2010 | |||||
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Sebastian Stober & Andreas Nürnberger. Visualisierung von großen Musiksammlungen unter Berücksichtigung projektionsbedingter Verzerrungen. In: 36. Jahrestagung für Akustik DAGA 2010, Berlin, German Acoustical Society (DEGA), Berlin, Mar 2010. (in German) |
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| Abstract: Viele Ansätze zur Visualisierung einer Musiksammlung basieren auf Techniken, bei denen Objekte (Musikstücke, Alben oder Künstler) aus einem hochdimensionalen Merkmalsraum für die Darstellung in den 2- oder 3-dimensionalen Raum projiziert werden. Dabei kommt es zwangsläufig zu Verzerrungen der Abstände. Als Folge kann es vorkommen, dass benachbarte Objekte sich gar nicht so sehr ähneln, wie es die Darstellung vermuten lässt, oder weit von einander entfernte Objekte sehr ähnlich sind. In diesem Beitrag wird eine interaktive Visualisierung vorgestellt, die eine globale Sicht auf eine Musiksammlung ermöglicht und mit adaptiven Filterfunktionen und multifokalem Zoom die beschriebenen Verzerrungsprobleme gezielt adressiert. | |||||
BibTeX:
@inproceedings{daga2010stober,
author = {Sebastian Stober and Andreas N\"{u}rnberger},
title = {Visualisierung von gro\{ss}en Musiksammlungen unter Ber\"{u}cksichtigung projektionsbedingter Verzerrungen},
booktitle = {36. Jahrestagung f\"{u}r Akustik DAGA 2010, Berlin},
address = {Berlin},
month = {Mar},
publisher = {German Acoustical Society (DEGA)},
year = {2010},
note = {in German}
}
|
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2009 | |||||
|
Proceedings of the 3rd Workshop on Learning the Semantics of Audio Signals (LSAS). Stephan Baumann; Juan José Burred; Andreas Nürnberger & Sebastian Stober (eds.) Graz, Austria, Dec 2009. (ISBN 978-3-940961-38-9) |
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BibTeX:
@proceedings{lsas2009,,
title = {{Proceedings of the 3rd Workshop on Learning the Semantics of Audio Signals (LSAS)}},
editor = {Stephan Baumann and Juan Jos\'{e} Burred and Andreas N\"{u}rnberger and Sebastian Stober},
address = {Graz, Austria},
month = {Dec},
year = {2009},
isbn = {978-3-940961-38-9},
url = {http://lsas2009.dke-research.de/proceedings/lsas2009proceedings.pdf}
}
|
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|
Sebastian Stober; Matthias Steinbrecher & Andreas Nürnberger. A Survey on the Acceptance of Listening Context Logging for MIR Applications. In Stephan Baumann; Juan José Burred; Andreas Nürnberger & Sebastian Stober (eds.): Proceedings of the 3rd Workshop on Learning the Semantics of Audio Signals (LSAS), Pages 45-57, Graz, Austria, Dec 2009. |
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| Abstract: In order to enrich music information retrieval applications with information about a user's listening habits, it is possible to automatically record a large variety of information about the listening context. However, recording such information may violate the user's privacy. This paper presents and discusses the results of a survey that has been conducted to assess the acceptance of listening context logging. | |||||
BibTeX:
@inproceedings{lsas2009stoberSteinbrecherNuernberger,
author = {Sebastian Stober and Matthias Steinbrecher and Andreas N\"{u}rnberger},
title = {A Survey on the Acceptance of Listening Context Logging for MIR Applications},
editor = {Stephan Baumann and Juan Jos\'{e} Burred and Andreas N\"{u}rnberger and Sebastian Stober},
booktitle = {Proceedings of the 3rd Workshop on Learning the Semantics of Audio Signals (LSAS)},
address = {Graz, Austria},
month = {Dec},
year = {2009},
pages = {45--57},
url = {http://lsas2009.dke-research.de/proceedings/lsas2009stoberSteinbrecherNuernberger.pdf}
}
|
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|
Korinna Bade; Jörg Garbers; Sebastian Stober; Frans Wiering & Andreas Nürnberger. Supporting Folk-Song Research by Automatic Metric Learning and Ranking. In: Proceedings of the 10th International Conference on Music Information Retrieval, ISMIR, Pages 741-746, Kobe, Japan, Oct 2009. |
