Knowledge based Semantic Annotation Generation of Music

Sunitha Abburu
<span title="2012-06-30">2012</span> <i title="Foundation of Computer Science"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/b637noqf3vhmhjevdfk3h5pdsu" style="color: black;">International Journal of Computer Applications</a> </i> &nbsp;
The storage capacity and the cost of the storage devises gives raise to voluminous music collection management. Various MIR techniques exist, but getting the required songs from large collection of music files, is still a challenging problem. Getting the required songs from voluminous collection with good recall and precision depends on good annotation, indexing and retrieval techniques. Among this annotation plays a vital role in developing an efficient and effective retrieval system. Tag
more &raquo; ... annotation or the low level feature based annotations retrieval systems performance is very poor, though the processing is very simple. Semantic concept based annotation, indexing and retrieval techniques are trying to fill the gap between the machine understanding and the human preferences. This raises the need for semantic based annotation of film songs. Ontology plays a major role in semantic web and information retrieval. This raises the need for an ontology based annotation generation tool for film songs. The current research designs and implements a tool M-SAGT -Music Semantic Annotation Generation Tool. Which is flexible, user friendly and ontology based semantic annotations can be generated and stored in RDF/XML format. The generated semantic annotations can be used in semantic indexing and retrieval, which will enhance the performance of the retrieval system. General Terms Semantic Information Retrieval.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5120/7206-9990">doi:10.5120/7206-9990</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/l52l55iywrbwtnpvdnaoevcbxu">fatcat:l52l55iywrbwtnpvdnaoevcbxu</a> </span>
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