Qiaoliang Xiang

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Social tagging can provide rich semantic information for large-scale retrieval in music discovery. Such collaborative intelligence, however, also generates a high degree of tags unhelpful to discovery, some of which obfuscate critical information. Towards addressing these shortcomings, tag recommendation for more robust music discovery is an emerging topic(More)
With the continuing advances in data storage and communication technology, there has been an explosive growth of music information from different application domains. As an effective technique for organizing, browsing, and searching large data collections, music information retrieval is attracting more and more attention. How to measure and model the(More)
A music retrieval system is introduced that incorporate tempo, cultural, and beat strength features to help music therapists provide appropriate music for gait training for Parkinson's patients. Unlike current methods available to music therapists (e.g., personal CD/MP3 library search) we propose a domain-specific search engine that utilizes database of(More)
How to measure and model the similarity between different music items is one of the most fundamental yet challenging research problems in music information retrieval. This paper demonstrates a novel multimodal and adaptive music similarity measure (CompositeMap) with its application in a personalized multimodal music search system. CompositeMap can(More)
The combination of heterogeneous knowledge sources has been widely regarded as an effective approach to boost retrieval accuracy in many information retrieval domains. While various technologies have been recently developed for information retrieval, multimodal music search has not kept pace with the enormous growth of data on the Internet. In this paper,(More)
Music classification based on cultural style is useful for music analysis and has potential applications in retrieval and recommendation systems. In this paper, we present the first attempt to classify audio signals automatically according to their cultural styles, which are characterized by timbre, rhythm, wavelet coefficients and musicology-based(More)
We propose an adaptive ensemble method to adapt coreference resolution across domains. This method has three features: (1) it can optimize for any user-specified objective measure ; (2) it can make document-specific prediction rather than rely on a fixed base model or a fixed set of base models; (3) it can automatically adjust the active ensemble members(More)
Clustering evaluation measures are frequently used to evaluate the performance of algorithms. However, most measures are not properly normalized and ignore some information in the inherent structure of clusterings. We model the relation between two clusterings as a bipartite graph and propose a general component-based decomposition formula based on the(More)
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