Three web-based heuristics to determine a person's or institution's country of origin

Schedl, Markus; Seyerlehner, Klaus; Schnitzer, Dominik; Widmer, Gerhard; Schiketanz, Cornelia

doi:10.1145/1835449.1835623

Cited by 6 publications

(3 citation statements)

References 4 publications

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“…For instance, an artist's geographic and cultural context, political background, or song lyrics are likely strongly related to his or her origin. Work on this task has been performed by Govaerts and Duval [86] and by Schedl et al [240]. While the former mines these pieces of information from specific web sites, the latter distills the country of origin from web pages identified by a search engine.…”

Section: Artist's or Band's Country Of Originmentioning

confidence: 99%

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Music Information Retrieval: Recent Developments and Applications

Schedl¹,

Urbano²

2014

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We provide a survey of the field of Music Information Retrieval (MIR), in particular paying attention to latest developments, such as semantic auto-tagging and user-centric retrieval and recommendation approaches. We first elaborate on well-established and proven methods for feature extraction and music indexing, from both the audio signal and contextual data sources about music items, such as web pages or collaborative tags. These in turn enable a wide variety of music retrieval tasks, such as semantic music search or music identification ("query by example"). Subsequently, we review current work on user analysis and modeling in the context of music recommendation and retrieval, addressing the recent trend towards user-centric and adaptive approaches and systems. A discussion follows about the important aspect of how various MIR approaches to different problems are evaluated and compared. Eventually, a discussion about the major open challenges concludes the survey.

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Section: Artist's or Band's Country Of Originmentioning

confidence: 99%

“…Schedl et al [240] propose three approaches to country of origin detection. The first one is a heuristic which compares the page count estimates returned by Google for queries of the form "artist/band" "country" and simply predicts the country with highest page count value for a given artist or band.…”

Section: Artist's or Band's Country Of Originmentioning

confidence: 99%

Music Information Retrieval: Recent Developments and Applications

Schedl¹,

Urbano²

2014

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“…For example, the meaning of a song's lyrics [29,26], the political background of the musician, or the geographic origin of an artist [19,66,65] are likely to have a large impact on the music, but are not manifested in the signal. An overview of the state-of-the-art in music context-based feature extraction (and similarity estimation) can be found in [61].…”

Section: Music Contextmentioning

confidence: 99%

Personalization in Multimodal Music Retrieval

Schedl

Knees

2013

Adaptive Multimedia Retrieval. Large-Scale Multimedia Retrieval and Evaluation

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Abstract. This position paper provides an overview of current research endeavors and existing solutions in multimodal music retrieval, where the term "multimodal" relates to two aspects. The first one is taking into account the music context of a piece of music or an artist, while the second aspect tackled is that of the user context. The music context is introduced as all information important to the music, albeit not directly extractable from the audio signal (such as editorial or collaboratively assembled meta-data, lyrics in textual form, cultural background of an artists, or images of album covers). The user context, in contrast, is defined by various external factors that influence how a listener perceives music. It is therefore strongly related to user modeling and personalization, both facets of music information research that have not gained large attention by the MIR community so far. However, we are confident that adding personalization aspects to existing music retrieval systems (such as playlist generators, recommender systems, or visual browsers) is key to the future of MIR. In this vein, this contribution aims at defining the foundation for future research directions and applications related to multimodal music information systems.

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Fusing Web and Audio Predictors to Localize the Origin of Music Pieces for Geospatial Retrieval

Schedl

Zhou

2016

Lecture Notes in Computer Science

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Three web-based heuristics to determine a person's or institution's country of origin

Cited by 6 publications

References 4 publications

Music Information Retrieval: Recent Developments and Applications

Music Information Retrieval: Recent Developments and Applications

Personalization in Multimodal Music Retrieval

Fusing Web and Audio Predictors to Localize the Origin of Music Pieces for Geospatial Retrieval

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