Demostrem com els arguments pro i con dels nostres aplecs d'arguments són molt semblants als presentats a Dpreview, fet que demostra la qualitat dels aplecs creats. Finalment, demostrem que les classificacions (rankings) de productes obtinguts amb la nostra implementació i els de Dpreview són molt semblants, mentre que la classificació donada per Amazon no s'assembla a cap de les altres dues.Millions of people interact and share interesting information every day in the Social Web. From daily conversations to comments about products in e-commerce sites, the content generated by people in these sites is huge and diverse. Among the wide diversity of user-contributed content on the web, there is a particular kind that has the potential of being put to good use by intelligent systems: human experiences. People very often use other people's experiences before making decisions, and when these kind of human experiences are expressed and recorded on the web, they can be shared with by large number of people. Nevertheless sometimes this content is not easily accessible, so a person trying to book a hotel may read a few reviews over a few hotels - but cannot possibly read them all. There is a clear need for an in-depth analysis of this kind of information, based on textual expressions of human particular experiences. Our approach, in the framework of the Web of Experiences, aims at acquiring practical knowledge from individual experiences with entities in the real world expressed in textual form. Moreover, this knowledge has to be represented in a way that facilitates the reuse of the experiential knowledge by other individuals with different preferences. Our approach has three stages: First, we extract the most salient set of aspects used by the individuals to describe their experiences with the entities in a domain. Second, using the set of extracted aspects, we group them in concepts to create a concept vocabulary that models the set of issues addressed in the reviews. Third, using the vocabulary of concepts, we create a bundle of arguments for each entity. An argument bundle characterizes the pros and cons of an entity, aggregating practical knowledge from judgments written by individuals with different biases and preferences. Moreover, we show how argument bundles allow us to define the notions of user query and the satisfaction degree of a bundle by a user query, proving that argument bundles are not only capable of representing practical knowledge but they are also useful to perform inference given a set of user preferences specified in a query. We evaluate the argument bundles of our approach with the Amazon score ratings and the camera characterizations of Dpreview. We show that pro and con arguments are very close to those listed in Dpreview. Evaluating entity rankings, we show that Dpreview and our approach give congruent rankings, while Amazon's is not congruent neither with Dpreview's or ours

Preferences in Case-Based Reasoning

Case-based reasoning (CBR) is a well-established problem solving paradigm that has been used in a wide range of real-world applications. Despite its great practical success, work on the theoretical foundations of CBR is still under way, and a coherent and universally applicable methodological framework is yet missing. The absence of such a framework inspired the motivation for the work developed in this thesis. Drawing on recent research on preference handling in Artificial Intelligence and related fields, the goal of this work is to develop a well theoretically-founded framework on the basis of formal concepts and methods for knowledge representation and reasoning with preferences

A semi-automatic computer-aided assessment framework for primary mathematics

Assessment and feedback processes shape students behaviour, learning and skill development. Computer-aided assessments are increasingly being used to support problem-solving, marking and feedback activities. However, many computer-aided assessment environments only replicate traditional pencil-and-paper tasks. Attention is on grading and providing feedback on the final product of assessment tasks rather than the processes of problem solving. Focusing on steps and problem-solving processes can help teachers to diagnose strengths and weaknesses, discover problem-solving strategies, and to provide appropriate feedback to students. This thesis presents a semi-automatic framework for capturing and marking students solution steps in the context of elementary school mathematics. The first focus is on providing an interactive touch-based tool called MuTAT to facilitate interactive problem solving for students. The second focus is on providing a marking tool named Marking Assistant which utilises the case-based reasoning artificial intelligence methodology to carry out marking and feedback activities more efficiently and consistently. Results from studies carried out with students showed that the MuTAT prototype tool was usable, and performance scores on it were comparable to those obtained when paper-and-pencil was used. More importantly, the MuTAT provided more explicit information on the problem-solving process, showing the students thinking. The captured data allowed for the detection of arithmetic strategies used by the students. Exploratory studies conducted using the Marking Assistant prototype showed that 26% savings in marking time can be achieved compared to traditional paper-and-pencil marking and feedback. The broad feedback capabilities the research tools provided can enable teachers to evaluate whether intended learning outcomes are being achieved and so decide on required pedagogical interventions. The implications of these results are that innovative CAA environments can enable more direct and engaging assessments which can reduce staff workloads while improving the quality of assessment and feedback for students

Advances in Public Transport Platform for the Development of Sustainability Cities

