In:
Electronic Research Archive, American Institute of Mathematical Sciences (AIMS), Vol. 3, No. 1 ( 2023), p. 44-78
Abstract:
〈abstract〉〈p〉Sequential Pattern Mining (SPM) is a branch of data mining that deals with finding statistically relevant regularities of patterns in sequentially ordered data. It has been an active area of research since mid 1990s. Even if many prime algorithms for SPM have a long history, the field is nevertheless very active. The literature is focused on novel challenges and applications, and on the development of more efficient and effective algorithms. In this paper, we present a brief overview on the landscape of algorithms for SPM, including an evaluation on performances for some of them. Further, we explore additional problems that have spanned from SPM. Finally, we evaluate available resources for SPM, and hypothesize on future directions for the field.〈/p〉〈/abstract〉
Type of Medium:
Online Resource
ISSN:
2688-1594
Language:
Unknown
Publisher:
American Institute of Mathematical Sciences (AIMS)
Publication Date:
2023
detail.hit.zdb_id:
3147960-1
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