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Documents authored by Hong, Ye

Found 2 Possible Name Variants:

Hong, Ye

Document
Short Paper
DOI: 10.4230/LIPIcs.GIScience.2023.84
Predicting visit frequencies to new places (Short Paper)

Authors: Nina Wiedemann, Ye Hong, and Martin Raubal

Published in: LIPIcs, Volume 277, 12th International Conference on Geographic Information Science (GIScience 2023)

Abstract
Human mobility exhibits power-law distributed visitation patterns; i.e., a few locations are visited frequently and many locations only once. Current research focuses on the important locations of users or on recommending new places based on collective behaviour, neglecting the existence of scarcely visited locations. However, assessing whether a user will return to a location in the future is highly relevant for personalized location-based services. Therefore, we propose a new problem formulation aimed at predicting the future visit frequency to a new location, focusing on the previous mobility behaviour of a single user. Our preliminary results demonstrate that visit frequency prediction is a difficult task, but sophisticated learning models can detect insightful patterns in the historic mobility indicative of future visit frequency. We believe these models can uncover valuable insights into the spatial factors that drive individual mobility behaviour.
Cite as

Nina Wiedemann, Ye Hong, and Martin Raubal. Predicting visit frequencies to new places (Short Paper). In 12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 84:1-84:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{wiedemann_et_al:LIPIcs.GIScience.2023.84,
  author =	{Wiedemann, Nina and Hong, Ye and Raubal, Martin},
  title =	{{Predicting visit frequencies to new places}},
  booktitle =	{12th International Conference on Geographic Information Science (GIScience 2023)},
  pages =	{84:1--84:6},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-288-4},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{277},
  editor =	{Beecham, Roger and Long, Jed A. and Smith, Dianna and Zhao, Qunshan and Wise, Sarah},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2023.84},
  URN =		{urn:nbn:de:0030-drops-189794},
  doi =		{10.4230/LIPIcs.GIScience.2023.84},
  annote =	{Keywords: Human mobility, Visitation patterns, Place recommendation, Next location prediction}
}
Document
DOI: 10.4230/LIPIcs.GIScience.2021.II.4
A Clustering-Based Framework for Individual Travel Behaviour Change Detection

Authors: Ye Hong, Yanan Xin, Henry Martin, Dominik Bucher, and Martin Raubal

Published in: LIPIcs, Volume 208, 11th International Conference on Geographic Information Science (GIScience 2021) - Part II

Abstract
The emergence of passively and continuously recorded movement data offers new opportunities to study the long-term change of individual travel behaviour from data-driven perspectives. This study proposes a clustering-based framework to identify travel behaviour patterns and detect potential change periods on the individual level. First, we extract important trips that depict individual characteristic movement. Then, considering trip mode, trip distance, and trip duration as travel behaviour dimensions, we measure the similarities of trips and group them into clusters using hierarchical clustering. The trip clusters represent dimensions of travel behaviours, and the change of their relative proportions over time reflect the development of travel preferences. We use two different methods to detect changes in travel behaviour patterns: the Herfindahl-Hirschman index-based method and the sliding window-based method. The framework is tested using data from a large-scale longitudinal GPS tracking data study in which participants had access to a Mobility-as-a-Service (MaaS) offer. The methods successfully identify significant travel behaviour changes for users. Moreover, we analyse the impact of the MaaS offer on individual travel behaviours with the obtained change information. The proposed framework for behaviour change detection provides valuable insights for travel demand management and evaluating people’s reactions to sustainable mobility options.
Cite as

Ye Hong, Yanan Xin, Henry Martin, Dominik Bucher, and Martin Raubal. A Clustering-Based Framework for Individual Travel Behaviour Change Detection. In 11th International Conference on Geographic Information Science (GIScience 2021) - Part II. Leibniz International Proceedings in Informatics (LIPIcs), Volume 208, pp. 4:1-4:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{hong_et_al:LIPIcs.GIScience.2021.II.4,
  author =	{Hong, Ye and Xin, Yanan and Martin, Henry and Bucher, Dominik and Raubal, Martin},
  title =	{{A Clustering-Based Framework for Individual Travel Behaviour Change Detection}},
  booktitle =	{11th International Conference on Geographic Information Science (GIScience 2021) - Part II},
  pages =	{4:1--4:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-208-2},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{208},
  editor =	{Janowicz, Krzysztof and Verstegen, Judith A.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2021.II.4},
  URN =		{urn:nbn:de:0030-drops-147635},
  doi =		{10.4230/LIPIcs.GIScience.2021.II.4},
  annote =	{Keywords: Human mobility, Travel behaviour, Change detection, Trip clustering}
}

Hong, Eunpyeong

Document
DOI: 10.4230/LIPIcs.ISAAC.2018.43
Approximation Algorithm for Vertex Cover with Multiple Covering Constraints

Authors: Eunpyeong Hong and Mong-Jen Kao

Published in: LIPIcs, Volume 123, 29th International Symposium on Algorithms and Computation (ISAAC 2018)

Abstract
We consider the vertex cover problem with multiple coverage constraints in hypergraphs. In this problem, we are given a hypergraph G=(V,E) with a maximum edge size f, a cost function w: V - > Z^+, and edge subsets P_1,P_2,...,P_r of E along with covering requirements k_1,k_2,...,k_r for each subset. The objective is to find a minimum cost subset S of V such that, for each edge subset P_i, at least k_i edges of it are covered by S. This problem is a basic yet general form of classical vertex cover problem and a generalization of the edge-partitioned vertex cover problem considered by Bera et al. We present a primal-dual algorithm yielding an (f * H_r + H_r)-approximation for this problem, where H_r is the r^{th} harmonic number. This improves over the previous ratio of (3cf log r), where c is a large constant used to ensure a low failure probability for Monte-Carlo randomized algorithms. Compared to previous result, our algorithm is deterministic and pure combinatorial, meaning that no Ellipsoid solver is required for this basic problem. Our result can be seen as a novel reinterpretation of a few classical tight results using the language of LP primal-duality.
Cite as

Eunpyeong Hong and Mong-Jen Kao. Approximation Algorithm for Vertex Cover with Multiple Covering Constraints. In 29th International Symposium on Algorithms and Computation (ISAAC 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 123, pp. 43:1-43:11, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{hong_et_al:LIPIcs.ISAAC.2018.43,
  author =	{Hong, Eunpyeong and Kao, Mong-Jen},
  title =	{{Approximation Algorithm for Vertex Cover with Multiple Covering Constraints}},
  booktitle =	{29th International Symposium on Algorithms and Computation (ISAAC 2018)},
  pages =	{43:1--43:11},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-094-1},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{123},
  editor =	{Hsu, Wen-Lian and Lee, Der-Tsai and Liao, Chung-Shou},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.ISAAC.2018.43},
  URN =		{urn:nbn:de:0030-drops-99919},
  doi =		{10.4230/LIPIcs.ISAAC.2018.43},
  annote =	{Keywords: Vertex cover, multiple cover constraints, Approximation algorithm}
}
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