Knowledge aggregation in people recommender systems : matching skills to tasks

People recommender systems (PRS) are a special type of RS. They are often adopted to identify people capable of performing a task. Recommending people poses several challenges not exhibited in traditional RS. Elements such as availability, overload, unresponsiveness, and bad recommendations can have adverse effects. This thesis explores how people’s preferences can be elicited for single-event matchmaking under uncertainty and how to align them with appropriate tasks. Different methodologies are introduced to profile people, each based on the nature of the information from which it was obtained. These methodologies are developed into three use cases to illustrate the challenges of PRS and the steps taken to address them. Each one emphasizes the priorities of the matching process and the constraints under which these recommendations are made. First, multi-criteria profiles are derived completely from heterogeneous sources in an implicit manner characterizing users from multiple perspectives and multi-dimensional points-of-view without influence from the user. The profiles are introduced to the conference reviewer assignment problem. Attention is given to distribute people across items in order reduce potential overloading of a person, and neglect or rejection of a task. Second, people’s areas of interest are inferred from their resumes and expressed in terms of their uncertainty avoiding explicit elicitation from an individual or outsider. The profile is applied to a personnel selection problem where emphasis is placed on the preferences of the candidate leading to an asymmetric matching process. Third, profiles are created by integrating implicit information and explicitly stated attributes. A model is developed to classify citizens according to their lifestyles which maintains the original information in the data set throughout the cluster formation. These use cases serve as pilot tests for generalization to real-life implementations. Areas for future application are discussed from new perspectives.Els sistemes de recomanació de persones (PRS) són un tipus especial de sistemes recomanadors (RS). Sovint s’utilitzen per identificar persones per a realitzar una tasca. La recomanació de persones comporta diversos reptes no exposats en la RS tradicional. Elements com la disponibilitat, la sobrecàrrega, la falta de resposta i les recomanacions incorrectes poden tenir efectes adversos. En aquesta tesi s'explora com es poden obtenir les preferències dels usuaris per a la definició d'assignacions sota incertesa i com aquestes assignacions es poden alinear amb tasques definides. S'introdueixen diferents metodologies per definir el perfil d’usuaris, cadascun en funció de la naturalesa de la informació necessària. Aquestes metodologies es desenvolupen i s’apliquen en tres casos d’ús per il·lustrar els reptes dels PRS i els passos realitzats per abordar-los. Cadascun destaca les prioritats del procés, l’encaix de les recomanacions i les seves limitacions. En el primer cas, els perfils es deriven de variables heterogènies de manera implícita per tal de caracteritzar als usuaris des de múltiples perspectives i punts de vista multidimensionals sense la influència explícita de l’usuari. Això s’aplica al problema d'assignació d’avaluadors per a articles de conferències. Es presta especial atenció al fet de distribuir els avaluadors entre articles per tal de reduir la sobrecàrrega potencial d'una persona i el neguit o el rebuig a la tasca. En el segon cas, les àrees d’interès per a caracteritzar les persones es dedueixen dels seus currículums i s’expressen en termes d’incertesa evitant que els interessos es demanin explícitament a les persones. El sistema s'aplica a un problema de selecció de personal on es posa èmfasi en les preferències del candidat que condueixen a un procés d’encaix asimètric. En el tercer cas, els perfils dels usuaris es defineixen integrant informació implícita i atributs indicats explícitament. Es desenvolupa un model per classificar els ciutadans segons els seus estils de vida que manté la informació original del conjunt de dades del clúster al que ell pertany. Finalment, s’analitzen aquests casos com a proves pilot per generalitzar implementacions en futurs casos reals. Es discuteixen les àrees d'aplicació futures i noves perspectives.Postprint (published version

Evolving routines and strategic change. Learning in practice through knowledge and knowing in evolving routines

A travers l'évolution d'une routine à fort contenu de connaissance : l'évaluation par les pairs d'articles scientifiques, on analyse l'impact des pratiques concrètes pour faire évoluer les processus stratégiques de l'organisation.routine;ingénierie des connaissances;micro-pratiques;caractérisation

A fuzzy-based evaluation of financial risks in build-own-operate-transfer water supply projects

The build–own–operate–transfer (BOOT) scheme is widely used for the provision of new bulk water supply. However, this scheme is complex and carries significant financial risks because of the characteristics of the water sector and the involvement of public-private stakeholders with new and extended responsibilities, large private capital, and long contract duration. Drawing on the Nungua Seawater Desalination Plant (NSDP) in Ghana, this study seeks to identify and assess the critical financial risks associated with BOOT water supply projects and evaluate the financial risk level of the NSDP project. The risks and their relative criticality on the NSDP project are investigated by using a questionnaire survey method. The questionnaire was formulated with a set of 18 risks derived from extant literature and project documentation. Perceived critical financial risks affecting the NSDP project were assessed by a team of experts who had direct involvement in the project. A fuzzy synthetic evaluation suggests that the project is financially risky and that all the risks are critical to the project. Bankruptcy of consortium members, unfavorable economy of the host country, uncertainty in tariff adjustment of water products, rate of return restrictions, and availability problem of private capital are the five most highly-ranked risks. The fuzzy technique is used to represent and model experiential knowledge of the survey participants and to address the fuzziness of their expert judgments. The study’s results facilitate prioritization of risks and a comprehensive risk management program during the lifecycle of the case project and future projects. The fuzzy technique is suitable for early phases of BOOT projects to prioritize the risks that require a detailed analysis and to predict the risk level of a project