Inferring user interests in microblogging social networks: a survey

With the growing popularity of microblogging services such as Twitter in recent years, an increasing number of users are using these services in their daily lives. The huge volume of information generated by users raises new opportunities in various applications and areas. Inferring user interests plays a significant role in providing personalized recommendations on microblogging services, and also on third-party applications providing social logins via these services, especially in cold-start situations. In this survey, we review user modeling strategies with respect to inferring user interests from previous studies. To this end, we focus on four dimensions of inferring user interest profiles: (1) data collection, (2) representation of user interest profiles, (3) construction and enhancement of user interest profiles, and (4) the evaluation of the constructed profiles. Through this survey, we aim to provide an overview of state-of-the-art user modeling strategies for inferring user interest profiles on microblogging social networks with respect to the four dimensions. For each dimension, we review and summarize previous studies based on specified criteria. Finally, we discuss some challenges and opportunities for future work in this research domain

Moving towards the semantic web: enabling new technologies through the semantic annotation of social contents.

La Web Social ha causat un creixement exponencial dels continguts disponibles deixant enormes quantitats de recursos textuals electrònics que sovint aclaparen els usuaris. Aquest volum d’informació és d’interès per a la comunitat de mineria de dades. Els algorismes de mineria de dades exploten característiques de les entitats per tal de categoritzar-les, agrupar-les o classificar-les segons la seva semblança. Les dades per si mateixes no aporten cap mena de significat: han de ser interpretades per esdevenir informació. Els mètodes tradicionals de mineria de dades no tenen com a objectiu “entendre” el contingut d’un recurs, sinó que extreuen valors numèrics els quals esdevenen models en aplicar-hi càlculs estadístics, que només cobren sentit sota l’anàlisi manual d’un expert. Els darrers anys, motivat per la Web Semàntica, molts investigadors han proposat mètodes semàntics de classificació de dades capaços d’explotar recursos textuals a nivell conceptual. Malgrat això, normalment aquests mètodes depenen de recursos anotats prèviament per poder interpretar semànticament el contingut d’un document. L’ús d’aquests mètodes està estretament relacionat amb l’associació de dades i el seu significat. Aquest treball es centra en el desenvolupament d’una metodologia genèrica capaç de detectar els trets més rellevants d’un recurs textual descobrint la seva associació semàntica, es a dir, enllaçant-los amb conceptes modelats a una ontologia, i detectant els principals temes de discussió. Els mètodes proposats són no supervisats per evitar el coll d’ampolla generat per l’anotació manual, independents del domini (aplicables a qualsevol àrea de coneixement) i flexibles (capaços d’analitzar recursos heterogenis: documents textuals o documents semi-estructurats com els articles de la Viquipèdia o les publicacions de Twitter). El treball ha estat avaluat en els àmbits turístic i mèdic. Per tant, aquesta dissertació és un primer pas cap a l'anotació semàntica automàtica de documents necessària per possibilitar el camí cap a la visió de la Web Semàntica.La Web Social ha provocado un crecimiento exponencial de los contenidos disponibles, dejando enormes cantidades de recursos electrónicos que a menudo abruman a los usuarios. Tal volumen de información es de interés para la comunidad de minería de datos. Los algoritmos de minería de datos explotan características de las entidades para categorizarlas, agruparlas o clasificarlas según su semejanza. Los datos por sí mismos no aportan ningún significado: deben ser interpretados para convertirse en información. Los métodos tradicionales no tienen como objetivo "entender" el contenido de un recurso, sino que extraen valores numéricos que se convierten en modelos tras aplicar cálculos estadísticos, los cuales cobran sentido bajo el análisis manual de un experto. Actualmente, motivados por la Web Semántica, muchos investigadores han propuesto métodos semánticos de clasificación de datos capaces de explotar recursos textuales a nivel conceptual. Sin embargo, generalmente estos métodos dependen de recursos anotados previamente para poder interpretar semánticamente el contenido de un documento. El uso de estos métodos está estrechamente relacionado con la asociación de datos y su significado. Este trabajo se centra en el desarrollo de una metodología genérica capaz de detectar los rasgos más relevantes de un recurso textual descubriendo su asociación semántica, es decir, enlazándolos con conceptos modelados en una ontología, y detectando los principales temas de discusión. Los métodos propuestos son no supervisados para evitar el cuello de botella generado por la anotación manual, independientes del dominio (aplicables a cualquier área de conocimiento) y flexibles (capaces de analizar recursos heterogéneos: documentos textuales o documentos semi-estructurados, como artículos de la Wikipedia o publicaciones de Twitter). El trabajo ha sido evaluado en los ámbitos turístico y médico. Esta disertación es un primer paso hacia la anotación semántica automática de documentos necesaria para posibilitar el camino hacia la visión de la Web Semántica.Social Web technologies have caused an exponential growth of the documents available through the Web, making enormous amounts of textual electronic resources available. Users may be overwhelmed by such amount of contents and, therefore, the automatic analysis and exploitation of all this information is of interest to the data mining community. Data mining algorithms exploit features of the entities in order to characterise, group or classify them according to their resemblance. Data by itself does not carry any meaning; it needs to be interpreted to convey information. Classical data analysis methods did not aim to “understand” the content and the data were treated as meaningless numbers and statistics were calculated on them to build models that were interpreted manually by human domain experts. Nowadays, motivated by the Semantic Web, many researchers have proposed semantic-grounded data classification and clustering methods that are able to exploit textual data at a conceptual level. However, they usually rely on pre-annotated inputs to be able to semantically interpret textual data such as the content of Web pages. The usability of all these methods is related to the linkage between data and its meaning. This work focuses on the development of a general methodology able to detect the most relevant features of a particular textual resource finding out their semantics (associating them to concepts modelled in ontologies) and detecting its main topics. The proposed methods are unsupervised (avoiding the manual annotation bottleneck), domain-independent (applicable to any area of knowledge) and flexible (being able to deal with heterogeneous resources: raw text documents, semi-structured user-generated documents such Wikipedia articles or short and noisy tweets). The methods have been evaluated in different fields (Tourism, Oncology). This work is a first step towards the automatic semantic annotation of documents, needed to pave the way towards the Semantic Web vision

