Reverse k-Ranks Queries on Large Graphs

Given a collection of objects, the reverse k-ranks query takes as input a query object q in the set and returns the top-k objects that rank q higher compared to where other objects rank q. This query has been studied in the vector space, however, there is no previous work in the context of graphs. In this paper, we propose a filterand-refinement framework, which prunes the search space while traversing the graph in search for the reverse k-ranks query results. We present an optimized algorithm and an index that apply on this framework and boost its performance. The proposed techniques are evaluated on real data; the experimental results show that our solutions scale well, rendering the query applicable for searching large graphs.

[1]  Man Lung Yiu,et al.  Efficient top-k aggregation of ranked inputs , 2007, TODS.

[2]  Raymond Chi-Wing Wong,et al.  Exact Top-k Nearest Keyword Search in Large Networks , 2015, SIGMOD Conference.

[3]  S. Muthukrishnan,et al.  Influence sets based on reverse nearest neighbor queries , 2000, SIGMOD '00.

[4]  Muhammad Aamir Cheema,et al.  Reverse k Nearest Neighbors Query Processing: Experiments and Analysis , 2015, Proc. VLDB Endow..

[5]  Ihab F. Ilyas,et al.  A survey of top-k query processing techniques in relational database systems , 2008, CSUR.

[6]  Zhao Zhang,et al.  Reverse k-Ranks Query , 2014, Proc. VLDB Endow..

[7]  Yufei Tao,et al.  Reverse nearest neighbors in large graphs , 2005, 21st International Conference on Data Engineering (ICDE'05).

[8]  Gert Sabidussi,et al.  The centrality index of a graph , 1966 .

[9]  Yufei Tao,et al.  Reverse kNN Search in Arbitrary Dimensionality , 2004, VLDB.

[10]  Panagiotis Symeonidis,et al.  Product recommendation and rating prediction based on multi-modal social networks , 2011, RecSys '11.

[11]  Hao Su,et al.  Reverse Top-k Search using Random Walk with Restart , 2013, Proc. VLDB Endow..

[12]  Feifei Li,et al.  Optimal location queries in road network databases , 2011, 2011 IEEE 27th International Conference on Data Engineering.

[13]  Shuchuan Lo,et al.  WMR--A Graph-Based Algorithm for Friend Recommendation , 2006, 2006 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2006 Main Conference Proceedings)(WI'06).

[14]  Christos Doulkeridis,et al.  Branch-and-bound algorithm for reverse top-k queries , 2013, SIGMOD '13.

[15]  Hong Cheng,et al.  Top-K Nearest Keyword Search on Large Graphs , 2013, Proc. VLDB Endow..

[16]  Alex Bavelas,et al.  Communication Patterns in Task‐Oriented Groups , 1950 .

[17]  Moni Naor,et al.  Optimal aggregation algorithms for middleware , 2001, PODS.

[18]  Ulrik Brandes,et al.  Centrality Estimation in Large Networks , 2007, Int. J. Bifurc. Chaos.

[19]  Marios Hadjieleftheriou,et al.  R-Trees - A Dynamic Index Structure for Spatial Searching , 2008, ACM SIGSPATIAL International Workshop on Advances in Geographic Information Systems.

[20]  Takuya Akiba,et al.  Fast exact shortest-path distance queries on large networks by pruned landmark labeling , 2013, SIGMOD '13.

[21]  Hanan Samet,et al.  Distance browsing in spatial databases , 1999, TODS.

[22]  Nikos Mamoulis,et al.  Efficient All Top-k Computation - A Unified Solution for All Top-k, Reverse Top-k and Top-m Influential Queries , 2013, IEEE Transactions on Knowledge and Data Engineering.

[23]  Chun Chen,et al.  Personalized tag recommendation using graph-based ranking on multi-type interrelated objects , 2009, SIGIR.

[24]  Akrivi Vlachou.  Reverse Top-k Queries , 2018, Encyclopedia of Database Systems.

[25]  Xu Sun,et al.  A unified graph model for personalized query-oriented reference paper recommendation , 2013, CIKM.

[26]  Edsger W. Dijkstra,et al.  A note on two problems in connexion with graphs , 1959, Numerische Mathematik.