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Similarity Search using Concept Graphs
Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, 2014The rapid proliferation of hand-held devices has led to the development of rich, interactive and immersive applications, such as e-readers for electronic books. These applications motivate retrieval systems that can implicitly satisfy any information need of the reader by exploiting the context of the user's interactions.
Rakesh Agrawal +3 more
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Efficient Graph Similarity Search Over Large Graph Databases
IEEE Transactions on Knowledge and Data Engineering, 2015Since many graph data are often noisy and incomplete in real applications, it has become increasingly important to retrieve graphs $g$ in the graph database $D$ that approximately match the query graph $q$ , rather than exact graph matching.
Weiguo Zheng +4 more
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Graph similarity search on large uncertain graph databases
The VLDB Journal, 2014Many studies have been conducted on seeking an efficient solution for graph similarity search over certain (deterministic) graphs due to its wide application in many fields, including bioinformatics, social network analysis, and Resource Description Framework data management. All prior work assumes that the underlying data is deterministic. However, in
Yuan, Ye +3 more
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Scalable graph similarity search in large graph databases
2015 IEEE Recent Advances in Intelligent Computational Systems (RAICS), 2015We consider the problem of searching a collection of graphs D to find graphs that are most similar to a query graph Q. This has several applications in areas like computational biology, drug design, computational chemistry, collaborative networks, social networks etc. We use graphlet kernel to define similarity between graphs.
P. Kiran, Naveen Sivadasan
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Tolerant similarity search in graph database
2017 Computing Conference, 2017In today's world, we come across number of problems which requires modeling the elements of these problems in the form of graph and then get the result by manipulating graphs. One of the operations on such graphs is finding graphs from the graph database that are similar to a particular query graph.
Meera Dhabu +2 more
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Efficient processing of graph similarity search
World Wide Web, 2014A graph similarity search is to find a set of graphs from a graph database that are similar to a given query graph. Existing works solve this problem by first defining a similarity measure between two graphs, and then presenting a filtering mechanism that reduces the number of candidate graphs.
Choi, R Choi, Ryan +1 more
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Substructure similarity search in graph databases
Proceedings of the 2005 ACM SIGMOD international conference on Management of data, 2005Advanced database systems face a great challenge raised by the emergence of massive, complex structural data in bioinformatics, chem-informatics, and many other applications. The most fundamental support needed in these applications is the efficient search of complex structured data.
Xifeng Yan, Philip S. Yu, Jiawei Han
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Tutorial: Graph-based Methods for Similarity Searches
Anais Estendidos do XXXVIII Simpósio Brasileiro de Banco de Dados (SBBD Estendido 2023), 2023Similarity searches are based on retrieving similar data of one or more data used as reference according to an intrinsic characteristic of the data. Recently, graph-based methods have emerged as a very efficient option to execute similarity queries in metric and non-metric spaces.
Larissa C. Shimomura, Daniel S. Kaster
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Toward Representation Independent Similarity Search Over Graphs
Proceedings of Workshop on GRAph Data management Experiences and Systems, 2014Finding similar entities over data graphs is an important problem with many applications. Current similarity search algorithms use intuitively appealing heuristics that leverage the link information in the data graph to quantify the degree of similarity between its entities.
Yodsawalai Chodpathumwan +4 more
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Efficient Similarity Search for Sets over Graphs
IEEE Transactions on Knowledge and Data Engineering, 2019Measuring similarities among different nodes is important in graph analysis tasks, such as link prediction, and recommendation. Among different similarity measures, SimRank is one of the most popular and promising ones, and has received a lot of research attention.
Wang, Yue +5 more
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