Conflicts, integration, hybridization of subcultures: An ecological approach to the case of queercore

This paper investigates the case study of queercore, providing a socio-historical analysis of its subcultural production, in the terms of what Michel Foucault has called archaeology of knowledge (1969). In particular, we will focus on: the self-definition of the movement; the conflicts between the two merged worlds of punk and queer culture; the \u201cinternal-subcultural\u201d conflicts between both queercore and punk, and between queercore and gay\lesbian music culture; the political aspects of differentiation. In the conclusion, we will offer an innovative theoretical proposal about the interpretation of subcultures in ecological and semiotic terms, combining the contribution of the American sociologist Andrew Abbot and of the Russian semiologist Jurij Michajlovi\u10d Lotma

Ontologiebasierte Indexierung und Kontextualisierung multimedialer Dokumente für das persönliche Wissensmanagement

Die Verwaltung persönlicher, multimedialer Dokumente kann mit Hilfe semantischer Technologien und Ontologien intelligent und effektiv unterstützt werden. Dies setzt jedoch Verfahren voraus, die den grundlegenden Annotations- und Bearbeitungsaufwand für den Anwender minimieren und dabei eine ausreichende Datenqualität und -konsistenz sicherstellen. Im Rahmen der Dissertation wurden notwendige Mechanismen zur semi-automatischen Modellierung und Wartung semantischer Dokumentenbeschreibungen spezifiziert. Diese bildeten die Grundlage für den Entwurf einer komponentenbasierten, anwendungsunabhängigen Architektur als Basis für die Entwicklung innovativer, semantikbasierter Lösungen zur persönlichen Dokumenten- und Wissensverwaltung.Personal multimedia document management benefits from Semantic Web technologies and the application of ontologies. However, an ontology-based document management system has to meet a number of challenges regarding flexibility, soundness, and controllability of the semantic data model. The first part of the dissertation proposes necessary mechanisms for the semi-automatic modeling and maintenance of semantic document descriptions. The second part introduces a component-based, application-independent architecture which forms the basis for the development of innovative, semantic-driven solutions for personal document and information management

Políticas de Copyright de Publicações Científicas em Repositórios Institucionais: O Caso do INESC TEC

