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A labeling and music technology, applied in the field of crawler-based music labeling methods and systems, to achieve the effects of improving usability, improving utilization, and improving usability
Active Publication Date: 2016-06-29
SOUTH CHINA UNIV OF TECH
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Problems solved by technology
However, in music labeling, there is no comprehensive, efficient and high-quality technical solution for labeling music library
Method used
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Embodiment 1
[0062] See Figure 1 to Figure 4 , figure 1 It is a flowchart of the crawler-based music labeling method and each corresponding step disclosed in the first embodiment. Such as Figure 1 to Figure 4 As shown, the method includes the following steps:
[0063] S1. Preprocess the crawler music tag records from different music websites;
[0064] S2. Convert playlist tags into song tags;
[0065] The step of converting the playlist tag in step S2 is specifically:
[0066] S21. For each sub-category tag, count its frequency of appearance in all playlist tag records;
[0067] S22. For each song, count the subcategory tags it contains and the corresponding frequency;
[0068] S23. For each song, calculate the credible value of each playlist tag;
[0069] S24. Filter out the playlist tags with higher credibility of the song;
[0070] S25: Judge whether there are other songs, if it is, execute step S23, otherwise end.
[0071] S3. Fuzzy matching the crawler music tag record and the music library m...
Embodiment 2
[0109] Corresponding to the above method, there is a crawler-based music labeling system, and the system includes:
[0110] The data preprocessing module is used to preprocess the crawler music tag records from different music websites to make them have a unified format; including removing the irrelevant characters, unifying the connectors of multiple singers into plus signs, etc.
[0111] The tag conversion module is used to calculate the credible value of the playlist tags to convert the playlist tags into song tags. Specifically: converting the playlist label of a song into the song label, and the label conversion module is used for calculating the frequency of appearance of each of the small category labels in all the playlist label records, In addition, for a song, count the sub-category tags it contains and the frequency corresponding to the tag, calculate the credibility value of each playlist tag contained in the song, and filter out the credible value of the song based on ...
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Abstract
The invention provides a crawler-based music labelling method and a crawler-based music labelling system. According to the method and the system, the availability of music label records is improved by pre-processing the music label records on the basis of crawling the music label records of a plurality of music websites by a crawler; meanwhile, a uniform format of the music label records from different music websites is guaranteed; moreover, song menu labels are converted into song labels by calculating credit values of the song menu labels; fuzzy matching is performed on the song names in the music label records crawled by the crawler and the song names in an unlabeled song bank by utilizing an edit distance algorithm, and a corresponding relation is established, so that the utilization rate of the crawler music label records is improved; more music labels are labelled on the song bank to the maximal extent on the premise of guaranteeing label accuracy; meanwhile, a set of complete music label system is established according to the music labels of the music websites, and labels are fused on the basis of the labels of the music label system.
Description
Technical field [0001] The invention belongs to the technical field of data acquisition and credibility calculation, and more specifically relates to a crawler-based method and system for putting music labels. Background technique [0002] With the continuous expansion of the digital music market, the characterization of digital music has become a hot spot of research at this stage, and the music label is the most important characterization. Music tags have rich semantics, but the premise of this labeling method is that there is an active music community with a large number of users with high stickiness; on the other hand, music tags are random and discrete, which is easy to form a "cold start" (ColdStart), the lack of tags for newly launched music will be difficult for users to retrieve, leading to "popularity bias" (Popularity Bias), affected by the first labeling of users, and later users’ choices will follow previous popular trends, which makes most Users have only listened ...
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