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| Abstract: In folk song research, appropriate similarity measures can be of great help, e.g. for classification of new tunes. Several measures have been developed so far. However, a particular musicological way of classifying songs is usually not directly reflected by just a single one of these measures. We show how a weighted linear combination of different basic similarity measures can be automatically adapted to a specific retrieval task by learning this metric based on a special type of constraints. Further, we describe how these constraints are derived from information provided by experts. In experiments on a folk song database, we show that the proposed approach outperforms the underlying basic similarity measures and study the effect of different levels of adaptation on the performance of the retrieval system. | |||||
BibTeX:
@inproceedings{ismir09stober,
author = {Korinna Bade and J\"{o}rg Garbers and Sebastian Stober and Frans Wiering and Andreas N\"{u}rnberger},
title = {Supporting Folk-Song Research by Automatic Metric Learning and Ranking},
booktitle = {Proceedings of the 10th International Conference on Music Information Retrieval, ISMIR},
address = {Kobe, Japan},
month = {Oct},
year = {2009},
pages = {741--746},
url = {http://ismir2009.ismir.net//proceedings/OS9-3.pdf}
}
|
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|
Korinna Bade; Andreas Nürnberger & Sebastian Stober. Everything in its right place? Learning a user's view of a music collection. In: Proceedings of NAG/DAGA 2009, International Conference on Acoustics, Rotterdam, Pages 344-347, German Acoustical Society (DEGA), Berlin, 2009. |
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| Abstract: Keeping one's personal music collections well organized can be a very tedious task. Fortunately, today, many popular music players (such as AmaroK or iTunes) have an integrated library function that can automatically rename and tag music files and sort them into subdirectories. However, their common approach to stick with some hierarchy of genre, artist name, and album title barely represents the way a user would structure his collection manually. When it comes to organizing a music collection according to a user-specific hierarchy, three things are required: First, the music files have to be described by appropriate features beyond simple meta-tags. This includes content-based analysis but also incorporation of external information sources such as the web. Second, knowledge about the user's structuring preferences must be available. And third, and most importantly, methods for learning personalized hierarchies that can integrate this knowledge are needed. We propose for this task a hierarchical constraint based clustering approach that can weight the importance of different features according to the user perceived similarity. A hierarchy based on this similarity measure reflects a user's view on the collection. | |||||
BibTeX:
@inproceedings{daga09stober,
author = {Korinna Bade and Andreas N\"{u}rnberger and Sebastian Stober},
title = {Everything in its right place? Learning a user's view of a music collection},
booktitle = {Proceedings of NAG/DAGA 2009, International Conference on Acoustics, Rotterdam},
address = {Berlin},
publisher = {German Acoustical Society (DEGA)},
year = {2009},
pages = {344--347}
}
|
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|
Sebastian Stober & Andreas Nürnberger. User-Adaptive Music Information Retrieval. In: KI Volume 23, Number 2, Pages 54-57, 2009. |
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| Abstract: Automatic structuring is one means to ease access to large music collections -- be it for organisation or exploration. The AUCOMA project (Adaptive User-Centered Organization of Music Archives) aims to find ways to make such a structuring intuitively understandable to a user through automatic adaptation.This article describes the motivation of the project, discusses related work in the field of music information retrieval and presents first project results. | |||||
BibTeX:
@article{ki09stober,
author = {Sebastian Stober and Andreas N\"{u}rnberger},
title = {User-Adaptive Music Information Retrieval},
journal = {KI},
year = {2009},
volume = {23},
number = {2},
pages = {54-57},
url = {http://www.kuenstliche-intelligenz.de/index.php?id=7778&tx_ki_pi1[showUid]=1800&cHash=5143a324cc}
}
|
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2008 | |||||
|
Sebastian Stober & Andreas Nürnberger. Towards User-Adaptive Structuring and Organization of Music Collections. In: Adaptive Multimedial Retrieval: 6th International Workshop, AMR 2008, Berlin, Germany, June 26-27, 2008. (to appear in LNCS) |
