Keyword extraction: Issues and methods

Firoozeh, Nazanin; Nazarenko, Adeline; Alizon, Fabrice; Daille, Béatrice

doi:10.1017/s1351324919000457

Cited by 117 publications

(74 citation statements)

References 67 publications

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“…Particularly after the development of mature computer networks, multimedia resources other than text have been freely disseminated. As one of the important types of art in human life, music is naturally a necessary need for people [2]. With the open sharing nature of digital music on the Internet, its dissemination has reached the ultimate.…”

Section: Introductionmentioning

confidence: 99%

[Retracted] Matching Subsequence Music Retrieval in a Software Integration Environment

Qin

2021

Complexity

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This paper firstly introduces the basic knowledge of music, proposes the detailed design of a music retrieval system based on the knowledge of music, and analyzes the feature extraction algorithm and matching algorithm by using the features of music. Feature extraction of audio data is the important research of this paper. In this paper, the main melody features, MFCC features, GFCC features, and rhythm features, are extracted from audio data and a feature fusion algorithm is proposed to achieve the fusion of GFCC features and rhythm features to form new features under the processing of principal component analysis (PCA) dimensionality reduction. After learning the main melody features, MFCC features, GFCC features, and rhythm features, based on the property that PCA dimensionality reduction can effectively reduce noise and improve retrieval efficiency, this paper proposes vector fusion by dimensionality reduction of GFCC features and rhythm features. The matching retrieval of audio features is an important task in music retrieval. In this paper, the DTW algorithm is chosen as the main algorithm for retrieving music. The classification retrieval of music is also achieved by the K-nearest neighbor algorithm. In this paper, after implementing the research and improvement of algorithms, these algorithms are integrated into the system to achieve audio preprocessing, feature extraction, feature postprocessing, and matching retrieval. This article uses 100 different kinds of MP3 format music as the music library and randomly selects 4 pieces each time, and it tests the system under different system parameters, recording duration, and environmental noise. Through the research of this paper, the efficiency of music retrieval is improved and theoretical support is provided for the design of music retrieval software integration system.

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Section: Introductionmentioning

confidence: 99%

[Retracted] Matching Subsequence Music Retrieval in a Software Integration Environment

Qin

2021

Complexity

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“…Therefore, it is a partially automated and systematic method (Boyack and Klavans 2010). Finally, in line with Firoozeh et al (2020), an automated keyword extraction is deployed to round out the systematic literature search and review. This shows the common keywords found throughout the abstracts and titles of the corpus, and how they connect and relate with one another, which ideally will help to guide future research.…”

Section: Methodological Approachmentioning

confidence: 99%

Green growth and innovation in the Global South: a systematic literature review

Herman

2021

Innovation and Development

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There has been much interest in green growth and innovation in recent years. The main idea is that domestic green growth policies can provide 'win-wins' to both the environment and the economy. But we still know very little about the impact of such policies, especially in developing countries-the 'Global South.' The literature remains underdeveloped. This is disappointing since the Global South could leverage green growth policies to enhance competitiveness, 'leapfrog' directly to cleaner technologies, and 'catch-up' economically and environmentally through innovation in environmental technologies. The lack of research is also problematic because greenhouse gas emissions from developing countries are growing rapidly. Without green growth and innovation it will be exceedingly difficult to meet the urgent needs of climate change. Against this backdrop, this paper conducts machine-aided citation, bibliometric, and keyword analyses on green growth research with a particular focus on developing countries, innovation, and environmental technologies.

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“…With the exponential growth in the amount of available textual resources, organization, categorization, and summarization of these data presents a challenge, the extent of which becomes even more apparent when it is taken into account that a majority of these resources do not contain any adequate meta information. Manual categorization and tagging of documents is unfeasible due to a large amount of data, therefore, development of algorithms capable of tackling these tasks automatically and efficiently has become a necessity (Firoozeh et al 2020).…”

Section: Introductionmentioning

confidence: 99%

TNT-KID: Transformer-based neural tagger for keyword identification

2021

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With growing amounts of available textual data, development of algorithms capable of automatic analysis, categorization, and summarization of these data has become a necessity. In this research, we present a novel algorithm for keyword identification, that is, an extraction of one or multiword phrases representing key aspects of a given document, called Transformer-Based Neural Tagger for Keyword IDentification (TNT-KID). By adapting the transformer architecture for a specific task at hand and leveraging language model pretraining on a domain-specific corpus, the model is capable of overcoming deficiencies of both supervised and unsupervised state-of-the-art approaches to keyword extraction by offering competitive and robust performance on a variety of different datasets while requiring only a fraction of manually labeled data required by the best-performing systems. This study also offers thorough error analysis with valuable insights into the inner workings of the model and an ablation study measuring the influence of specific components of the keyword identification workflow on the overall performance.

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Keyword extraction: Issues and methods

Cited by 117 publications

References 67 publications

[Retracted] Matching Subsequence Music Retrieval in a Software Integration Environment

[Retracted] Matching Subsequence Music Retrieval in a Software Integration Environment

Green growth and innovation in the Global South: a systematic literature review

TNT-KID: Transformer-based neural tagger for keyword identification

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