Towards Diversity in Recommendations Using Social Networks

While there has been a lot of research towards improving the accuracy of recommender systems, the resulting systems have tended to become increasingly narrow in suggestion variety. An emerging trend in recommendation systems is to actively seek out diversity in recommendations, where the aim is to provide unexpected, varied, and serendipitous recommendations to the user. Our main contribution in this paper is a new approach to diversity in recommendations called "Social Diversity," a technique that uses social network information to diversify recommendation results. Social Diversity utilizes social networks in recommender systems to leverage the diverse underlying preferences of different user communities to introduce diversity into recommendations. This form of diversification ensures that users in different social networks (who may not collaborate in real life, since they are in a different network) share information, helping to prevent siloization of knowledge and recommendations. We describe our approach and show its feasibility in providing diverse recommendations for the MovieLens dataset

The horse before the cart: improving the accuracy of taxonomic directions when building tag hierarchies

Content on the Web is huge and constantly growing, and building taxonomies for such content can help with navigation and organisation, but building taxonomies manually is costly and time-consuming. An alternative is to allow users to construct folksonomies: collective social classifications. Yet, folksonomies are inconsistent and their use for searching and browsing is limited. Approaches have been suggested for acquiring implicit hierarchical structures from folksonomies, however, but these approaches suffer from the ‘popularity-generality’ problem, in that popularity is assumed to be a proxy for generality, i.e. high-level taxonomic terms will occur more often than low-level ones. To tackle this problem, we propose in this paper an improved approach. It is based on the Heymann–Benz algorithm, and works by checking the taxonomic directions against a corpus of text. Our results show that popularity works as a proxy for generality in at most 90.91% of cases, but this can be improved to 95.45% using our approach, which should translate to higher-quality tag hierarchy structure

Diferencias entre las actividades de mantenimiento en los procesos de desarrollo tradicional y open source

Versión electrónica de la ponencia presentada en la XVII Jornadas de Ingeniería del Software y de Bases de Datos (JISBD’2012), celebrada en 2012 en AlmeríaAntecedentes. La creciente importancia del Open Source Software (OSS) ha llevado a los investigadores a estudiar cómo los procesos OSS difieren de los procesos de la ingeniería del software tradicional. Objetivo. Determinar las diferencias y similitudes entre las actividades del proceso de mantenimiento seguido por la comunidad OSS y el establecido por el estándar IEEE 1074:2006. Método. Para conocer las actividades que conforman el proceso de desarrollo OSS realizamos un Systematic Mapping Study. Posteriormente, realizamos un emparejamiento entre las actividades del estándar IEEE 1074:2006 con las actividades del proceso OSS. Resultados. Encontramos un total de 22 estudios primarios. De estos estudios, el 73% contaban con actividades relacionadas con el proceso de mantenimiento. Conclusiones. El proceso de mantenimiento tradicional del software no encaja con lo que ocurre en la comunidad OSS. En su lugar, puede ser mejor caracterizar la dinámica general de la evolución OSS como reinvención. Esta reinvención emerge continuamente de la adaptación, aprendizaje, y mejora de las funcionalidades y calidad del OSS. Los proyectos OSS evolucionan a través de mejoras menores donde participan tanto usuarios como desarrolladores.Esta investigación ha sido financiada por el Ministerio de Ciencia e Innovación de España con los proyectos titulados “Tecnologías para la Replicación y Síntesis de Experimentos en IS” (TIN2011-23216) y “Go Lite” (TIN2011-24139)

Diferencias entre las Actividades de Mantenimiento en los Procesos de Desarrollo Tradicional y Open Source

Antecedentes. La creciente importancia del Open Source Software (OSS) ha llevado a los investigadores a estudiar cómo los procesos OSS difieren de los procesos de la ingeniería del software tradicional. Objetivo. Determinar las diferencias y similitudes entre las actividades del proceso de mantenimiento seguido por la comunidad OSS y el establecido por el estándar IEEE 1074:2006. Método. Para conocer las actividades que conforman el proceso de desarrollo OSS realizamos un Systematic Mapping Study. Posteriormente, realizamos un emparejamiento entre las actividades del estándar IEEE 1074:2006 con las actividades del proceso OSS. Resultados. Encontramos un total de 22 estudios primarios. De estos estudios, el 73% contaba con actividades relacionadas con el proceso de mantenimiento. Conclusiones. El proceso de mantenimiento tradicional del software no encaja con lo que ocurre en la comunidad OSS. En su lugar, puede ser mejor caracterizar la dinámica general de la evolución OSS como reinvención. Esta reinvención emerge continuamente de la adaptación, aprendizaje, y mejora de las funcionalidadess y calidad del OSS. Los proyectos OSS evolucionan a través de mejoras menores donde participan tanto usuarios como desarrolladores

Collaborative semantic structuring of folksonomies (short article)

