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Graph based Nearest Neighbor Search: Promises and Failures [article]

Peng-Cheng Lin, Wan-Lei Zhao
2019 arXiv   pre-print
Recently, graph based nearest neighbor search gets more and more popular on large-scale retrieval tasks.  ...  Moreover, we find that similar high search speed efficiency as the one with hierarchical structure could be achieved with the support of flat k-NN graph after graph diversification.  ...  Since overlapping happens between the neighbors and reverse neighbors, we actually take the union of diversified neighbors and reverse neighbors.  ... 
arXiv:1904.02077v5 fatcat:gdlf26kxpje55aul2hhx5qsy3u

Fast Instance Search Based on Approximate Bichromatic Reverse Nearest Neighbor Search

Masakazu Iwamura, Nobuaki Matozaki, Koichi Kise
2014 Proceedings of the ACM International Conference on Multimedia - MM '14  
neighbor search method, bucket distance hashing (BDH).  ...  Since the BM25 is obtained by solving the bichromatic reverse nearest neighbor (BRNN) search problem, we propose an approximate method for the problem based on the state-of-the-art approximate nearest  ...  APPROXIMATE BRNN SEARCH Reverse Nearest Neighbor Search Reverse nearest neighbor (RNN) search problem is to find the nearest neighbor (query) to a datum [5] .  ... 
doi:10.1145/2647868.2654988 dblp:conf/mm/IwamuraMK14 fatcat:ynkrxpqbcvbllk2smydddmbmqi

Efficient reverse k-nearest neighbor search in arbitrary metric spaces

Elke Achtert, Christian Böhm, Peer Kröger, Peter Kunath, Alexey Pryakhin, Matthias Renz
2006 Proceedings of the 2006 ACM SIGMOD international conference on Management of data - SIGMOD '06  
The reverse k-nearest neighbor (RkNN) problem, i.e. finding all objects in a data set the k-nearest neighbors of which include a specified query object, is a generalization of the reverse 1-nearest neighbor  ...  In this paper, we propose the first approach for efficient RkNN search in arbitrary metric spaces where the value of k is specified at query time.  ...  Acknowledgement We are grateful with Yufei Tao, Dimitris Papadias, Xiang Lian and Xiaokui Xiao providing us the source code of their Reverse kNN Search in [11] .  ... 
doi:10.1145/1142473.1142531 dblp:conf/sigmod/AchtertBKKPR06 fatcat:3qgpvzngvrbf3gxvofqb26vxge

Exact and Approximate Reverse Nearest Neighbor Search for Multimedia Data [chapter]

Jessica Lin, David Etter, David DeBarr
2008 Proceedings of the 2008 SIAM International Conference on Data Mining  
In this work we motivate and investigate the problem of reverse nearest neighbor search on high dimensional, multimedia data.  ...  We demonstrate the utility of reverse nearest neighbor search by showing how it can help improve the classification accuracy.  ...  Given a query object, reverse nearest neighbor search finds all objects in the database whose nearest neighbors are the query object.  ... 
doi:10.1137/1.9781611972788.60 dblp:conf/sdm/LinED08 fatcat:ij3g62hupna4hancgu62l6syni

Approximate Direct and Reverse Nearest Neighbor Queries, and the k-nearest Neighbor Graph

Karina Figueroa, Rodrigo Paredes
2009 2009 Second International Workshop on Similarity Search and Applications  
A related, far less explored primitive is to obtain the dataset elements which would have the query object within their own k-nearest neighbors, known as the reverse k-nearest neighbor query.  ...  Retrieving the k-nearest neighbors of a query object is a basic primitive in similarity searching.  ...  In this paper we use the alternative search order to efficiently solve direct and reverse kNN queries with high probability.  ... 
doi:10.1109/sisap.2009.33 dblp:conf/sisap/FigueroaP09 fatcat:wieiyzyfdngdlarrn5rg2bjv6m

Contiguous Neighbour Exploration through Keywords

G. Pushpa, G. Mutyalamma
2017 International Journal of Trend in Scientific Research and Development  
answer closest neighbor questions with pivotal words progressively.  ...  calculations that may answer closest neighbor questions with pivotal words progressively.  ...  CONCLUSION In this paper, we proposed a new technique for efficient nearest neighbor search in a set of high-dimensional points.  ... 
doi:10.31142/ijtsrd8235 fatcat:q2m3scdz6bc2tiikzjkxcez4bq

Efficient k-nearest neighbor graph construction for generic similarity measures

Wei Dong, Charikar Moses, Kai Li
2011 Proceedings of the 20th international conference on World wide web - WWW '11  
K-Nearest Neighbor Graph (K-NNG) construction is an important operation with many web related applications, including collaborative filtering, similarity search, and many others in data mining and machine  ...  We present NN-Descent, a simple yet efficient algorithm for approximate K-NNG construction with arbitrary similarity measures.  ...  We start by picking a random approximation of K-NN for each object, iteratively improve that approximation by comparing each object against its current neighbors' neighbors, including both K-NN and reverse  ... 
doi:10.1145/1963405.1963487 dblp:conf/www/DongCL11 fatcat:bsy4mgky6jbbtg7jp5p2lhr6qm