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| Abstract: We present a prototype system for organization and exploration of music archives that adapts to the user's way of structuring music collections. Initially, a growing self-organizing map is induced that clusters the music collection. The user has then the possibility to change the location of songs on the map by simple drag-and-drop actions. Each movement of a song causes a change in the underlying similarity measure based on a quadratic optimization scheme. As a result, the location of other songs is modified as well. Experiments simulating user interaction with the system show, that in this stepwise adaption the similarity measure indeed converges to one that captures how the user compares songs. This utimately leads to an individually adapted presentation that is intuitively understandable to the user and thus eases access to the database. | |||||
BibTeX:
@inproceedings{amr08stober,
author = {Sebastian Stober and Andreas N\"{u}rnberger},
title = {Towards User-Adaptive Structuring and Organization of Music Collections},
booktitle = {Adaptive Multimedial Retrieval: 6th International Workshop, AMR 2008, Berlin, Germany, June 26-27},
year = {2008},
note = {to appear in LNCS}
}
|
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|
Valentin Laube; Christian Moewes & Sebastian Stober. Browsing Music by Usage Context. In Juan J. Burred; Andreas Nürnberger; Geoffroy Peeters & Sebastian Stober (eds.): Proceedings of the 2nd Workshop on Learning the Semantics of Audio Signals (LSAS), Pages 19-29, IRCAM, Paris, June 2008. |
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| Abstract: This paper aims to motivate and demonstrate how widely available environmental data can be exploited to allow organization, structuring and exploration of music collections by personal listening contexts. We describe a logging plug-in for music players that automatically records data about the listening context and discuss possible extensions for more sophisticated context logging. Based on data collected in a small user experiment, we show how data mining techniques can be applied to reveal common usage patterns. Further, a prototype user interface based on elastic lists for browsing by listening context is presented. | |||||
BibTeX:
@inproceedings{lsas08stober,
author = {Valentin Laube and Christian Moewes and Sebastian Stober},
title = {Browsing Music by Usage Context},
editor = {Juan J. Burred and Andreas N\"{u}rnberger and Geoffroy Peeters and Sebastian Stober},
booktitle = {Proceedings of the 2nd Workshop on Learning the Semantics of Audio Signals (LSAS)},
address = {Paris},
month = {June},
publisher = {IRCAM},
year = {2008},
pages = {19--29},
url = {http://lsas2008.dke-research.de/proceedings/lsas2008_p19-29_LaubeMoewesStober.pdf}
}
|
|||||
|
Proceedings of the 2nd Workshop on Learning the Semantics of Audio Signals (LSAS). Juan J. Burred; Andreas Nürnberger; Geoffroy Peeters & Sebastian Stober (eds.) IRCAM, Paris, June 2008. (ISBN 978-3-9804874-7-4) |
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BibTeX:
@proceedings{lsas2008,,
title = {{Proceedings of the 2nd Workshop on Learning the Semantics of Audio Signals (LSAS)}},
editor = {Juan J. Burred and Andreas N\"{u}rnberger and Geoffroy Peeters and Sebastian Stober},
address = {Paris},
month = {June},
publisher = {IRCAM},
year = {2008},
isbn = {978-3-9804874-7-4},
url = {http://lsas2008.dke-research.de/proceedings/lsas2008_proceedings.pdf}
}
|
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|
Johannes Reinhard; Sebastian Stober & Andreas Nürnberger. Enhancing Chord Classification through Neighbourhood Histograms. In: Proceedings of the 6th International Workshop on Content-Based Multimedia Indexing (CBMI 2008), 2008. |
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| Abstract: The chord progression of a song is an important high-level feature which enables indexing as well as deeper analysis of musical recordings. Different approaches to chord recognition have been suggested in the past. Though their performance increased, still significant error rates seem to be unavoidable. One way to improve accuracy is to try to correct possible misclassifications. In this paper, we propose a post-processing method based on considerations of musical harmony, assuming that the pool of chords used in a song is limited and that strong oscillations of chords are uncommon. We show that exploiting (uncertain) knowledge about the chord-distribution in a chord's neighbourhood can significantly improve chord detection accuracy by evaluating our proposed post-processing method for three baseline classifiers on two early Beatles albums. | |||||
