The concept of sequential pattern mining for text

3rd Annual Applied Science and Engineering Conference

工业技术;自然科学

Maylawati, D.S.^1 ; Aulawi, H.^2 ; Ramdhani, M.A.^3

Departement of Informatics, Sekolah Tinggi Teknologi Garut, Jalan Mayor Syamsu No 1, Tarogong, Kidul Kabupaten Garut

44151, Indonesia^1

Industrial Engineering, Sekolah Tinggi Teknologi Garut, Jalan Mayor Syamsu No 1, Tarogong, Kidul Kabupaten Garut

44151, Indonesia^2

Departement of Informatics, UIN Sunan Gunung Djati Bandung, Jalan A H Nasution No 105, Bandung

40614, Indonesia^3

关键词: Concise representations;    Literature reviews;    Sequential pattern mining algorithm;    Sequential pattern mining problem;    Sequential patterns;    Sequential-pattern mining;    Structured data;    Unstructured data;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/434/1/012042/pdf
DOI  :  10.1088/1757-899X/434/1/012042

来源: IOP

【 摘 要 】

Sequential pattern mining is one of popular data mining technique with sequential pattern as representation of data. However, most of sequential pattern mining research was conducted for structured data. In this paper, we did literature review of the sequential pattern mining algorithm that suitable for unstructured data such as text data. We reviewed several sequential pattern mining algorithm that had already used in text mining research, among others GSP, Spade, PrefixSpan, Spam, Lapin, SM-Spam, CM-Spade, BIDE, and another various algorithm based on sequential pattern mining problem such as concise representation and how to extract more rich pattern. The result showed that that from year to year research on text data using sequential pattern mining had increased. Although, not many algorithm were developed and also still rarely new algorithms were implemented in text data.