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There is a constantly growing interest in evaluating music information retrieval (MIR) systems that can provide effective management of the music resources. The crucial characteristic of music is its emotion, which reflect the human's perception. To do the automatic classification of Chinese music emotions more effective, we use the lyrics of music to analysis and classify music based on emotion....
Input Queued switches have been very well studied in the recent past. The Maximum Weight Matching (MWM) algorithm is known to deliver 100% throughput under any admissible traffic. However, MWM is not practical for its high computational complexity O(N3). In this paper, we study a class of approximations to MWM from the point of view of local search. Firstly, we propose a greedy scheduling...
Music structural analysis tasks have an important position in the field of Music information retrieval which require an understanding of how humans process music internally, such as music indexing, music summarization, and similarity analysis. Many schemes have been proposed to analyze the structure of recorded music, however they usually use single feature to detect boundaries of songs and the results...
Automatic extraction of popular music ringtones have become an important and useful area for communications and telecommunications industry. Quick and batch extraction of music ringtones increases the convenience in practical application. In this paper, we propose an automatic technology to extract the ringtones from popular music based on the musical structural analysis. This is a meaning attempt...
In this paper, a text similarity computation method named VSM-Cilin which is based on semantic vector space model is proposed in the background of radio station. VSM-Cilin improved the traditional VSM in the following areas. First, consider the semantic relations between words. Second, use semantic resources to reduce dimension. Third, use inverted index to filter out candidate document set. Forth,...
This paper has analyzed the property of the structure of MP3 file, and provided a parallel decoding method for the property. Thus, for CPU with multiple cores, this paper has provided a parallel decoding method based on multi-thread. The method can increase the utilization rate of CPU and decrease the decoding time while the load of each core of CPU is not balanced. At last, we have conducted three...
Histograms of Oriented Gradients (HOG) feature has been successfully used in pedestrian detection and achieves high accuracy. This paper introduces a content retrieval algorithm based on improved HOG. The method has two steps which are adjusting the HOG structure by scanning the image with a sliding HOG window and reducing feature dimension by principle component analysis (PCA) technique. The experimental...
Singing voice detection for musical structural analysis is an important but difficult area, which makes a great contribution to music segment. This paper proposes an efficient singing voice detection system by using beat tracking technique and SVM classification. We do the experiment using beat as a unit of classification instead of frame. Compared with a conventional frame-based classification, the...
With the popularity of parallel computing, the serial program is unable to take advantage of the multi-core. In this paper, A MP3 audio parallel decoding algorithm based on libmad library for multicore platform is proposed to improve the decoding speed. In this method, to reach the parallel aim, more than one decoder is provided. Experimental results indicate that the algorithm improves the efficiency...
with the development of electronic commerce, there is a growing emphasis on recommender systems. As one of the most mature recommend technology, the collaborative filtering method has been used in personalized recommender system. But the technology is based on rating, which doesn't take the user interest into account. This article gives the improved algorithm which based on ratings and user interest...
In the research of sentiment analysis, some supervised learning algorithms play an important role. Among them, Naïve Bayes is often used in engineering application due to its low computational and space complexity. While traditional Naïve Bayes algorithm has been shown to perform very well in domain-specific sentiment classification, it often performs badly in domain-transfer problem. So we propose...
With the development of World Wide Web technologies, more and more netizens express their opinions on society and politics in net news comments. Sentiment classification is one of the most important sub-problems of opinion mining, which can classify net news comments as positive or negative to help government automatically identify the netizens' viewpoints on news event and make right decision or...
With the development of network technology, all kinds of events will be shown up as news rapidly on the World Wide Web. Internet users read the news and some of them give their comments online. It is important for crisis public relations, government decision-making and news impact analysis to understanding the netizens' comments on the news events. Due to the huge amount of news and comments on Web,...
As scalable routers being a promising way to scale to higher capacity, scalable switch fabric as its key component has received a great deal of attention. However, the reliability calculation method for general switch fabric does not suit scalable switch fabrics with special features. In this paper, we study the features of scalable switch fabrics, and propose a novel reliability measure called Failure...
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