A progressiva transformação das práticas científicas, impulsionada pelo desenvolvimento das novas Tecnologias de Informação e Comunicação (TIC), têm possibilitado aumentar o acesso à informação, caminhando gradualmente para uma abertura do ciclo de pesquisa. Isto permitirá resolver a longo prazo uma adversidade que se tem colocado aos investigadores, que passa pela existência de barreiras que limitam as condições de acesso, sejam estas geográficas ou financeiras. Apesar da produção científica ser dominada, maioritariamente, por grandes editoras comerciais, estando sujeita às regras por estas impostas, o Movimento do Acesso Aberto cuja primeira declaração pública, a Declaração de Budapeste (BOAI), é de 2002, vem propor alterações significativas que beneficiam os autores e os leitores. Este Movimento vem a ganhar importância em Portugal desde 2003, com a constituição do primeiro repositório institucional a nível nacional. Os repositórios institucionais surgiram como uma ferramenta de divulgação da produção científica de uma instituição, com o intuito de permitir abrir aos resultados da investigação, quer antes da publicação e do próprio processo de arbitragem (preprint), quer depois (postprint), e, consequentemente, aumentar a visibilidade do trabalho desenvolvido por um investigador e a respetiva instituição. O estudo apresentado, que passou por uma análise das políticas de copyright das publicações científicas mais relevantes do INESC TEC, permitiu não só perceber que as editoras adotam cada vez mais políticas que possibilitam o auto-arquivo das publicações em repositórios institucionais, como também que existe todo um trabalho de sensibilização a percorrer, não só para os investigadores, como para a instituição e toda a sociedade. A produção de um conjunto de recomendações, que passam pela implementação de uma política institucional que incentive o auto-arquivo das publicações desenvolvidas no âmbito institucional no repositório, serve como mote para uma maior valorização da produção científica do INESC TEC.The progressive transformation of scientific practices, driven by the development of new Information and Communication Technologies (ICT), which made it possible to increase access to information, gradually moving towards an opening of the research cycle. This opening makes it possible to resolve, in the long term, the adversity that has been placed on researchers, which involves the existence of barriers that limit access conditions, whether geographical or financial. Although large commercial publishers predominantly dominate scientific production and subject it to the rules imposed by them, the Open Access movement whose first public declaration, the Budapest Declaration (BOAI), was in 2002, proposes significant changes that benefit the authors and the readers. This Movement has gained importance in Portugal since 2003, with the constitution of the first institutional repository at the national level. Institutional repositories have emerged as a tool for disseminating the scientific production of an institution to open the results of the research, both before publication and the preprint process and postprint, increase the visibility of work done by an investigator and his or her institution. The present study, which underwent an analysis of the copyright policies of INESC TEC most relevant scientific publications, allowed not only to realize that publishers are increasingly adopting policies that make it possible to self-archive publications in institutional repositories, all the work of raising awareness, not only for researchers but also for the institution and the whole society. The production of a set of recommendations, which go through the implementation of an institutional policy that encourages the self-archiving of the publications developed in the institutional scope in the repository, serves as a motto for a greater appreciation of the scientific production of INESC TEC

Internet of Things and Sensors Networks in 5G Wireless Communications

This book is a printed edition of the Special Issue Internet of Things and Sensors Networks in 5G Wireless Communications that was published in Sensors

Internet of Things and Sensors Networks in 5G Wireless Communications

The Internet of Things (IoT) has attracted much attention from society, industry and academia as a promising technology that can enhance day to day activities, and the creation of new business models, products and services, and serve as a broad source of research topics and ideas. A future digital society is envisioned, composed of numerous wireless connected sensors and devices. Driven by huge demand, the massive IoT (mIoT) or massive machine type communication (mMTC) has been identified as one of the three main communication scenarios for 5G. In addition to connectivity, computing and storage and data management are also long-standing issues for low-cost devices and sensors. The book is a collection of outstanding technical research and industrial papers covering new research results, with a wide range of features within the 5G-and-beyond framework. It provides a range of discussions of the major research challenges and achievements within this topic

Internet of Things and Sensors Networks in 5G Wireless Communications

This book is a printed edition of the Special Issue Internet of Things and Sensors Networks in 5G Wireless Communications that was published in Sensors