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20 results on '"Hauger, David"'

1. Personality Correlates for Digital Concert Program Notes

Author

Tkalčič, Marko, Ferwerda, Bruce, Hauger, David, Schedl, Markus, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Ricci, Francesco, editor, Bontcheva, Kalina, editor, Conlan, Owen, editor, and Lawless, Séamus, editor

Published
2015
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2. On the Influence of User Characteristics on Music Recommendation Algorithms

Author

Schedl, Markus, Hauger, David, Farrahi, Katayoun, Tkalčič, Marko, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Kobsa, Alfred, Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Hanbury, Allan, editor, Kazai, Gabriella, editor, Rauber, Andreas, editor, and Fuhr, Norbert, editor

Published
2015
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3. From Improved Auto-Taggers to Improved Music Similarity Measures

Author

Seyerlehner, Klaus, Schedl, Markus, Sonnleitner, Reinhard, Hauger, David, Ionescu, Bogdan, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Nürnberger, Andreas, editor, Stober, Sebastian, editor, Larsen, Birger, editor, and Detyniecki, Marcin, editor

Published
2014
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4. Exploring Geospatial Music Listening Patterns in Microblog Data

Author

Hauger, David, Schedl, Markus, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Nürnberger, Andreas, editor, Stober, Sebastian, editor, Larsen, Birger, editor, and Detyniecki, Marcin, editor

Published
2014
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5. Using Browser Interaction Data to Determine Page Reading Behavior

Author

Hauger, David, Paramythis, Alexandros, Weibelzahl, Stephan, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Konstan, Joseph A., editor, Conejo, Ricardo, editor, Marzo, José L., editor, and Oliver, Nuria, editor

Published
2011
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10. Impact of Listening Behavior on Music Recommendation

Author

Farrahi, Katayoun, Schedl, Markus, Vall, Andreu, Hauger, David, and Tkalcic, Marko

Abstract

The next generation of music recommendation systems will be increasingly intelligent and likely take into account user behavior for more personalized recommendations. In this work we consider user behavior when making recommendations with features extracted from a user’s history of listening events. We investigate the impact of listener’s behavior by considering features such as play counts, “mainstreaminess”, and diversity in music taste on the performance of various music recommendation approaches. The underlying dataset has been collected by crawling social media (specifically Twitter) for listening events. Each user’s listening behavior is characterized into a three dimensional feature space consisting of play count, “mainstreaminess” (i.e. the degree to which the observed user listens to currently popular artists), and diversity (i.e. the diversity of genres the observed user listens to). Drawing subsets of the 28,000 users in our dataset, according to these three dimensions, we evaluate whether these dimensions influence figures of merit of various music recommendation approaches, in particular, collaborative filtering (CF) and CF enhanced by cultural information such as users located in the same city or country.

Published
2014
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15. Analyzing Client-side Interactions to Determine Reading Behaviour

Author

Hauger, David, van Velsen, Lex, Köck, Mirjam, and Nauerz, Andreas

Subjects
METIS-261511
Abstract

Traditional monitoring and user modeling techniques in adaptive hypermedia systems consider pages as atomic units although different sections may refer to different concepts. This has been mainly due to the fact that most user interactions being monitored referred to the request of a new document and there was too little activity information to differentiate between sections of a page. Client-side monitoring can provide additional information on user interactions inside the browser window and may relate them to areas within a document. A user study was carried out to show whether and how this data might be used to identify which parts of a page have been read.

Published
2009

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