Finding reverse nearest neighbors by region

Adhinugraha, Kiki Maulana; Taniar, David; Indrawan, Maria

doi:10.1002/cpe.3056

Cited by 15 publications

(7 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Therefore, the challenge is how to create a zone of influence for one query object only, without creating zones of influence of all objects. Maulana et al [2] has solved this problem by incrementally processing objects. The process will stop processing objects once a zone of influence is formed; consequently objects that have not been processed will not need to be processed at all.…”

Section: Zones Of Influencementioning

confidence: 99%

“…The process will stop processing objects once a zone of influence is formed; consequently objects that have not been processed will not need to be processed at all. Maulana et al [2] assumes that all candidate objects have been pre-sorted based on their distances to the query object. Further improvement of this method becomes a challenge.…”

Section: Zones Of Influencementioning

confidence: 99%

“…It means that any points or coordinates or locations will consider object p 3 as their closest object of interest -this gives the notion of zones of influence that object p 3 has. This zone of influence has been used in bichromatic RNN [2,24], whereby there are two groups of objects; one of which is object group p. The aim is to create a region for a given p as the query object, and form a region. Once the region is formed, we can search for all non-p objects that are located in this region.…”

Section: Zones Of Influencementioning

confidence: 99%

See 2 more Smart Citations

A taxonomy for region queries in spatial databases

Taniar

Rahayu

2015

Journal of Computer and System Sciences

Self Cite

View full text Add to dashboard Cite

In spatial databases, there are two basic types of queries, namely nearest neighbour queries (kNN) and range queries. Spatial range queries are not only finding objects of interest within a certain range or radius, but feature a wide spectrum: from finding objects of interest to forming the range (or region). Therefore, in this paper, we coin a term "Region Queries" to indicate a broad category of spatial range queries. It is imperative to understand the full capabilities of region queries, before starting to work on processing and optimising such queries. The aim of this paper is to show a complete picture of region queries. In this study, we present taxonomy of region queries, comprising of three categories: (i) finding objects of interest, (ii) forming regions, and (iii) determining centroids. These three query types form a comprehensive view of what region queries are about.

show abstract

Section: Zones Of Influencementioning

confidence: 99%

Section: Zones Of Influencementioning

confidence: 99%

Section: Zones Of Influencementioning

confidence: 99%

See 1 more Smart Citation

A taxonomy for region queries in spatial databases

Taniar

Rahayu

2015

Journal of Computer and System Sciences

Self Cite

View full text Add to dashboard Cite

show abstract

“…A lot of applications are using spatial data to help our daily necessity, such as the GPS. The application of spatial data itself is accessible not only on desktop computers, but it is also very popular in mobile environments these days as mobile devices provide significant services in our everyday life [7,27,41,42,47,53,32]. According to StatisticBrain, about 81% of mobile users use their device for Maps and directions [1].…”

Section: Fig 1 Illustration Of a Road Network With Spatial Keyword Omentioning

confidence: 99%

IG-Tree: an efficient spatial keyword index for planning best path queries on road networks

et al. 2018

Self Cite

View full text Add to dashboard Cite

Due to the popularity of Spatial Databases, many search engine providers have started to expand their text searching capability to include geographical information. Because of this reason, many new queries on spatial objects affiliated with textual information, known as the Spatial Keyword Queries, have taken significant research interest in the past years. Unfortunately, most of existing works on Spatial Keyword Queries only focus on objects retrieval. There is barely any work on route planning queries, even though route planning is often needed in our daily life. In this research, we propose the Best Path Query, which we find the best optimum route from two different spatial locations that visits or avoids the objects that are specified by the textual data given by the user. We show that Best Path Query is an NP-Hard problem. We propose an efficient indexing technique, namely IG-Tree, and three different algorithms with different trade-offs to process the Best Path Queries on Road Networks. Our extensive experimental study demonstrates the efficiency and accuracy of our proposed approach.

show abstract

“…The next three papers present intelligent optimization and data processing techniques, including genetic algorithms, independent component analysis, and evolutionary game theory. The following three papers deal with data modeling and analysis in wireless, mobile, and Web‐based computing systems. The final two papers bring intelligent techniques from image processing field.…”

mentioning

confidence: 99%

Advances in secure and intelligent data processing

Xhafa

Chen

Huang

et al. 2013

Concurrency and Computation

View full text Add to dashboard Cite

EDITORIALAdvances in secure and intelligent data processingWith the fast proliferation of various computational paradigms, from Web-based to wireless and mobile computing, intelligent data processing and security have become cross-cutting features of large scale Internet-based system. On the one hand, there is data being generated everywhere, from various sources and heterogenous formats (such as document repositories, business process data, network data, mobile communications data, server logs data, etc.). On the other hand, the nature of the data, the amount, and data sensitivity, among other features, are promoting the combination of intelligent processing with security intelligence to deliver next generation secure and intelligent systems and applications.This special issue brings together high quality contributions in the interleaving research areas of intelligent data processing and intelligent techniques in security data analysis. The papers of the special issues have also identified and discussed the challenges in the field that will lead to new avenues in intelligent processing for secure and intelligent systems and applications.The special issue consists of 13 papers organized as follows. The first five papers [1][2][3][4][5] are devoted to intelligent secure data analysis, encryption, and authentication techniques. The next three papers [6][7][8] present intelligent optimization and data processing techniques, including genetic algorithms, independent component analysis, and evolutionary game theory. The following three papers [9][10][11] deal with data modeling and analysis in wireless, mobile, and Web-based computing systems. The final two papers [12,13] bring intelligent techniques from image processing field.

show abstract

Finding reverse nearest neighbors by region

Cited by 15 publications

References 33 publications

A taxonomy for region queries in spatial databases

A taxonomy for region queries in spatial databases

IG-Tree: an efficient spatial keyword index for planning best path queries on road networks

Advances in secure and intelligent data processing

Contact Info

Product

Resources

About