Submitted by Sonia Burnier (sdesouza@ibict.br) on 2012-07-19T16:46:10Z No. of bitstreams: 1 SilviaBarcellosSouthwick2001.pdf: 1110117 bytes, checksum: f1fca9461f81bd17fca8c3e1966570aa (MD5) / Made available in DSpace on 2012-07-19T16:46:10Z (GMT). No. of bitstreams: 1 SilviaBarcellosSouthwick2001.pdf: 1110117 bytes, checksum: f1fca9461f81bd17fca8c3e1966570aa (MD5) Previous issue date: 2001 / [en] The internet individual with the opportunity to access unprecdented amounsts of information on any given subject.However, there remain barriers to rerieving the best and most relevant documents.The present study focuses on processes of resolving user ( versus technical) issues.Informations system users have traditionally relied on expert intermediarias for resolving problems.Face-to-face encounters have been he traditional form of human-expert intermediation.Increasinly, however, information-provision services have begun to offer human-mediated information services through computer networks-especially the internet-recognizing the poencial advantages in overcoming barriers of time and space in user-intermeiary communications.Despite the likely increase in this trend future, there remains at this point an inadequate understanding of he effectiveness of these sysems.The present study investigaes intermediation in the context of an asyncronous text-based compuer-mediated medium, such as e-mail and web-orms.The goal of the research is in describing and gaining a further understanding of processes of intemediation.The main objectives are to identify the factors that are perceived as affecting digital intermediation and to investigate how and under what circumstances these factrs miht affect digital intermediation.The research takes the form of anexploratory case study of a hospital library infomation service.The overall approach is naturalistic.Grouunded theory provides a framework for data analysis.In order to elicit a rich and fully infomed accounting of the phenomenon under investigation, the researcher interpret s and relates the diverse human perpectives of the intermediaries, the users, and the researcher herself.This provides a basis for highlighting potentially conflicting, as well as corroborating, evidence.The study contributes at both the conceptual and practical leves to an overall understanding of digital intermediation by producing a descriptive framework of analysis.Nine cateories of factores potentially affecting digital intermediation are identified.These factores form three broad aspets of digital intermediation: media use, question negotiation and personal comminication preference.The researche also proposes directions for future research in the area of reference intermediation in a digital environment.

El treball desenvolupat en aquesta tesi presenta un profund estudi i proveïx solucions innovadores en el camp dels sistemes recomanadors. Els mètodes que usen aquests sistemes per a realitzar les recomanacions, mètodes com el Filtrat Basat en Continguts (FBC), el Filtrat Col·laboratiu (FC) i el Filtrat Basat en Coneixement (FBC), requereixen informació dels usuaris per a predir les preferències per certs productes. Aquesta informació pot ser demogràfica (Gènere, edat, adreça, etc), o avaluacions donades sobre algun producte que van comprar en el passat o informació sobre els seus interessos. Existeixen dues formes d'obtenir aquesta informació: els usuaris ofereixen explícitament aquesta informació o el sistema pot adquirir la informació implícita disponible en les transaccions o historial de recerca dels usuaris. Per exemple, el sistema recomanador de pel·lícules MovieLens (http://movielens.umn.edu/login) demana als usuaris que avaluïn almenys 15 pel·lícules dintre d'una escala de * a * * * * * (horrible, ...., ha de ser vista). El sistema genera recomanacions sobre la base d'aquestes avaluacions. Quan els usuaris no estan registrat en el sistema i aquest no té informació d'ells, alguns sistemes realitzen les recomanacions tenint en compte l'historial de navegació. Amazon.com (http://www.amazon.com) realitza les recomanacions tenint en compte les recerques que un usuari a fet o recomana el producte més venut. No obstant això, aquests sistemes pateixen de certa falta d'informació. Aquest problema és generalment resolt amb l'adquisició d'informació addicional, se li pregunta als usuaris sobre els seus interessos o es cerca aquesta informació en fonts addicionals. La solució proposada en aquesta tesi és buscar aquesta informació en diverses fonts, específicament aquelles que contenen informació implícita sobre les preferències dels usuaris. Aquestes fonts poden ser estructurades com les bases de dades amb informació de compres o poden ser no estructurades com les pàgines web on els usuaris deixen la seva opinió sobre algun producte que van comprar o posseïxen.Nosaltres trobem tres problemes fonamentals per a aconseguir aquest objectiu: 1 . La identificació de fonts amb informació idònia per als sistemes recomanadors.2 . La definició de criteris que permetin la comparança i selecció de les fonts més idònies. 3 . La recuperació d'informació de fonts no estructurades. En aquest sentit, en la tesi proposada s'ha desenvolupat: 1 . Una metodologia que permet la identificació i selecció de les fonts més idònies. Criteris basats en les característiques de les fonts i una mesura de confiança han estat utilitzats per a resoldre el problema de la identificació i selecció de les fonts. 2 . Un mecanisme per a recuperar la informació no estructurada dels usuaris disponible en la web. Tècniques de Text Mining i ontologies s'han utilitzat per a extreure informació i estructurar-la apropiadament perquè la utilitzin els recomanadors. Les contribucions del treball desenvolupat en aquesta tesi doctoral són: 1. Definició d'un conjunt de característiques per a classificar fonts rellevants per als sistemes recomanadors2. Desenvolupament d'una mesura de rellevància de les fonts calculada sobre la base de les característiques definides3. Aplicació d'una mesura de confiança per a obtenir les fonts més fiables. La confiança es definida des de la perspectiva de millora de la recomanació, una font fiable és aquella que permet millorar les recomanacions. 4. Desenvolupament d'un algorisme per a seleccionar, des d'un conjunt de fonts possibles, les més rellevants i fiable utilitzant les mitjanes esmentades en els punts previs. 5. Definició d'una ontologia per a estructurar la informació sobre les preferències dels usuaris que estan disponibles en Internet. 