Modern societies demand high and varied mobility, which in turn requires a complex transport system adapted to social needs that guarantees the movement of people and goods in an economically efficient and safe way, but all are subject to a new environmental rationality and the new logic of the paradigm of sustainability. From this perspective, an efficient and flexible transport system that provides intelligent and sustainable mobility patterns is essential to our economy and our quality of life. The current transport system poses growing and significant challenges for the environment, human health, and sustainability, while current mobility schemes have focused much more on the private vehicle that has conditioned both the lifestyles of citizens and cities, as well as urban and territorial sustainability. Transport has a very considerable weight in the framework of sustainable development due to environmental pressures, associated social and economic effects, and interrelations with other sectors. The continuous growth that this sector has experienced over the last few years and its foreseeable increase, even considering the change in trends due to the current situation of generalized crisis, make the challenge of sustainable transport a strategic priority at local, national, European, and global levels. This Special Issue will pay attention to all those research approaches focused on the relationship between evolution in the area of transport with a high incidence in the environment from the perspective of efficiency

Establishing User Requirements for a Recommender System in an Online Union Catalogue: an Investigation of WorldCat.org

This project, undertaken in collaboration with OCLC, aimed to investigate the potential role of recommendations within WorldCat, the publicly accessible union catalogue of libraries participating in the OCLC global cooperative. The goal of the project was a set of conceptual design guidelines for a WorldCat.org recommender system, based on a comprehensive understanding of the systems users and their needs. Taking a mixed-methods approach, the investigation consisted of four phases. Phase one consisted of twenty-one focus groups with key user goups held in three locations; the UK, the US, and Australia and New Zealand. Phase 2 consisted of a pop-up survey implemented on WorldCat.org, and gathered 2,918 responses. Phase three represented an analysis of two months of WorldCat.org transaction log data, consisting of over 15,000,000 sessions. Phase four was a lab based user study investigating and comparing the use of WorldCat.org with Amazon. Findings from each strand were integrated, and the key themes to emerge from the research are discussed. Different methods of classifying the WorldCat.org user population are presented, along with a taxonomy of work- and search-tasks. Key perspectives on the utility of a recommender system are considered, along with a reflection on how the information search behaviour exhibited by users interacting with recommendations while undertaking typical catalogue tasks can be interpreted. Based on the enriched perspective of the system, and the role of recommendation in the catalogue, a series of conceptual design specifications are presented for the development of a WorldCat.org recommender system

La terminología de la gastronomía puertorriqueña y su traducción al inglés

[ES] La cocina se presenta como un espacio en el que los alimentos se transforman en cultura. La receta, particularmente, aquella que se enmarca en el contexto de un libro vinculado a una cocina nacional, se configura como un acto de comunicación especializada en el que se integran el conocimiento técnico y la definición de la identidad. Estudiamos el entramado que subyace a la terminología utilizada en cinco libros de recetas de Puerto Rico, en su versión original y en su traducción al inglés. Los textos de los que extraemos los términos objeto de análisis se publicaron en momentos clave de la historia puertorriqueña: la década de los cincuenta del siglo XX, marcada por los cambios políticos en la isla con respecto a su relación con Estados Unidos, y la primera década del siglo XXI, momento en que el movimiento “foodie” se encuentra en auge. A fin de representar los términos en una base de datos terminológica que dé cuenta de las categorías y relaciones conceptuales del dominio, combinamos el estudio de corpus paralelos con fuentes de referencia, estudios semánticos y ontologías que describen el dominio culinario desde diferentes perspectivas. El estudio se inserta en los Estudios de Traducción y en la Terminología. [EN] In the kitchen, food transforms into culture. Recipes, particularly those framed in the context of recipe books linked to a national cuisine, stand as an act of specialized communication that combines technical knowledge with the definition of identity. We describe the framework that underlies the terminology used in a sample of recipes from five iconic Puerto Rican cookbooks, both in their original version in Spanish and in their English translation. The texts included in the corpus were published during key periods in Puerto Rican history, the fifties of the 20th century, an era marked by political changes on the island dealing with its relationship to the United States, and the first decade of the 21st century, a decade characterized by a “foodie boom”. In order to create a terminological database that gives an adequate account of the categories and conceptual relations of this domain, we combine the analysis of parallel corpora with lexicographic resources, semantic studies, and ontologies that describe the culinary domain from different points of view. The theoretical framework includes literature from both Translation Studies and Terminology