Finally, I finished my studies in May 2011. I’m now a degreed something (I would prefer the name Philosphical Engineer or Data Engineer or something like that 😉 ). Since I’m still struggling with formatting my thesis into HTML (LaTeX to HTML transformation doesn’t seem to an easy task when utilising quite customized macros 😦 – anyone woh can help me realizing this task is more than welcome).
So here we go with the PDF version of my thesis and the HTML-based presentation slides* of my defence talk.
Abstract:
Music is perceived and described very subjectively by every individual. Nowadays, people often get lost in their steadily growing, multi-placed, digital music collection. Existing music player and management applications get in trouble when dealing with poor metadata that is predominant in personal music collections. There are several music information services available that assist users by providing tools for precisely organising their music collection, or for presenting them new insights into their own music library and listening habits. However, it is still not the case that music consumers can seamlessly interact with all these auxiliary services directly from the place where they access their music individually.
To profit from the manifold music and music-related knowledge that is or can be available via various information services, this information has to be gathered up, semantically federated, and integrated into a uniform knowledge base that can personalised represent this data in an appropriate visualisation to the users. This personalised semantic aggregation of music metadata from several sources is the gist of this thesis. The outlined solution particularly concentrates on users’ needs regarding music collection management which can strongly alternate between single human beings.
The author’s proposal, the personal music knowledge base (PMKB), consists of a client-server architecture with uniform communication endpoints and an ontological knowledge representation model format that is able to represent the versatile information of its use cases. The PMKB concept is appropriate to cover the complete information flow life cycle, including the processes of user account initialisation, information service choice, individual information extraction, and proactive update notification.
The PMKB implementation makes use of SemanticWeb technologies. Particularly the knowledge representation part of the PMKB vision is explained in this work. Several new Semantic Web ontologies are defined or existing ones are massively modified to meet the requirements of a personalised semantic federation of music and music-related data for managing personal music collections. The outcome is, amongst others,
- a new vocabulary for describing the play back domain,
- another one for representing information service categorisations and quality ratings, and
- one that unites the beneficial parts of the existing advanced user modelling ontologies.
The introduced vocabularies can be perfectly utilised in conjunction with the existing Music Ontology framework. Some RDFizers that also make use of the outlined ontologies in their mapping definitions, illustrate the fitness in practise of these specifications.
A social evaluation method is applied to carry out an examination dealing with the reutilisation, application and feedback of the vocabularies that are explained in this work. This analysis shows that it is a good practise to properly publish Semantic Web ontologies with the help of some Linked Data principles and further basic SEO techniques to easily reach the searching audience, to avoid duplicates of such KR specifications, and, last but not least, to directly establish a “shared understanding”. Due to their project-independence, the proposed vocabularies can be deployed in every knowledge representation model that needs their knowledge representation capacities.
This thesis added its value to make the vision of a personal music knowledge base come true.
Have fun!
See also: http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-72434
*) best view with Firefox 4.x+, full-screen mode on, and Univers font family installed
PS: the HTML-based presentation slides are based on an extended version of the Slidy template
Some More Individual 
Very interesting. I kind of have the same dream.
But my most recent conclusions were that the best recommendation system in Music is human aggregation (like Musicplayr.com). Because Music is so personal, no algorithm can predict what one will enjoy or not. First because an algorithm can’t tell whether it is good quality music or pure commercial crap.
But I haven’t read your thesis yet.
And concerning the htmling of you thesis, I don’t think you should use automatic latex converter, but make it plain html as a whole.
Best
Hi Augustin,
thanks a lot for your comment. You are absolutely right, human recommendations are still by far more qualitative than the majority of algorithm based ones (see also ex.fm or thisismyjam.com). However, companies such as echonest are trying their best to compete with human recommendations.
Cheers
PS: re. the latex to html converting – I tried it several times with various tools in this area – without any success so far. building a html page manually would be very time intensive (especially, when trying to keep all the interlinking … 😉 )