Evidence map›Paper›PMID 36017242›Full record

ArticleJournal of environmental and public health2022

Analysis of Music Retrieval Based on Emotional Tags Environment.

Nuan Bao

RetractedAbstract readRetracted Publication
In one paragraph

Article in Journal of environmental and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Retracted: Analysis of Music Retrieval Based on Emotional Tags Environment.Journal of environmental and public health · 2023
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

1 author.

Nuan BaoInstitute of Music, Theater and Choreography, The Herzen State Pedagogical University, Saint Petersburg 191186, Russia.ORCID 0000-0002-2419-4239

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In general, tags are used to interpret the content of music, while the music itself expresses emotion. The emotional information conveyed by the same music is described by a large number of emotion tags in various ways. This paper proposes and establishes an algorithm for music retrieval based on emotional tags. By modelling user emotional tags and music, a bipartite graph with emotional tags and music as nodes is first created. The tags and semantic similarity between the music are then calculated using the T_SimRank algorithm, and the popularity of the music is calculated using the T_PageRank algorithm. Finally, the two methods are combined using the concept of ranking learning to produce the final ranking of the music. Experiments demonstrate that the method suggested in this paper can better satisfy user retrieval needs than conventional cosine similarity and tag co-occurrence-based similarity methods and that the fusion of multiple methods is preferable to a single method.

Indexed as

MusicEmotions

Identifiers

PMID36017242
PMCPMC9398802

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.