Adaptive text mining: inferring structure from sequences
type: Item
instance of: scholarly article
title: Adaptive text mining: inferring structure from sequences
zbMATH Open document ID: 1118.68668
DOI: 10.1016/S1570-8667(03)00084-4
published in: Journal of Discrete Algorithms
publication date: 2007-04-26T00:00:00Z
Mathematics Subject Classification ID: 68T30
Mathematics Subject Classification ID: 68T05
zbMATH DE Number: 5147091
zbMATH Keywords: text mining
zbMATH Keywords: phrase hierarchies
zbMATH Keywords: keyphrase extraction
zbMATH Keywords: generic entity extraction
zbMATH Keywords: text categorization
zbMATH Keywords: word segmentation
zbMATH Keywords: acronym extraction
zbMATH Keywords: compression algorithms
zbMATH Keywords: adaptive techniques
Wikidata QID: Q59820996
author: Ian H. Witten
MaRDI profile type: Publication
cites work: Bagging predictors
cites work: Algorithms on Strings, Trees and Sequences
cites work: Q4386970
cites work: Error bounds for convolutional codes and an asymptotically optimum decoding algorithm
cites work: Q4833659
cites work: A universal algorithm for sequential data compression
cites work: Compression of individual sequences via variable-rate coding
DBLP publication ID: journals/jda/Witten04
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description: scientific article; zbMATH DE number 5147091