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teaching:mfe:is [2016/04/01 16:30] svsummer |
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| * Contact: [[ezimanyi@ulb.ac.be|Esteban Zimányi]] | * Contact: [[ezimanyi@ulb.ac.be|Esteban Zimányi]] | ||
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| + | =====Efficient Management of (Sub-)structure Similarity Search Over Large Graph Databases. ===== | ||
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| + | The problem of (sub-)structure similarity search over graph data has recently drawn significant research interest due to its importance in many application areas such as in Bio-informatics, Chem-informatics, Social Network, Software Engineering, World Wide Web, Pattern Recognition, etc. Consider, for example, the area of drug design, efficient techniques are required to query and analyze huge data sets of chemical molecules thus shortening the discovery cycle in drug design and other scientific activities. | ||
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| + | Graph edit distance is widely accepted as a similarity measure of labeled graphs due to its ability to cope with any kind of graph structures and labeling schemes. Today, graph edit similarity plays a significant role in managing graph data , and is employed in a variety of analysis tasks such as graph classification and clustering, object recognition in computer vision, etc. | ||
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| + | In this master thesis project, due to the hardness of graph edit distance (computing graph edit distance is known to be NP-hard problem), the student will investigate the current approaches that deals with problem complexity while searching for similar (sub-)structures. At the end, the student should be able to empirically analyze and contrast some of the interesting approaches. | ||