BibTeX:
@inproceedings{cbmi08stober,
author = {Johannes Reinhard and Sebastian Stober and Andreas N\"{u}rnberger},
title = {Enhancing Chord Classification through Neighbourhood Histograms},
booktitle = {Proceedings of the 6th International Workshop on Content-Based Multimedia Indexing (CBMI 2008)},
year = {2008},
url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4564924},
doi = {10.1109/CBMI.2008.4564924}
}
|
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|
Sebastian Stober & Andreas Nürnberger. AUCOMA - Adaptive Nutzerzentrierte Organisation von Musikarchiven. In Ute Jekosch & Rüdiger Hoffmann (eds.): Fortschritte der Akustik: Plenarvorträge und Fachbeiträge der 34. Deutschen Jahrestagung für Akustik DAGA 2008, Dresden, Pages 547-548, German Acoustical Society (DEGA), Berlin, Mar 2008. (in German) |
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| Abstract: Automatische Strukturierung kann den Zugriff auf Musikarchive, speziell die Exploration und Organisation, wesentlich erleichtern. Noch hilfreicher wäre eine Darstellung, die sich an die Art und Weise, wie der Nutzer Musiksammlungen strukturiert, anpasst und somit für ihn intuitiv nachvollziehbar ist. Wir stellen hier ein prototypisches System vor, welches ein personalisiertes Ähnlichkeitsmaß anhand der Nutzerinteraktion mit einer Musiksammlung lernt. Zunächst wird dazu eine wachsende Selbstorganisierende Karte (SOM) trainiert, die nutzerunabhängig ähnliche Musikstücke gruppiert. Der Nutzer kann anschließend die Position von Musikstücken in der Karte durch einfache Drag&Drop-Aktionen verändern. Jede Bewegung verursacht eine automatische Anpassung des der Karte zugrunde liegenden Ähnlichkeitsmaßes, wodurch auch andere Stücke ihre Position ändern können. | |||||
BibTeX:
@inproceedings{daga08stober,
author = {Sebastian Stober and Andreas N\"{u}rnberger},
title = {{AUCOMA - Adaptive Nutzerzentrierte Organisation von Musikarchiven}},
editor = {Ute Jekosch and R\"{u}diger Hoffmann},
booktitle = {Fortschritte der Akustik: Plenarvortr\"{a}ge und Fachbeitr\"{a}ge der 34. Deutschen Jahrestagung f\"{u}r Akustik DAGA 2008, Dresden},
address = {Berlin},
month = {Mar},
publisher = {German Acoustical Society (DEGA)},
year = {2008},
pages = {547--548},
note = {in German}
}
|
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|
Christian Hentschel; Sebastian Stober; Andreas Nürnberger & Marcin Detyniecki. Automatic Image Annotation Using a Visual Dictionary Based on Reliable Image Segmentation. In Marcin Detyniecki & Andreas Nürnberger (eds.): Adaptive Multimedial Retrieval: Retrieval, User, and Semantics. 5th International Workshop, AMR 2007, Paris, France, July 5-6, 2007, Revised Selected Papers, LNCS, Volume 4918, Pages 45-56, Springer Verlag, Heidelberg / Berlin, 2008. |
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| Abstract: Recent approaches in Automatic Image Annotation (AIA) try to combine the expressiveness of natural language queries with approaches to minimize the manual effort for image annotation. The main idea is to infer the annotations of unseen images using a smallset of manually annotated training examples. However, typically these approaches suffer from low correlation between the globallyassigned annotations and the local features used to obtain annotations automatically. In this paper we propose a frameworkto support image annotations based on a visual dictionary that is created automatically using a set of locally annotated trainingimages. We designed a segmentation and annotation interface to allow for easy annotation of the traing data. In order to providea framework that is easily extendable and reusable we make broad use of the MPEG-7 standard. | |||||
BibTeX:
@inproceedings{amr07hentschel,
author = {Christian Hentschel and Sebastian Stober and Andreas N\"{u}rnberger and Marcin Detyniecki},
title = {Automatic Image Annotation Using a Visual Dictionary Based on Reliable Image Segmentation},
editor = {Marcin Detyniecki and Andreas N\"{u}rnberger},