The advent of tagging and folksonomies for organizing shared resources on the social Web brought promising opportunities to help communities of users capture their knowledge. However, the lack of semantics, or the spelling variations between tags lowers the potentials for browsing and exploring these data. To overcome these limitations, we propose exploiting the interactions between the users and the systems to validate or correct semantic analysis automatically applied to the tags. This process is based upon our model of the assistance of folksonomies enrichment which supports conflictual points of view. Several strategies can then be applied to propose novel browsing facilities to users

Semantic Social Network Analysis: A Concrete Case

In this chapter we present our approach to analyzing such semantic social networks and capturing collective intelligence from collaborative interactions to challenge requirements of Enterprise 2.0. Our tools and models have been tested on an anonymized dataset from Ipernity.com, one of the biggest French social web sites centered on multimedia sharing. This dataset contains over 60,000 users, around half a million declared relationships of three types, and millions of interactions (messages, comments on resources, etc.). We show that the enriched semantic web framework is particularly well-suited for representing online social networks, for identifying their key features and for predicting their evolution. Organizing huge quantity of socially produced information is necessary for a future acceptance of social applications in corporate contexts

Port Sustainability Management System for Smaller Ports in Cornwall and Devon

Many smaller ports in Cornwall and Devon (CAD) are situated in environmentally sensitive habitats and generate benefits for stakeholders and local communities. Such ports are often embedded in tourist based economies. Increasing environmental legislation is placing a strain on the resources of smaller ports making compliance a threat to profitability and thus the future of some ports and local economies. Over-reliance on environmental management systems (EMS) across the ports industry has predominated over the importance of holistic sustainability. This project develops and disseminates a port sustainability management system (PSMS) in CAD, assisting ports to plan marine and maritime operations more sustainably, to facilitate mitigation of potential risks, to increase knowledge and awareness of port sustainability, and to promote the adoption of a proactive stance towards sustainable port management. A constructivist philosophy suited a multiple methods research design which included ethnographic content analysis (ECA), statistical verification of qualitative coding, nine scoping interviews, and eight semi-structured interviews during the main phase of data collection. The seven Harbour Masters (HMs) in this phase represented all port governance types found in the UK. Charmaz’s grounded theory (GT) methodology guided the collection and analysis of primary data between August 2012 and February 2013 to create new theory using an inductive constructivist approach. Validation by fifteen of the thirty local HMs during industry testing revealed numerous advantages and benefits of deploying PSMS which is estimated to generate £50,000 worth of benefits per port annually, and £3,865,005 for the 15 participating ports over 5 years. A new model of smaller port sustainability has emerged. PSMS has eleven pillars of sustainability which underpin the spectrum of port operations. Within this model, each pillar is equally important in contributing to the overall sustainability of a port, and neglect of one could jeopardise sustainability overall and potentially cause a chain reaction with other pillars.European Social Fund Combined Universities of Cornwall (ESF-CUC

SPA: A Graph Spectral Alignment Perspective for Domain Adaptation

Unsupervised domain adaptation (UDA) is a pivotal form in machine learning to extend the in-domain model to the distinctive target domains where the data distributions differ. Most prior works focus on capturing the inter-domain transferability but largely overlook rich intra-domain structures, which empirically results in even worse discriminability. In this work, we introduce a novel graph SPectral Alignment (SPA) framework to tackle the tradeoff. The core of our method is briefly condensed as follows: (i)-by casting the DA problem to graph primitives, SPA composes a coarse graph alignment mechanism with a novel spectral regularizer towards aligning the domain graphs in eigenspaces; (ii)-we further develop a fine-grained message propagation module -- upon a novel neighbor-aware self-training mechanism -- in order for enhanced discriminability in the target domain. On standardized benchmarks, the extensive experiments of SPA demonstrate that its performance has surpassed the existing cutting-edge DA methods. Coupled with dense model analysis, we conclude that our approach indeed possesses superior efficacy, robustness, discriminability, and transferability. Code and data are available at: https://github.com/CrownX/SPA.Comment: NeurIPS 2023 camera read

Potential Indirect Relationships in Productive Networks

Productive Networks, such as Social Networks Services, organize evidence about human behavior. This evidence is independent of the network content type, and may support the discovery of new relationships between users and content, or with other users. These indirect relationships are important for recommendation systems, and systems where potential relationships between users and content (e.g., locations) is relevant, such as with the emergency management domain, where the discovery of relationships between users and locations on productive networks may enable the identification of population density variations, increasing the accuracy of emergency alerts. This thesis presents a Productive Networks model, which enables the development of a methodology for indirect relationships discovery, using the metadata on the network, and avoiding the computational cost of content analysis. We designed and conducted a set of experiments to evaluate our proposals. Our results are twofold: firstly, the productive network model is sufficiently robust to represent a wide range of networks; secondly, the indirect relationship discovery methodology successfully identifies relevant relationships between users and content. We also present applications of the model and methodology in several contexts