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<Article>
<Journal>
				<PublisherName>University of Isfahan</PublisherName>
				<JournalTitle>Transactions on Combinatorics</JournalTitle>
				<Issn>2251-8657</Issn>
				<Volume>12</Volume>
				<Issue>2</Issue>
				<PubDate PubStatus="epublish">
					<Year>2023</Year>
					<Month>06</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Approximate $k$-nearest neighbor graph on moving points</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage>65</FirstPage>
			<LastPage>72</LastPage>
			<ELocationID EIdType="pii">26356</ELocationID>
			
<ELocationID EIdType="doi">10.22108/toc.2022.130533.1943</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Zahed</FirstName>
					<LastName>Rahmati</LastName>
<Affiliation>Department of Mathematics and Computer Science, Amirkabir University of Technology, P.O.Box 15875-4413, Tehran,
Iran.</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2021</Year>
					<Month>12</Month>
					<Day>04</Day>
				</PubDate>
			</History>
		<Abstract>In this paper, we introduce an approximation for the $k$-nearest neighbor graph ($k$-NNG) on a point set $P$ in $\mathbb{R}^d$. For any given $\varepsilon&gt;0$, we construct a graph, that we call the \emph{approximate $k$-NNG}, where the edge with the $i$th smallest length incident to a point $p$ in this graph is within a factor of $(1+\varepsilon)$ of the length of the edge with the $i$th smallest length incident to $p$ in the $k$-NNG.&lt;br /&gt; &lt;br /&gt;For a set $P$ of $n$ moving points in $\mathbb{R}^d$, where the trajectory of each point $p\in P$ is given by $d$ polynomial functions of constant bounded degree, where each function gives one of the $d$ coordinates of $p$, we compute the number of combinatorial changes to the approximate $k$-NNG, and provide a kinetic data structure (KDS) for maintenance of the edges of the approximate $k$-NNG over time. Our KDS processes $O(kn^2\log^{d+1} n)$ events, each in time $O(\log^{d+1}n)$.</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">approximation</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">$k$-Nearest Neighbor Graph</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Moving Points</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://toc.ui.ac.ir/article_26356_e43137e88ed08bf405990ce3538fd339.pdf</ArchiveCopySource>
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