A Position-Sensitive Sequence-Alignment Method Illustrated for Space–Time Activity-Diary Data

Sequence-alignment methods which have been recently introduced in time-use research analyse the cross-sectional as well as the sequential information embedded in space–time activity-diary data. As these methods have been developed to trace the evolutionary history of random mutations of the elements in biological sequences, they are not appropriate to measure the distances by which activities change their sequential order in activity diaries. In this paper we report on the development of a position-sensitive sequence-alignment method for activity analysis. First, the problem is specified, and the key concepts to analyse the problem are addressed. Then, the principles of the new method are introduced. The method is illustrated with data on activity patterns collected in the Netherlands. The paper concludes with a critical discussion of the basic assumptions of the method and avenues of future research are identified.

[1]  M. A. McClure,et al.  Comparative analysis of multiple protein-sequence alignment methods. , 1994, Molecular biology and evolution.

[2]  W C Wilson,et al.  Activity Pattern Analysis by Means of Sequence-Alignment Methods , 1998 .

[3]  Ryuichi Kitamura,et al.  Incorporating trip chaining into analysis of destination choice , 1984 .

[4]  Pat Burnett,et al.  THE ANALYSIS OF TRAVEL AS AN EXAMPLE OF COMPLEX HUMAN BEHAVIOR IN SPATIALLY-CONSTRAINED SITUATIONS: DEFINITION AND MEASUREMENT ISSUES , 1982 .

[5]  Michael S. Waterman,et al.  Introduction to computational biology , 1995 .

[6]  S Gregory Hatcher,et al.  DAILY VARIABILITY OF ROUTE AND TRIP SCHEDULING DECISIONS FOR THE EVENING COMMUTE , 1992 .

[7]  Roger K. Moore,et al.  Dynamic Programming and Statistical Modelling in Automatic Speech Recognition , 1986 .

[8]  Dan Gusfield,et al.  Algorithms on Strings, Trees, and Sequences: The Importance of (Sub)sequence Comparison in Molecular Biology , 1997 .

[9]  M. McNally,et al.  Travel/activity analysis: Pattern recognition, classification and interpretation , 1985 .

[10]  T. Arentze,et al.  A model of multi-purpose shopping trip behavior , 1993 .

[11]  Hjp Harry Timmermans,et al.  A Stated Choice Model of Sequential Mode and Destination Choice Behaviour for Shopping Trips , 1996 .

[12]  Susan R. Wilson.  INTRODUCTION TO COMPUTATIONAL BIOLOGY: MAPS, SEQUENCES AND GENOMES. , 1996 .

[13]  Ta Theo Arentze,et al.  Pattern Recognition in Complex Activity Travel Patterns: Comparison of Euclidean Distance, Signal-Processing Theoretical, and Multidimensional Sequence Alignment Methods , 2001 .

[14]  J. Thompson,et al.  CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. , 1994, Nucleic acids research.

[15]  Ryuichi Kitamura,et al.  The sequenced activity mobility simulator (SAMS): an integrated approach to modeling transportation, land use and air quality , 1996 .

[16]  J. Gower.  A General Coefficient of Similarity and Some of Its Properties , 1971 .

[17]  Eric I. Pas,et al.  Travel-Activity Behavior in Time and Space: Methods for Representation and Analysis , 1985 .