booktitle = {Adaptive Multimedial Retrieval: Retrieval, User, and Semantics. 5th International Workshop, AMR 2007, Paris, France, July 5-6, 2007, Revised Selected Papers},
address = {Heidelberg / Berlin},
publisher = {Springer Verlag},
year = {2008},
series = {LNCS},
volume = {4918},
pages = {45--56},
url = {http://dx.doi.org/10.1007/978-3-540-79860-6_4},
doi = {10.1007/978-3-540-79860-6_4}
}
|
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|
Sebastian Stober & Andreas Nürnberger. User Modelling for Interactive User-Adaptive Collection Structuring. In Marcin Detyniecki & Andreas Nürnberger (eds.): Adaptive Multimedial Retrieval: Retrieval, User, and Semantics. 5th International Workshop, AMR 2007, Paris, France, July 5-6, 2007, Revised Selected Papers, LNCS, Volume 4918, Pages 95-108, Springer Verlag, Heidelberg / Berlin, 2008. |
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| Abstract: Automatic structuring is one means to ease access to document collections, be it for organization or for exploration. Of even greater help would be a presentation that adapts to the user's way of structuring and thus is intuitively understandable. We extend an existing user-adaptive prototype system that is based on a growing self-organizing map and that learns a feature weighting scheme from a user's interaction with the system resulting in a personalized similarity measure. The proposed approach for adapting the feature weights targets certain problems of previously used heuristics. The revised adaptation method is based on quadratic optimization and thus we are able to pose certain contraints on the derived weighting scheme. Moreover, thus it is guaranteed that an optimal weighting scheme is found if one exists. The proposed approach is evaluated by simulating user interaction with the system on two text datasets: one artificial data set that is used to analyze the performance for different user types and a real world data set - a subset of the banksearch dataset - containing additional class information. | |||||
BibTeX:
@inproceedings{amr07stober,
author = {Sebastian Stober and Andreas N\"{u}rnberger},
title = {User Modelling for Interactive User-Adaptive Collection Structuring},
editor = {Marcin Detyniecki and Andreas N\"{u}rnberger},
booktitle = {Adaptive Multimedial Retrieval: Retrieval, User, and Semantics. 5th International Workshop, AMR 2007, Paris, France, July 5-6, 2007, Revised Selected Papers},
address = {Heidelberg / Berlin},
publisher = {Springer Verlag},
year = {2008},
series = {LNCS},
volume = {4918},
pages = {95-108},
url = {http://dx.doi.org/10.1007/978-3-540-79860-6_8},
doi = {10.1007/978-3-540-79860-6_8}
}
|
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2007 | |||||
|
Alexander Duda; Andreas Nürnberger & Sebastian Stober. Towards Query by Singing/Humming on Audio Databases. In Simon Dixon; David Bainbridge & Rainer Typke (eds.): Proceedings of the 8th International Conference on Music Information Retrieval, ISMIR 2007, Pages 331-334, ÖCG, Vienna, Austria, September 2007. |
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| Abstract: Current work on Query-by-Singing/Humming (QBSH) focusses mainly on databases that contain MIDI files. Here, we present an approach that works on real audio recordings that bring up additional challenges. To tackle the problem of extracting the melody of the lead vocals from recordings, we introduce a method inspired by the popular “karaoke effect” exploiting information about the spatial arrangement of voices and instruments in the stereo mix. The extracted signal time series are aggregated into symbolic strings preserving the local approximated values of a feature and revealing higher-level context patterns. This allows distance measures for string pattern matching to be applied in the matching process. A series of experiments are conducted to assess the discrimination and robustness of this representation. They show that the proposed approach provides a viable baseline for further development and point out several possibilities for improvement. | |||||
BibTeX:
@inproceedings{ismir07qbsh,
author = {Alexander Duda and Andreas N\"{u}rnberger and Sebastian Stober},
title = {Towards Query by Singing/Humming on Audio Databases},
editor = {Simon Dixon and David Bainbridge and Rainer Typke},
booktitle = {Proceedings of the 8th International Conference on Music Information Retrieval, ISMIR 2007},
