1,262 research outputs found

    Product Recommendations in E-Commerce Retailing Applications

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    The book deals with product recommendations generated by information systems referred to as recommender systems. Recommender systems assist consumers in making product choices by providing recommendations of the range of products and services offered in an online purchase environment. The quantitative research study investigates the influence of psychographic and sociodemographic determinants on the interest of consumers in personalized online book recommendations. The author presents new findings regarding the interest in recommendations, importance of product reviews for the decision process, motives for submitting ratings as well as comments, and the delivery of recommendations. The results show that opinion seeking, opinion leading, domain specific innovativeness, online shopping experience, and age are important factors in respect of the interest in personalized recommendations

    Music Streaming's Impact on Cultural Diversity : Spotify and Recommendation Algorithms as Gatekeepers

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    The rapid growth of music streaming business has brought significant changes to the music industry, creating new opportunities for artists, labels, and consumers alike. Streaming services, like Spotify, use algorithmic recommendation systems to help users find the content relevant to them from the seemingly endless trove of music. As modern gatekeepers, these services – and the algorithms they use – yield significant power over culture, affecting the rights of both artists and listeners. This thesis examines the music business in the digitalized era, the algorithmic recommendation of music, and its impact on cultural diversity, the right to express and access culture. Additionally, I will examine what kinds of methods the international society, UN at its helm, has proposed to protect cultural rights and diversity.Musiikin suoratoistopalveluiden nopea kasvu on muuttanut musiikkialaa merkittävästi, luoden uusia mahdollisuuksia niin artisteille, levy-yhtiöille kuin kuluttajillekin. Suoratoistoalustat, kuten Spotify, käyttävät suosittelualgoritmeja ja koneoppimista helpottaakseen käyttäjälle relevantin sisällön löytämistä musiikin loputtomasta tulvasta. Moderneina portinvartijoina suoratoistopalveluilla – ja näin myös niiden käyttämillä suosittelualgoritmeilla – on paljon kulttuurista valtaa. Opinnäytetyössäni tutkin, minkälaisia vaikutuksia suoratoistopalveluilla ja suosittelualgoritmeilla, voi olla ihmisoikeuksiin; kulttuuriseen monimuotoisuuteen, ilmaisunvapauteen ja pääsyyn kulttuurin äärelle. Lisäksi tutkin, minkälaisia toimia kansainvälinen yhteisö YK:n johdolla on ehdottanut kulttuuristen oikeuksien turvaamiseksi

    Providing lightweight telepresence in mobile communication to enhance collaborative living

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    Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2004.Includes bibliographical references (p. 117-124).Two decades of computer-supported cooperative work (CSCW) research has addressed how people work in groups and the role technology plays in the workplace. This body of work has resulted in a myriad of deployed technologies with underlying theories and evaluations. It is our hypothesis that similar technologies, and lessons learned from this domain, can also be employed outside the workplace to help people get on with life. The group in this environment is a special set of people with whom we have day-to-day relationships, people who are willing to share intimate personal information. Therefore we call this computer-supported collaborative living. This thesis describes a personal communicator in the form of a watch, intended to provide a link between family members or intimate friends, providing social awareness and helping them infer what is happening in another space and the remote person's availability for communication. The watch enables the wearers to be always connected via awareness cues, text and voice instant message, or synchronous voice connectivity. Sensors worn with the watch track location (via GPS), acceleration, and speech activity; these are classified and conveyed to the other party, where they appear in iconic form on the watch face, providing a lightweight form of telepresence. When a remote person with whom this information is shared examines it, their face appears on the watch of the person being checked on. A number of design criteria defined for collaborative living systems are illustrated through this device.by Natalia Marmasse.Ph.D

    CHORUS Deliverable 2.1: State of the Art on Multimedia Search Engines

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    Based on the information provided by European projects and national initiatives related to multimedia search as well as domains experts that participated in the CHORUS Think-thanks and workshops, this document reports on the state of the art related to multimedia content search from, a technical, and socio-economic perspective. The technical perspective includes an up to date view on content based indexing and retrieval technologies, multimedia search in the context of mobile devices and peer-to-peer networks, and an overview of current evaluation and benchmark inititiatives to measure the performance of multimedia search engines. From a socio-economic perspective we inventorize the impact and legal consequences of these technical advances and point out future directions of research

