T3: On mapping Text To Time series

Tao Yang, Dongwon Lee

Research output: Contribution to journalConference article

2 Scopus citations

Abstract

We investigate if the mapping between text and time series data is feasible such that relevant data mining problems in text can find their counterparts in time series (and vice versa). As a preliminary work, we present the T 3 (Text To Time series) framework that utilizes different combinations of granularity (e.g., character or word level) and n-grams (e.g., unigram or bigram). To assign appropriate numeric values to each character, T3 adopts different space-filling curves (e.g., linear, Hilbert, Z orders) based on the keyboard layout. When we applied T3 approach to the "record linkage" problem, despite the lossy transformation, T 3 achieved comparable accuracy with considerable speed-up.

Original languageEnglish (US)
JournalCEUR Workshop Proceedings
Volume450
StatePublished - Dec 1 2009
Event3rd Alberto Mendelzon International Workshop on Foundations of Data Management, AMW 2009 - Arequipa, Peru
Duration: May 12 2009May 15 2009

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All Science Journal Classification (ASJC) codes

  • Computer Science(all)

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