Preference Networks: Probabilistic Models for Recommendation Systems

Recommender systems are important to help users select relevant and personalised information over massive amounts of data available. We propose an unified framework called Preference Network (PN) that jointly models various types of domain knowledge for the task of recommendation. The PN is a probabilistic model that systematically combines both content-based filtering and collaborative filtering into a single conditional Markov random field. Once estimated, it serves as a probabilistic database that supports various useful queries such as rating prediction and top-$N$ recommendation. To handle the challenging problem of learning large networks of users and items, we employ a simple but effective pseudo-likelihood with regularisation. Experiments on the movie rating data demonstrate the merits of the PN.Comment: In Proc. of 6th Australasian Data Mining Conference (AusDM), Gold Coast, Australia, pages 195--202, 200

Preference networks : probabilistic models for recommendation systems

Recommender systems are important to help users select relevant and personalised information over massive amounts of data available. We propose an unified framework called Preference Network (PN) that jointly models various types of domain knowledge for the task of recommendation. The PN is a probabilistic model that systematically combines both content-based filtering and collaborative filtering into a single conditional Markov random field. Once estimated, it serves as a probabilistic database that supports various useful queries such as rating prediction and top-N recommendation. To handle the challenging problem of learning large networks of users and items, we employ a simple but effective pseudo-likelihood with regularisation. Experiments on the movie rating data demonstrate the merits of the PN.<br /

Environmental conflict analysis using an integrated grey clustering and entropy-weight method: A case study of a mining project in Peru

[EN] Environmental conflict analysis (henceforth ECA) has become a key factor for the viability of projects and welfare of affected populations. In this study, we propose an approach for ECA using an integrated grey clustering and entropy-weight method (The IGCEW method). The case study considered a mining project in northern Peru. Three stakeholder groups and seven criteria were identified. The data were gathered by conducting field interviews. The results revealed that for the groups urban population, rural population and specialists, the project would have a positive, negative and normal social impact, respectively. We also noted that the criteria most likely to generate environmental conflicts in order of importance were: access to drinking water, poverty, GDP per capita and employment. These results could help regional and central governments to seek appropriate measures to prevent environmental conflicts. The proposed method showed practical results and a potential for application to other types of projects.Delgado-Villanueva, KA.; Romero Gil, I. (2016). Environmental conflict analysis using an integrated grey clustering and entropy-weight method: A case study of a mining project in Peru. Environmental Modelling & Software. 77:108-121. doi:10.1016/j.envsoft.2015.12.011S1081217

Methodological proposal for social impact assessment and environmental conflict analysis

