This is the Windows app named LTS: Learning to Search whose latest release can be downloaded as LTS.zip. It can be run online in the free hosting provider OnWorks for workstations.
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LTS: Learning to Search
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DESCRIPTION
LTS (Learning to Search) is an implementation of an algorithm described in "LTS: Discriminative Subgraph Mining by Learning from Search History" in Data Engineering (ICDE), IEEE 27th International Conference, pages 207-218, 2011. The purpose of LTS is to find discriminative subgraphs, which are smaller graphs that are embedded in larger graphs that all share a certain trait. A discriminative subgraph can help to characterize a complex graph and can be used to classify new graphs with unknown traits. LTS is an improvement on other subgraph mining algorithms because it uses empirical data from the search history of a first pass to help weed out unpromising search directions. This allows a second pass to spend more time investigating promising areas of search to generate the most discriminative subgraphs more quickly than before.
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This is an application that can also be fetched from https://sourceforge.net/projects/learning2search/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