    MensSana: Design of a mental well-being self-report interface for shop floor workers

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    A ascensão da Indústria 4.0 trouxe consigo novas tecnologias e oportunidades que estão a mudar a natureza do trabalho, especialmente em ambientes de chão de fábrica. No entanto, essas mudanças também trouxeram novos desafios para os trabalhadores, incluindo desafios na sua saúde mental. Estes trabalhadores, em particular, enfrentam no seu trabalho estressores físicos e mentais que podem afetar seu bem-estar geral, apesar dos esforços da Indústria 4.0. O conceito de Operador 4.0 na Indústria 4.0 introduz muitos operadores, como o Operador Saudável, que enfatiza a centralidade no ser humano e visa melhorar a eficiência e o bem-estar do trabalhador por meio de tecnologias avançadas e análise de dados. Esta tese propõe o desenvolvimento de uma ferramenta protótipo, co-criada e validada no contexto da Indústria 4.0 para medir métricas do trabalhador e do local de trabalho, criando uma imagem holística do trabalhador, sua competência e bem-estar, alinhado ao conceito de um trabalhador "mais saudável" de Romero et al. Essas informações são devolvidas ao trabalhador e apresentadas de maneira legível e compreensível para identificar tendências e informar decisões futuras relacionadas ao trabalho e bem-estar.The rise of Industry 4.0 has brought about new technologies and opportunities that are changing the nature of work, particularly in factory floor settings. However, these changes have also brought about new challenges for workers, including mental health issues. Shop floor workers, in particular, face physical and mental stressors in their work that can impact their overall well-being, despite Industry 4.0 efforts. The Operator 4.0 concept in Industry 4.0 introduces a lot of operators like the Healthy Operator that emphasises human-centricity and aims to improve worker efficiency and well-being through advanced technologies and data analytics. This thesis proposes the development of a prototype tool co-created and validated in the context of Industry 4.0 to measure metrics from the worker and the workplace, creating a holistic picture of the worker, their competence and well-being in line with Romero's et al. concept of a "healthier" worker. This information is returned to the worker and presented in a readable and understandable manner to identify trends and inform future decisions concerning their work and well-being

    Semantic image retrieval using relevance feedback and transaction logs

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    Due to the recent improvements in digital photography and storage capacity, storing large amounts of images has been made possible, and efficient means to retrieve images matching a user’s query are needed. Content-based Image Retrieval (CBIR) systems automatically extract image contents based on image features, i.e. color, texture, and shape. Relevance feedback methods are applied to CBIR to integrate users’ perceptions and reduce the gap between high-level image semantics and low-level image features. The precision of a CBIR system in retrieving semantically rich (complex) images is improved in this dissertation work by making advancements in three areas of a CBIR system: input, process, and output. The input of the system includes a mechanism that provides the user with required tools to build and modify her query through feedbacks. Users behavioral in CBIR environments are studied, and a new feedback methodology is presented to efficiently capture users’ image perceptions. The process element includes image learning and retrieval algorithms. A Long-term image retrieval algorithm (LTL), which learns image semantics from prior search results available in the system’s transaction history, is developed using Factor Analysis. Another algorithm, a short-term learner (STL) that captures user’s image perceptions based on image features and user’s feedbacks in the on-going transaction, is developed based on Linear Discriminant Analysis. Then, a mechanism is introduced to integrate these two algorithms to one retrieval procedure. Finally, a retrieval strategy that includes learning and searching phases is defined for arranging images in the output of the system. The developed relevance feedback methodology proved to reduce the effect of human subjectivity in providing feedbacks for complex images. Retrieval algorithms were applied to images with different degrees of complexity. LTL is efficient in extracting the semantics of complex images that have a history in the system. STL is suitable for query and images that can be effectively represented by their image features. Therefore, the performance of the system in retrieving images with visual and conceptual complexities was improved when both algorithms were applied simultaneously. Finally, the strategy of retrieval phases demonstrated promising results when the query complexity increases
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