address = {Vienna, Austria},
month = {September},
publisher = {\"{O}CG},
year = {2007},
pages = {331-334},
url = {http://ismir2007.ismir.net/proceedings/ISMIR2007_p331_duda.pdf}
}
|
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|
Christian Hentschel; Andreas Nürnberger; Ingo Schmitt & Sebastian Stober. SAFIRE: Towards Standardized Semantic Rich Image Annotation. In Marcin Detyniecki; Andreas Nürnberger; Eric Bruno & Stephane Marchand-Maillet (eds.): Adaptive Multimedia Retrieval: User, Context, and Feedback. 4th International Workshop, AMR 2006, Geneva, Switzerland, July, 27-28, 2006, Revised Selected Papers, LNCS, Volume 4398, Pages 12-27, Springer Verlag, Berlin / Heidelberg, 2007. |
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| Abstract: Most of the currently existing image retrieval systems make use of either low-level features or semantic (textual) annotations. A combined usage during annotation and retrieval is rarely attempted. In this paper, we propose a standardized annotation framework that integrates semantic and feature based information about the content of images. The presented approach is based on the MPEG-7 standard with some minor extensions. The proposed annotation system SAFIRE (Semantic Annotation Framework for Image REtrieval) enables the combined use of low-level features and annotations that can be assigned to arbitrary hierarchically organized image segments. Besides the framework itself, we discuss query formalisms required for this unified retrieval approach. | |||||
BibTeX:
@inproceedings{amr06safire,
author = {Christian Hentschel and Andreas N\"{u}rnberger and Ingo Schmitt and Sebastian Stober},
title = {{SAFIRE: Towards Standardized Semantic Rich Image Annotation}},
editor = {Marcin Detyniecki and Andreas N\"{u}rnberger and Eric Bruno and Stephane Marchand-Maillet},
booktitle = {Adaptive Multimedia Retrieval: User, Context, and Feedback. 4th International Workshop, AMR 2006, Geneva, Switzerland, July, 27-28, 2006, Revised Selected Papers},
address = {Berlin / Heidelberg},
publisher = {Springer Verlag},
year = {2007},
series = {LNCS},
volume = {4398},
pages = {12--27},
url = {http://dx.doi.org/10.1007/978-3-540-71545-0_2},
doi = {10.1007/978-3-540-71545-0_2}
}
|
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2006 | |||||
|
Proceedings of the 1st Workshop on Learning the Semantics of Audio Signals (LSAS). Pedro Cano; Andreas Nürnberger; Sebastian Stober & George Tzanetakis (eds.) Athens, Greece, Dec 2006. |
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BibTeX:
@proceedings{lsas2006,,
title = {{Proceedings of the 1st Workshop on Learning the Semantics of Audio Signals (LSAS)}},
editor = {Pedro Cano and Andreas N\"{u}rnberger and Sebastian Stober and George Tzanetakis},
address = {Athens, Greece},
month = {Dec},
year = {2006},
url = {http://irgroup.cs.uni-magdeburg.de/lsas2006/proceedings/LSAS06_Full.pdf}
}
|
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|
Sebastian Stober & Andreas Nürnberger. DAWN -- A System for Context-Based Link Recommendation in Web Navigation. In Bogdan Gabrys; Robert J. Howlett & Lakhmi C. Jain (eds.): Knowledge-Based Intelligent Information and Engineering Systems, LNAI, Volume 4251, Pages 763-770, Springer Verlag, Berlin / Heidelberg, Oct 2006. (ISBN 3-540-46535-9) |
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| Abstract: We have developed the system DAWN (direction anticipation in web navigation) that learns navigational patterns to help users navigating through the world wide web. In this paper, we present the prediction model and the algorithm for link recommendation of this system. Besides this main focus, we briefly outline the system architecture and further motivate the purpose of such a system and the approach taken. A first evaluation on real-world data gave promising results. | |||||
BibTeX:
@inproceedings{stober06dawn,
author = {Sebastian Stober and Andreas N\"{u}rnberger},
title = {{DAWN -- A System for Context-Based Link Recommendation in Web Navigation}},
editor = {Bogdan Gabrys and Robert J. Howlett and Lakhmi C. Jain},
booktitle = {Knowledge-Based Intelligent Information and Engineering Systems},
address = {Berlin / Heidelberg},
month = {Oct},
publisher = {Springer Verlag},
year = {2006},
series = {LNAI},
volume = {4251},
pages = {763--770},