6. Creació d'un procés de mapatge que extreu automàticament informació de les preferències dels usuaris disponibles en la web i posa aquesta informació dintre de l'ontologia. Aquestes contribucions permeten aconseguir dos objectius importants: 1 . Millorament de les recomanacions usant fonts d'informació alternatives que sigui rellevants i fiables.2 . Obtenir informació implícita dels usuaris disponible en Internet. / The work developed in this thesis presents an in-depth study and provides innovative solutions in the field of recommender systems. The methods used by these systems to carry out recommendations, such as Content-Based Filtering (CBF), Collaborative Filtering (CF) and Knowledge-Based Filtering (KBF), require information from users to predict preferences for certain products. This may be demographic information (genre, age and address), evaluations given to certain products in the past or information about their interests. There are two ways of obtaining this information: users offer it explicitly or the system can retrieve the implicit information available in the purchase and search history. For example, the movie recommender system MovieLens (http://movielens.umn.edu/login) asks users to rate at least 15 movies on a scale of * to * * * * * (awful, ... , must be seen). The system generates recommendations based on these evaluations. When users are not registered into the site and it has no information about them, recommender systems make recommendations according to the site search history. Amazon.com (http://www.amazon.com) make recommendations according to the site search history or recommend the best selling products. Nevertheless, these systems suffer from a certain lack of information. This problem is generally solved with the acquisition of additional information; users are asked about their interests or that information is searched for in additional available sources. The solution proposed in this thesis is to look for that information in various sources, specifically those that contain implicit information about user preferences. These sources can be structured like databases with purchasing information or they can be unstructured sources like review pages where users write their experiences and opinions about a product they buy or possess.We have found three fundamental problems to achieve this objective: 1. The identification of sources with suitable information for recommender systems.2. The definition of criteria that allows the comparison and selection of the most suitable sources.3. Retrieving the information from unstructured sources.In this sense, the proposed thesis has developed:1. A methodology that allows the identification and selection of the most suitable sources. Criteria based on the characteristics of sources and a trust measure have been used to solve the problem of identifying and selecting sources.2. A mechanism to retrieve unstructured information from users available on the Web. Text mining techniques and ontologies have been used to extract information and structure it appropriately for use by the recommenders.The contributions of the work developed in this doctoral thesis are:1. Definition of a set of characteristics to classify relevant sources of information for recommender systems.2. Development of a measure of relevance of sources according to characteristics defined in previous point.3. Application of a trust measure to obtain the most reliable sources. Confidence is measured from the perspective of improving the recommendation; a reliable source is one that leads to improved recommendations.4. Development of an algorithm to select, from a set of possible sources, the most relevant and reliable ones according to measures defined in previous points.5. Definition of an ontology to structure information about user preferences that are available on the Internet.6. The creation of a mapping process that automatically extracts information about user preferences available on the web and put in the ontology.These contributions allow us the achievement of two important objectives:1. Improving recommendations using alternative sources of information that are relevant and trustworthy.2. Obtaining implicit information about user available on the Internet.

[pt] Hoje em dia e-learning está se tornando mais importante por possibilitar a disseminação de conhecimento e informação através da internet de uma forma mais rápida e menos dispendiosa. Consequentemente, de modo a filtrar o que é mais relevante e/ou de interesse do usuário, arquiteturas e técnicas de personalização vêm sendo abordadas. Dentre as muitas possibilidades de personalização existentes, a que lida com acessibilidade está se tornando essencial, pois garante que uma grande variedade de usuários possa ter acesso à informação conforme suas necessidades e características. Acessibilidade não é apenas garantir que pessoas com alguma deficiência, ou dificuldade, possam ter acesso à informação, apesar de ser importante e eventualmente ser uma exigência legal. Acessibilidade é também garantir que uma larga variedade de usuários e interfaces possam obter acesso à informação, maximizando assim a audiência potencial. Esta dissertação apresenta uma extensão do LORIS, um sistema de integração de repositórios de objetos de aprendizagem, descrevendo as alterações na sua arquitetura para ser capaz de lidar com acessibilidade e reconhecer diferentes versões de um mesmo objeto de aprendizagem, permitindo assim que um usuário execute uma consulta considerando seu perfil e preferências. Foi desenvolvido um protótipo dos serviços descritos na arquitetura utilizando serviços Web e navegação facetada, bem como padrões web, de e-learning e de acessibilidade. O uso de serviços Web e de padrões visa promover flexibilidade e interoperabilidade, enquanto a navegação facetada, como implementada, permite que o usuário aplique múltiplos filtros aos resultados da consulta sem a necessidade de re-submetê-la. / [en] Nowadays e-learning is becoming more important as it makes possible the dissemination of knowledge and information through the internet in a faster and costless way. Consequently, in order to filter what is more relevant and/or of users interest, architectures and personalization techniques have been raised. Among the many existing possibilities of personalization, the one that deals with accessibility is becoming essential because it guarantees that a wide variety of users may have access to the information according to their preferences and needs. Accessibility is not just about ensuring that disabled people can access information, although this is important and may be a legal requirement. It is also about ensuring that the wide variety of users and devices can all gain access to information, thereby maximizing the potential audience. This dissertation presents an extension of LORIS, an integration system of learning object repositories, describing the changes on its architecture to make it able to deal with accessibility and to recognize different versions of the same learning object, thus allowing a user to execute a query considering his/her preferences and needs. A prototype of the services that are described in the architecture was developed using web services and faceted navigation, as well as e-learning and accessibility standards. The use of web services and standards aims at providing flexibility and interoperability, while the faceted navigation, as implemented, allows the user to apply multiple filters to the query results without the need to resubmit it.