11,827 research outputs found

    Ten years of MIREX: reflections, challenges and opportunities

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    The Music Information Retrieval Evaluation eXchange (MIREX) has been run annually since 2005, with the October 2014 plenary marking its tenth iteration. By 2013, MIREX has evaluated approximately 2000 individual music information retrieval (MIR) algorithms for a wide range of tasks over 37 different test collections. MIREX has involved researchers from over 29 different contrives with a median of 109 individual participants per year. This pater summarizes the history of MIREX form its earliest planning meeting in 2001 to the present. It reflects upon the administrative, financial, and technological challenges MIREX has faced and describes how those challenges have been surmounted. We propose new funding models, a distributed evaluation framework, and more holistic user experience evaluation tasks-some evolutionary, some revolutionary-for the continued success of MIREX. We hope that this paper will inspire MIR community members to contribute their ideas so MIREX can have many more successful years to come

    Collaborative recommendations with content-based filters for cultural activities via a scalable event distribution platform

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    Nowadays, most people have limited leisure time and the offer of (cultural) activities to spend this time is enormous. Consequently, picking the most appropriate events becomes increasingly difficult for end-users. This complexity of choice reinforces the necessity of filtering systems that assist users in finding and selecting relevant events. Whereas traditional filtering tools enable e.g. the use of keyword-based or filtered searches, innovative recommender systems draw on user ratings, preferences, and metadata describing the events. Existing collaborative recommendation techniques, developed for suggesting web-shop products or audio-visual content, have difficulties with sparse rating data and can not cope at all with event-specific restrictions like availability, time, and location. Moreover, aggregating, enriching, and distributing these events are additional requisites for an optimal communication channel. In this paper, we propose a highly-scalable event recommendation platform which considers event-specific characteristics. Personal suggestions are generated by an advanced collaborative filtering algorithm, which is more robust on sparse data by extending user profiles with presumable future consumptions. The events, which are described using an RDF/OWL representation of the EventsML-G2 standard, are categorized and enriched via smart indexing and open linked data sets. This metadata model enables additional content-based filters, which consider event-specific characteristics, on the recommendation list. The integration of these different functionalities is realized by a scalable and extendable bus architecture. Finally, focus group conversations were organized with external experts, cultural mediators, and potential end-users to evaluate the event distribution platform and investigate the possible added value of recommendations for cultural participation

    Auditing Personal Information Management

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    This paper firstly introduces personal information management using computers. It then describes a suggested approach to auditing the information needs which are personal to a knowledge worker. As part of an overall research programme in personal information management, the paper describes a personal auditing approach which is positioned as part of the experimental research aspect of the overall research. The paper aims to give practical guidance including on the effective classification of an individual’s data

    Information Outlook, May 2005

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    Volume 9, Issue 5https://scholarworks.sjsu.edu/sla_io_2005/1004/thumbnail.jp

    Information Outlook, May 1997

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    Volume 1, Issue 5https://scholarworks.sjsu.edu/sla_io_1997/1004/thumbnail.jp

    Web and Electronic Publishing Trends

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    Information Outlook, April 2001

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    Volume 5, Issue 4https://scholarworks.sjsu.edu/sla_io_2001/1003/thumbnail.jp
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