isbn = {3-540-46535-9},
url = {http://dx.doi.org/10.1007/11892960},
doi = {10.1007/11892960}
}
|
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|
Sebastian Stober & Andreas Nürnberger. Context-Based Navigational Support in Hypermedia. In Barry Smyth; Helen Ashman & Vincent Wade (eds.): Proceedings of the International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems (AH 2006), LNCS, Volume 4018, Pages 328 - 332, Springer Verlag, Berlin / Heidelberg, Jun 2006. |
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| Abstract: In this paper, we present the system DAWN (direction anticipation in web navigation) that helps users to navigate through the world wide web. Firstly, the purpose of such a system and the approach taken are motivated. We then point out relations to other approaches, describe the system and outline the underlying prediction model. Evaluation on real world data gave promising results. | |||||
BibTeX:
@inproceedings{stober06contextBased,
author = {Sebastian Stober and Andreas N\"{u}rnberger},
title = {{Context-Based Navigational Support in Hypermedia}},
editor = {Barry Smyth and Helen Ashman and Vincent Wade},
booktitle = {Proceedings of the International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems (AH 2006)},
address = {Berlin / Heidelberg},
month = {Jun},
publisher = {Springer Verlag},
year = {2006},
series = {LNCS},
volume = {4018},
pages = {328 -- 332},
url = {http://dx.doi.org/10.1007/11768012_43},
doi = {10.1007/11768012_43}
}
|
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|
Korinna Bade; Ernesto William De Luca; Andreas Nürnberger & Sebastian Stober. CARSA - An Architecture for the Development of Context Adaptive Retrieval Systems. In Keith van Rijsbergen; Andreas Nürnberger; Joemon M. Jose & Marcin Detyniecki (eds.): Adaptive Multimedia Retrieval: User, Context, and Feedback. 3rd International Workshop, AMR 2005, Glasgow, UK, July 28-29, 2005, Revised Selected Papers, LNCS, Volume 3877, Pages 91 - 101, Springer Verlag, Berlin / Heidelberg, Feb 2006. |
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| Abstract: Searching the Web and other local resources has become an every day task for almost everybody. However, the currently available tools for searching still provide only very limited support with respect to categorization and visualization of search results as well as personalization. In this paper, we present a system for searching that can be used by an end user and also by researchers in order to develop and evaluate a variety of methods to support a user in searching. The CARSA system provides a very flexible architecture based on web services and XML. This includes the use of different search engines, categorization methods, visualization techniques, and user interfaces. The user has complete control about the features used. This system therefore provides a platform for evaluating the usefulness of different retrieval support methods and their combination. | |||||
BibTeX:
@inproceedings{amr05carsa,
author = {Korinna Bade and Ernesto William {De Luca} and Andreas N\"{u}rnberger and Sebastian Stober},
title = {{CARSA - An Architecture for the Development of Context Adaptive Retrieval Systems}},
editor = {Keith van Rijsbergen and Andreas N\"{u}rnberger and Joemon M. Jose and Marcin Detyniecki},
booktitle = {Adaptive Multimedia Retrieval: User, Context, and Feedback. 3rd International Workshop, AMR 2005, Glasgow, UK, July 28-29, 2005, Revised Selected Papers},
address = {Berlin / Heidelberg},
month = {Feb},
publisher = {Springer Verlag},
year = {2006},
series = {LNCS},
volume = {3877},
pages = {91 -- 101},
url = {http://dx.doi.org/10.1007/11670834_8},
doi = {10.1007/11670834_8}
}
|
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2005 | |||||
|
Sebastian Stober. Kontextbasierte Navigationsunterstützung mit Markov-Modellen. Otto-von-Guericke University Magdeburg, Germany, Dec 2005. (in German) |
