From edit distance to augmented space-time-weighted edit distance: Detecting and clustering patterns of human activities in Puget Sound region

Zhai, Wei; Bai, Xueyin; Peng, Zhong-Ren; Gu, Chaolin

doi:10.1016/j.jtrangeo.2019.05.003

Cited by 13 publications

(6 citation statements)

References 44 publications

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“…However, for the similarity of two non-equal-length strings or arrays, they need to be calculated by edit distance, which is often called the Levenshtein distance [110]. It is defined as the minimum number of edits required for one of two strings to be converted to another [111]. The edit operation includes replacing a character with another character, inserting a character, or deleting a character.…”

Section: Levenshtein Distancementioning

confidence: 99%

Review of Clustering Technology and Its Application in Coordinating Vehicle Subsystems

et al. 2023

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Clustering is an unsupervised learning technology, and it groups information (observations or datasets) according to similarity measures. Developing clustering algorithms is a hot topic in recent years, and this area develops rapidly with the increasing complexity of data and the volume of datasets. In this paper, the concept of clustering is introduced, and the clustering technologies are analyzed from traditional and modern perspectives. First, this paper summarizes the principles, advantages, and disadvantages of 20 traditional clustering algorithms and 4 modern algorithms. Then, the core elements of clustering are presented, such as similarity measures and evaluation index. Considering that data processing is often applied in vehicle engineering, finally, some specific applications of clustering algorithms in vehicles are listed and the future development of clustering in the era of big data is highlighted. The purpose of this review is to make a comprehensive survey that helps readers learn various clustering algorithms and choose the appropriate methods to use, especially in vehicles.

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Section: Levenshtein Distancementioning

confidence: 99%

Review of Clustering Technology and Its Application in Coordinating Vehicle Subsystems

et al. 2023

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“…Furthermore, the EDR method was originally used to calculate the smallest number of operations (i.e., addition, deletion, and modification) required between two strings for complete consistency. This method has been widely used and was extended to similarity analyses of spatiotemporal trajectories [34][35][36][37][38]. However, similar to LCSS, this method cannot easily determine the distance threshold; LCSS and EDR only consider the similar or different components, respectively, such that the results of the similarity analysis are not ideal with uneven sampling point distributions or significant variations in the number of track points.…”

Section: Related Researchmentioning

confidence: 99%

Trajectory Similarity Analysis with the Weight of Direction and k-Neighborhood for AIS Data

Nie

Chen

Xia

et al. 2021

IJGI

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Automatic Identification System (AIS) data have been widely used in many fields, such as collision detection, navigation, and maritime traffic management. Similarity analysis is an important process for most AIS trajectory analysis topics. However, most traditional AIS trajectory similarity analysis methods calculate the distance between trajectory points, which requires complex and time-consuming calculations, often leading to substantial errors when processing AIS trajectory data characterized by substantial differences in length or uneven trajectory points. Therefore, we propose a cell-based similarity analysis method that combines the weight of the direction and k-neighborhood (WDN-SIM). This method quantifies the similarity between trajectories based on the degree of proximity and differences in motion direction. In terms of its effectiveness and efficiency, WDN-SIM outperformed seven traditional methods for trajectory similarity analysis. Particularly, WDN-SIM has a high robustness to noise and can distinguish the similarities between trajectories under complex situations, such as when there are opposing directions of motion, large differences in length, and uneven point distributions.

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“…Others also applied string or sequence clustering algorithms. For instance, Wang et al (2018) [28] and Zhai et al (2019) [29] measured categorical sequence distance with an edit distance which is the essential number of substitutions, insertions and deletions when converting a string into a target one. However, the edit distance did not consider the characteristics of each change operation.…”

Section: Activity Pattern Clustering Techniquesmentioning

confidence: 99%

Transport for the Elderly: Activity Patterns, Mode Choices, and Spatiotemporal Constraints

2020

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The rapid aging of the population has posed significant challenges to society and raised new demand for transportation services. Understanding travel needs of the elderly is crucial to making effective strategies for accommodating their demand in many newly motorized cities in developing countries such as China. Using a Markov-chain-based mixture model, we identify two main activity patterns of the elderly: recreation-shopping-oriented (RS-oriented) pattern and schooling-drop-off/pick-up-oriented (SDP-oriented) pattern. Elderly people in the RS-oriented pattern enjoy a cozy life with much time spent on recreation and shopping activities, while those in the SDP-oriented pattern take responsibility of sending grandchildren to school and taking them back home. The RS-oriented elderly people are faced with spatial constraints to access the sparsely distributed recreational sights; however, the SDP-oriented group is subject to temporal constraints when making daily trips. These results would encourage policy makers to reconsider the role of transportation in aged people’s lives and better accommodate their demand through designing safer walking and cycling environment and improving the quality of transit services.

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From edit distance to augmented space-time-weighted edit distance: Detecting and clustering patterns of human activities in Puget Sound region

Cited by 13 publications

References 44 publications

Review of Clustering Technology and Its Application in Coordinating Vehicle Subsystems

Review of Clustering Technology and Its Application in Coordinating Vehicle Subsystems

Trajectory Similarity Analysis with the Weight of Direction and k-Neighborhood for AIS Data

Transport for the Elderly: Activity Patterns, Mode Choices, and Spatiotemporal Constraints

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