In this paper, we present a complete set of procedures to automatically extract a music snippet, defined as the most representative or the highlighted excerpt of a music clip. We first generate a modified and compact ...In this paper, we present a complete set of procedures to automatically extract a music snippet, defined as the most representative or the highlighted excerpt of a music clip. We first generate a modified and compact similarity matrix based on selected features and distance metrics, and then several improved techniques for music repeated pattern discovery are utilized because a music snippet is usually a part of the repeated melody, main theme or chorus. During the process, redundant and wrongly detected patterns are discarded, boundaries are corrected using beat information, and final clusters are also further sorted according to the occurrence frequency and energy information. Subsequently, following our methods, we designed a music snippet extraction system which allows users to detect snippets. Experiments performed on the system show the superiority of our proposed approach.展开更多
Nowadays,with increasing open knowledge graphs(KGs)being published on the Web,users depend on open data portals and search engines to find KGs.However,existing systems provide search services and present results with ...Nowadays,with increasing open knowledge graphs(KGs)being published on the Web,users depend on open data portals and search engines to find KGs.However,existing systems provide search services and present results with only metadata while ignoring the contents of KGs,i.e.,triples.It brings difficulty for users’comprehension and relevance judgement.To overcome the limitation of metadata,in this paper we propose a content-based search engine for open KGs named CKGSE.Our system provides keyword search,KG snippet generation,KG profiling and browsing,all based on KGs’detailed,informative contents rather than their brief,limited metadata.To evaluate its usability,we implement a prototype with Chinese KGs crawled from Open KG.CN and report some preliminary results and findings.展开更多
基金Supported by the National Natural Science Foundation of China (Grant No. 60873098)
文摘In this paper, we present a complete set of procedures to automatically extract a music snippet, defined as the most representative or the highlighted excerpt of a music clip. We first generate a modified and compact similarity matrix based on selected features and distance metrics, and then several improved techniques for music repeated pattern discovery are utilized because a music snippet is usually a part of the repeated melody, main theme or chorus. During the process, redundant and wrongly detected patterns are discarded, boundaries are corrected using beat information, and final clusters are also further sorted according to the occurrence frequency and energy information. Subsequently, following our methods, we designed a music snippet extraction system which allows users to detect snippets. Experiments performed on the system show the superiority of our proposed approach.
基金supported by the Nantional Science Foundation of Chnia(No.62072224)
文摘Nowadays,with increasing open knowledge graphs(KGs)being published on the Web,users depend on open data portals and search engines to find KGs.However,existing systems provide search services and present results with only metadata while ignoring the contents of KGs,i.e.,triples.It brings difficulty for users’comprehension and relevance judgement.To overcome the limitation of metadata,in this paper we propose a content-based search engine for open KGs named CKGSE.Our system provides keyword search,KG snippet generation,KG profiling and browsing,all based on KGs’detailed,informative contents rather than their brief,limited metadata.To evaluate its usability,we implement a prototype with Chinese KGs crawled from Open KG.CN and report some preliminary results and findings.