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| Abstract: Im stetig wachsenden und sich verändernden Datenmeer des World Wide Web sind Nutzer bei der Navigation von Webseite zu Webseite weitestgehend auf sich allein gestellt. In dieser Arbeit wird ein Ansatz vorgestellt, mit Hilfe dessen vorhergesagt werden kann, ob ein Link von einem Benutzer wahrscheinlich weiterverfolgt werden wird. Diese Vorhersagen ermöglichen es, bestimmte Links besonders hervorzuheben, wodurch ein Benutzer bei der Navigation unterstützt werden kann. Das implementierte Verfahren ist clientseitig einsetzbar und damit in seiner Anwendung nicht auf bestimmte Bereiche des World Wide Web beschränkt. Zur Vorhersage wird ein Markov Modell höherer Ordnung aus aufgezeichneten Browsingpfaden gelernt. Ein Browsingpfad wird dabei in eine Folge von Kontexten zerlegt, wobei jeder Kontext als Dokumentenvektor mit TF/iDF-Gewichten repräsentiert wird und beispielsweise dem Text einer Webseite oder eines Absatzes entspricht. Die Menge der Kontexte wird geclustert, wodurch Browsingpfade zu Navigationsmustern abstrahiert werden und sich die Größe des daraus gelernten Modells reduziert. Zum Lernen des Modells wurde ein von Borges und Levene für den serverseitigen Einsatz entwickelter Algorithmus erweitert und auf die clientseitige Anwendung übertragen. Die Vorhersage von Links erfolgt schließlich durch ein speziell entwickeltes Verfahren, das für einen Browsingpfad die gleichzeitige Betrachtung mehrerer ähnlicher Navigationsmuster im Modell erlaubt. Das gesamte Verfahren ist parametrisiert. Der Einfluß der verschiedenen Parameter und die Qualität der Vorhersagen konnten jedoch nur auf einer kleinen Datensammlung untersucht werden, wodurch nur ein grundlegender Eindruck von der Funktionsweise des Systems vermittelt werden kann. Das System ist in ein Framework zur clientseitigen Aufzeichnung und Analyse von Benutzeraktionen beim Browsen eingebettet, welches ebenfalls im Kontext dieser Arbeit entwickelt wurde. Dieses Framework ist ein eigenständiges und erweiterbares System, welches auch für andere Arbeiten verwendet und nach den jeweiligen Anforderungen leicht erweitert werden kann. |
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BibTeX:
@mastersthesis{stober05diploma,
author = {Sebastian Stober},
title = {Kontextbasierte Navigationsunterst\"{u}tzung mit Markov-Modellen},
address = {Magdeburg, Germany},
month = {Dec},
school = {Otto-von-Guericke University},
year = {2005},
note = {in German}
}
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Sebastian Stober. Design and Implementation of an Algorithm and Data Structure for Matching of Geometric Primitives in Visual Object Classification. Otto-von-Guericke University Magdeburg, Germany, Apr 2005. |
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| Abstract: This report refers to work completed during my internship with the Mechatronics Research Group at the department of Mechanical and Manufacturing Engineering at the University of Melbourne, Australia from September 5th, 2003 until March 5th, 2004. Recognition of three-dimensional objects in two-dimensional images is a key area of research in computer vision. One approach is to save multiple 2D views instead of a 3D object representation thus reducing the problem to a 2D to 2D matching problem. The Mechatronics Research Group is developing a novel system that focuses on artificial objects and further reduces the 2D views to symbolic descriptions. These descriptions are based on shape-primitives: ellipses, rectangles and isosceles triangles. Evidence insupport of a hypothesis for a certain object classification is collected through an active vision approach. This work deals with the design and implementation of a data structure that is capable of holding such a symbolic representation and an algorithm for comparison and matching. The chosen symbolic representation of an object view is rotation-, scaling- and translation-invariant. For the comparison and matching of two object views a branch & bound algorithm based on problem specific heuristics is used. Furthermore, a GA-based generalization operator is proposed to reduce the number of object views in the system database. Experiments show that the query performance scales linearly with the size of the database. For a database containing 10000 entries, a response time of less than a second is expected on an average system. |
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BibTeX:
@mastersthesis{stober05internship,
author = {Sebastian Stober},
title = {Design and Implementation of an Algorithm and Data Structure for Matching of Geometric Primitives in Visual Object Classification},
address = {Magdeburg, Germany},
month = {Apr},
school = {Otto-von-Guericke University},
year = {2005}
}
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