N.Minojini .
2014 International Journal of Research in Engineering and Technology  
Conventional spatial queries, nearest neighbor retrieval and vary search consists solely conditions on objects geometric property.  ...  As an example instead of considering all the hotels, a nearest neighbor queries would instead elicit the building that's nearest to among people who offer services like pool, internet at a similar time  ...  [2] , combined the notion of keyword searches with reverse nearest neighbor queries.  ... 
doi:10.15623/ijret.2014.0311084 fatcat:asflbzy7gvcdvc3nbja6eyiama

Approximate k-NN Graph Construction: a Generic Online Approach [article]

Wan-Lei Zhao, Hui Wang, Chong-Wah Ngo
2020 arXiv   pre-print
On the other hand, the built k-nearest neighbor graph is used to support k-nearest neighbor search.  ...  On the one hand, the approximate k-nearest neighbor graph construction is treated as a search task.  ...  Memory for IDs, occlusion factors and distances of k neighbors and reverse neighbors must be allocated.  ... 
arXiv:1804.03032v5 fatcat:4go4mznqtrahjgfudlaiojxxsi


Sonal S. Kasare .
2013 International Journal of Research in Engineering and Technology  
Conservative spatial queries, such as range search and nearest neighbor reclamation, involve only conditions on objects' numerical properties.  ...  Currently the best solution to such queries is based on the InformationRetrieval2-tree, which, has a few deficiencies that seriously impact its efficiency.  ...  A typical example is that the real nearest neighbor lies quite far away from the query point, while all the closer neighbors are missing at least one of the query keywords.  ... 
doi:10.15623/ijret.2013.0212094 fatcat:yof4wjntgbdfrnqjk2lrznd4cu

Reverse Furthest Neighbors in Spatial Databases

Bin Yao, Feifei Li, Piyush Kumar
2009 Proceedings / International Conference on Data Engineering  
Experiments on both synthetic and real data sets confirm the efficiency and scalability of proposed algorithms over the bruteforce search based approach.  ...  Another interesting version of RFN query is the bichromatic reverse furthest neighbor (BRFN) query.  ...  MONOCHROMATIC REVERSE FURTHEST NEIGHBORS We search for efficient, R-tree based algorithms for the MRFN queries in this section.  ... 
doi:10.1109/icde.2009.62 dblp:conf/icde/YaoLK09 fatcat:3gq66oikhbhalbkwc2ngg52jv4

Monitoring path nearest neighbor in road networks

Zaiben Chen, Heng Tao Shen, Xiaofang Zhou, Jeffrey Xu Yu
2009 Proceedings of the 35th SIGMOD international conference on Management of data - SIGMOD '09  
This paper addresses the problem of monitoring the k nearest neighbors to a dynamically changing path in road networks.  ...  In the searching phase, the BNE finds the shortest path to the destination, during which a candidate set that guarantees to include the k -PNN is generated at the same time.  ...  This problem is well studied in the literature, and its variants include k -Nearest Neighbor search [6, 17] , Continuous Nearest Neighbor search [1, 10, 21] , Aggregate Nearest Neighbor queries [14,  ... 
doi:10.1145/1559845.1559907 dblp:conf/sigmod/ChenSZY09 fatcat:467fil4ovzb3vn45tdxgncogre

Improve Searching by Reinforcement Learning in Unstructured P2Ps

Xiuqi Li, Jie Wu
2006 26th IEEE International Conference on Distributed Computing Systems Workshops (ICDCSW'06)  
It explores new paths by forwarding queries to randomly chosen neighbors. It also exploits the paths that have been discovered to reduce the cumulative query cost.  ...  Keywords: Hint-based search, intelligent search, peer-to-peer networks, reinforcement learning, unstructured P2P.  ...  To avoid searching loops (duplicate queries), each Query message carries all node IDs on the query path so far.  ... 
doi:10.1109/icdcsw.2006.64 dblp:conf/icdcsw/LiW06 fatcat:tmtzojahzjgfvitayqsb3ibyga

Approximate reverse k-nearest neighbor queries in general metric spaces

Elke Achtert, Christian Böhm, Peer Kröger, Peter Kunath, Alexey Pryakhin, Matthias Renz
2006 Proceedings of the 15th ACM international conference on Information and knowledge management - CIKM '06  
Our method uses an approximation of the nearest-neighbor-distances in order to prune the search space.  ...  In this paper, we propose an approach for efficient approximative RkNN search in arbitrary metric spaces where the value of k is specified at query time.  ...  INTRODUCTION A reverse k-nearest neighbor (RkNN) query returns the data objects that have the query object in the set of their k-nearest neighbors.  ... 
doi:10.1145/1183614.1183731 dblp:conf/cikm/AchtertBKKPR06 fatcat:vflcsehwbbgevlcgytp4wng2fi

ISRL: intelligent search by reinforcement learning in unstructured peer-to-peer networks

Xiuqi Li, Jie Wu, Shi Zhong
2008 International Journal of Parallel, Emergent and Distributed Systems  
To discover the best path to desired files, ISRL not only explores new paths by forwarding queries to randomly chosen neighbors, but also exploits the paths that have been discovered for reducing the cumulative  ...  In this paper, we propose an intelligent searching scheme, called ISRL (Intelligent Search by Reinforcement Learning), which systematically seeks the best route to desired files by reinforcement learning  ...  To avoid searching loops (duplicate queries), each Query message carries all node IDs on the query path so far.  ... 
doi:10.1080/17445760701442176 fatcat:66zwjarjgjbddo7qezuhn7azda
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