Domain Specific Key Feature Extraction Using Knowledge Graph Mining

• Autorzy: Mohit Kumar Barai , Subhasis Sanyal
• Języki publikacji: EN

Abstrakty

EN

In the field of text mining, many novel feature extraction approaches have been propounded. The following research paper is based on a novel feature extraction algorithm. In this paper, to formulate this approach, a weighted graph mining has been used to ensure the effectiveness of the feature extraction and computational efficiency; only the most effective graphs representing the maximum number of triangles based on a predefined relational criterion have been considered. The proposed novel technique is an amalgamation of the relation between words surrounding an aspect of the product and the lexicon-based connection among those words, which creates a relational triangle. A maximum number of a triangle covering an element has been accounted as a prime feature. The proposed algorithm performs more than three times better than TF-IDF within a limited set of data in analysis based on domain-specific data. (original abstract)

Słowa kluczowe

EN

Consumer Product Rating; Product features; Text mining; Natural languages; Graph theory

PL

Konsumencka ocena produktu; Cechy produktu; Eksploracja tekstu; Języki naturalne; Teoria grafów

• Czasopismo: Multiple Criteria Decision Making / University of Economics in Katowice
• Rocznik: 2020
• Tom: 15
• Strony: 1--22

Twórcy

autor

Mohit Kumar Barai

• Samsung Research Institute, Noida, India

autor

Subhasis Sanyal

• Samsung Research Institute, Noida, India

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Identyfikatory

DOI

10.22367/mcdm/2020.15.01