Tesis por compendio[EN] Social impact assessment (SIA) is a part of environmental impact assessment (EIA), which is characterized by a high level of uncertainty and the subjective aspects that are presents in the methods used during its conduction. In addition, environmental conflict analysis (ECA) has become a key factor for the viability of projects and welfare of affected populations. In this thesis, an integrated method for SIA and ECA is proposed, by the combination of the grey clustering method and the entropy-weight method. SIA was performed using the grey clustering method, which enables qualitative information coming from a stakeholder group to be quantified. In turn, ECA was performed using the entropy-weight method, which identifies the criteria in which there is greater divergence between stakeholder groups, thus enabling to establish measures to prevent potential environmental conflicts. Then, in order to apply and test the proposed integrated method, two case studies were conducted. The first case study was a mining project in northern Peru. In this study, three stakeholder groups and seven criteria were identified. The results revealed that for the urban population group and the rural population group, the project would have a positive and negative social impact, respectively. For the group of specialists the project would have a normal social impact. It was also noted that the criteria most likely to generate environmental conflicts in order of importance were: access to drinking water, poverty, GDP per capita, and employment. The second case study considered was a hydrocarbon exploration project located in the Gulf of Valencia, Spain. In this study, four stakeholder groups and four criteria were identified. The results revealed that for the group of specialists the project would have a negative social impact, and contrary perceptions were shown between the group of those directly affected by the project and the group of citizens in favour. It was also noted that the criteria most likely to generate environmental conflict were the percentage of unemployment and GDP per capita. The proposed integrated method in this thesis showed great potential on the studied cases, and could be applied to other contexts and other projects, such as water resources management, industrial projects, construction projects, and to measure social impact and prevent conflicts during the implementation of government policies and programs.[ES] La evaluación del impacto social (SIA) forma parte de la evaluación de impacto ambiental (EIA), y está caracterizada por su alto nivel de incertidumbre, y por los aspectos subjetivos presentes en los métodos usados para su realización. Por otro lado, el análisis del conflicto ambiental (ECA) se ha convertido en un factor clave para la viabilidad de los proyectos y el bienestar de la población afectada. En esta tesis, se propone un método integrado para la SIA y el ECA, mediante la combinación de los métodos grey clustering y entropy-weight. La SIA fue desarrollada usando el método grey clustering, el cual permite cuantificar la información cualitativa recogida de los grupos de interés o stakeholders. Sucesivamente, el ECA fue realizado usando el método entropy-weight, el cual identifica los criterios en los cuales existe gran divergencia entre los grupos de interés, permitiendo así establecer medidas para prevenir potenciales conflictos ambientales. Luego, con el fin de aplicar y testear el método integrado propuesto fueron realizados dos casos de estudio. El primer caso de estudio fue un proyecto minero ubicado en el norte de Perú. En este estudio se identificaron tres grupos de interés y siete criterios. Los resultados revelaron que para el grupo población urbana y el grupo población rural, el proyecto tendría un impacto social positivo y negativo, respectivamente. Para el grupo de los especialistas el proyecto tendría un impacto social normal. También fue notado que los criterios más probables de generar conflicto ambiental en orden de importancia fueron: acceso al agua potable, pobreza, PIB per cápita, y empleo. El segundo caso de estudio considerado fue un proyecto de exploración de hidrocarburos ubicado en el Golfo de Valencia, España. En este estudio se identificaron cuatro grupos de interés y cuatro criterios. Los resultados revelaron que para el grupo de los especialistas el proyecto tendría un impacto social negativo, y contrarias percepciones se encontraron entre el grupo de los directamente afectados y el grupo de los ciudadanos a favor. También fue notado que los criterios más probables de generar conflicto ambiental fueron el porcentaje de desempleo y el PIB per cápita. El método integrado propuesto en esta tesis mostró un gran potencial sobre los casos estudiados, y podría ser aplicado a otros contextos y otros tipos de proyectos, tales como gestión de recursos hídricos, proyectos industriales, proyectos de construcción de obras públicas, y para medir el impacto social y prevenir conflictos durante la aplicación de políticas y programas gubernamentales.[CA] L'avaluació de l'impacte social (SIA) és una part de l'avaluació de l'impacte ambiental (EIA), la qual està caracteritzada pel seu alt nivell d'incertitud i els aspectes subjectius presents en els mètodes amprats durant la seua conducció. A més, la anàlisis del conflicte ambiental (ECA) s'ha convertit en un factor clau per a la viabilitat dels projectes i el benestar de la població afectada. En esta tesis es proposa un mètode integrat per a l'avaluació de l'impacte social i la anàlisis del conflicte ambiental, mitjançant la combinació del mètode grey clustering i el mètode entropy-weight. L'avaluació de l'impacte social ha segut realitzada usant el mètode grey clustering, el qual permet que la informació qualitativa arreplegada dels grups d'interès siga quantificada. Successivament, la anàlisis del conflicte ambiental ha segut realitzada usant el mètode entropy-weight, el qual identifica els criteris en els quals existeix gran divergència entre els grups d'interès, la qual cosa permet establir mides per a prevenir conflictes ambientals potencials. Després, amb la finalitat d'aplicar i testejar el mètode integrat proposat han segut realitzats dos casos d'estudi. El primer d'ells ha segut un projecte miner al nord de Perú. En aquest estudi, tres grups d'interès i set criteris foren identificats. Els resultats revelaren que per al grup població-urbana i el grup població-rural, el projecte experimentaria un positiu i un negatiu impacte social respectivament. Per al grup dels especialistes el projecte tindria un impacte social normal. Per altra banda també va ser reconegut que els criteris més probables de generar conflicte ambiental en orde d'importància foren: accés a l'aigua potable, pobresa, PIB per càpita, i ofici. El segon cas d'estudi considerat va ser un projecte d'exploració d'hidrocarburs ubicat al Golf de València, Espanya. En este estudi, quatre grups d'interès i quatre criteris foren identificats. Els resultats revelaren que per al grup dels especialistes el projecte tindria un impacte social negatiu, mentre que entre el grup dels directament afectats i el grup dels ciutadans a favor es mostraren percepcions contraries. Va ser també reconegut que els criteris més probables de generar conflicte ambiental foren el percentatge de desocupació i el PIB per càpita. El mètode integrat proposat en aquesta tesis mostra un gran potencial sobre els casos estudiats, i pot ser aplicat a altres contexts i altres tipus de projectes com gestió de recursos hídrics, projectes industrials i projectes de construcció d'obres públiques. A més pot fer-se servir per mesurar l'impacte social i prevenir conflictes durant l'aplicació de polítiques i programes governamentals.Delgado Villanueva, KA. (2016). Methodological proposal for social impact assessment and environmental conflict analysis [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/64063TESISCompendi

A Novel Non-Negative Matrix Factorization Method for Recommender Systems

Recommender systems collect various kinds of data to create their recommendations. Collaborative filtering is a common technique in this area. This technique gathers and analyzes information on users preferences, and then estimates what users will like based on their similarity to other users. However, most of current collaborative filtering approaches have faced two problems: sparsity and scalability. This paper proposes a novel method by applying non-negative matrix factorization, which alleviates these problems via matrix factorization and similarity. Non-negative matrix factorization attempts to find two non-negative matrices whose product can well approximate the original matrix. It also imposes non-negative constraints on the latent factors. The proposed method presents novel update rules to learn the latent factors for predicting unknown rating. Unlike most of collaborative filtering methods, the proposed method can predict all the unknown ratings. It is easily implemented and its computational complexity is very low. Empirical studies on MovieLens and Book-Crossing datasets display that the proposed method is more tolerant against the problems of sparsity and scalability, and obtains good results

Multi-Criteria Evaluation in Support of the Decision-Making Process in Highway Construction Projects

The decision-making process in highway construction projects identifies and selects the optimal alternative based on the user requirements and evaluation criteria. The current practice of the decision-making process does not consider all construction impacts in an integrated decision-making process. This dissertation developed a multi-criteria evaluation framework to support the decision-making process in highway construction projects. In addition to the construction cost and mobility impacts, reliability, safety, and emission impacts are assessed at different evaluation levels and used as inputs to the decision-making process. Two levels of analysis, referred to as the planning level and operation level, are proposed in this research to provide input to a Multi-Criteria Decision-Making (MCDM) process that considers user prioritization of the assessed criteria. The planning level analysis provides faster and less detailed assessments of the inputs to the MCDM utilizing analytical tools, mainly in a spreadsheet format. The second level of analysis produces more detailed inputs to the MCDM and utilizes a combination of mesoscopic simulation-based dynamic traffic assignment tool, and microscopic simulation tool, combined with other utilities. The outputs generated from the two levels of analysis are used as inputs to a decision-making process based on present worth analysis and the Fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Situation) MCDM method and the results are compared