Search arXivSearch

arXiv · 1809.10702

A Novel and Efficient Data Point Neighborhood Construction Algorithm based on Apollonius Circle

Abstract

Neighborhood construction models are important in finding connection among the data points, which helps demonstrate interrelations among the information. Hence, employing a new approach to find neighborhood among the data points is a challenging issue. The methods, suggested so far, are not useful for simultaneous analysis of distances and precise examination of the geometric position of the data as well as their geometric relationships. Moreover, most of the suggested algorithms depend on regulating parameters including number of neighborhoods and limitations in fixed regions. The purpose of the proposed algorithm is to detect and offer an applied geometric pattern among the data through data mining. Precise geometric patterns are examined according to the relationships among the data in neighborhood space. These patterns can reveal the behavioural discipline and similarity across the data. It is assumed that there is no prior information about the data sets at hand. The aim of the present research study is to locate the precise neighborhood using Apollonius circle, which can help us identify the neighborhood state of data points. High efficiency of Apollonius structure in assessing local similarities among the observations has opened a new field of the science of geometry in data mining. In order to assess the proposed algorithm, its precision is compared with the state-of-the-art and well-known (k-Nearest Neighbor and epsilon-neighborhood) algorithms.

Explore related subjects

Keep this discovery

BibTeXRIS

Shahin Pourbahrami, Leyli Mohammad Khanli, Sohrab Azimpour. 2018-09-27. A Novel and Efficient Data Point Neighborhood Construction Algorithm based on Apollonius Circle. https://arxiv.org/abs/1809.10702

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Almost Linear Universal Point Sets for Planar Graphs

A point set is universal for planar graphs on $n$ vertices if every such graph has a straight-line drawing without crossings whose vertices belong to the set. We construct universal point sets of size $n^{1+o(1)}$, improving the previous quadratic upper bound. Our construction uses the reduction of Bannister, Cheng, Devanny, and Eppstein from universal point sets to superpatterns for $213$-avoiding permutations. We represent these permutations by ordered rooted forests and construct a small family of intervals containing every such forest. The result follows from a straightforward bound on the size of the family of intervals. GPT-6 Astra assisted in developing the construction and proof.

cs.CG

Some results on Archdeacon's conjecture for rotation systems

A rotation system on $n$ elements assigns to each element a cyclic order of the other $n-1$ elements. A four-element subset is non-planar if its induced rotation system cannot be realized by a crossing-free drawing of $K_4$. As a combinatorial strengthening of Hill's conjecture on the crossing number of the complete graph, Archdeacon conjectured that every rotation system on $n$ elements has at least $H(n)=\frac{1}{4} \lfloor\frac {n}{2}\rfloor \lfloor\frac{n-1}{2}\rfloor \lfloor\frac{n-2}{2}\rfloor \lfloor\frac{n-3}{2}\rfloor$ non-planar four-element subsets. We computationally verify Archdeacon's conjecture for $n\leq 10$ and show that every extremal rotation system in these orders is realizable by a simple drawing. With computer assistance, we prove that every rotation system on $n$ elements has at least $(8/9 - o(1)) H(n)$ non-planar four-element subsets. We also present a proof by hand for a weaker lower bound of $(2/3-o(1)) H(n)$. Finally, extending recent work of Felsner on antipodal pairs in drawings, we show that Archdeacon's conjecture holds for antipodally shellable rotation systems.

cs.CG

The Hyperbolic Surface Distance, Diameter, and Dirichlet Problems

Despite the prominence of hyperbolic surfaces in mathematics, basic algorithmic questions about them, even computing the distance between two points, have remained open, leaving many features of these surfaces inaccessible. The classical machinery assumes a polyhedral structure absent on a smooth surface. We remove these obstacles. We begin with an efficient $O(g^2)$ algorithm for the distance between two points, where $g$ is the genus of the surface. Building on it, we obtain an $O(g^2 \log g)$ method for answering distance queries from a fixed source and, as a consequence, for recentering a Dirichlet domain around an arbitrary point. This understanding of distances on the surface then lets us approximate the diameter to within any $\eps$ in time $O(g^3 \log g / \eps^2)$. We further show that the diameter, a single real number encoding a great deal about the surface, is exactly computable. Its hyperbolic cosine is an algebraic number over the field encoding the coefficients of the hyperbolic isometries defining the surface.

cs.CG