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Home / programming language / Online Java Projects / Newspaper article reconstruction using ant colony optimization and bipartite
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Newspaper article reconstruction using ant colony optimization and bipartite

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SKU: PROJ1199 Categories: 2013 Projects, 2014 Projects, Datamining Projects, Final Year Projects, Online Java Projects Tags: academic projects, Android project 2013-2014, Android project Abstract, Android project list, btech projects, dotnet project 2013-2014, dotnet project Abstract, dotnet project list, Final Year Projects, ieee abstracts, ieee paper download, ieee projects 2013, ieee projects 2013 paper list, ieee projects 2013-2014, ieee projects 2014, ieee projects 2014 paper list, ieee projects 2015, ieee projects 2015 paper list., ieee titles, java project list, java projects 2013-2014, java projects Abstract, madurai software company, matlab project 2013-2014, matlab project Abstract, matlab project list, mtech projects, phd research work, Php project 2013-2014, Php project Abstract, Php project list, Power Electronic project 2013-2014, Power Electronic project Abstract, Power Electronic project list, project center Bangalore, project center chennai, project center coimbatore, project center Erode, project center Hyderabad, project center Kollam, project center madurai, project center Pandicherry, project center ramnad, project center Salem, project center Tiruneveli, project center trichy, research center, Students Projects, Vlsi project 2013-2014, Vlsi project Abstract, Vlsi project list
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Newspaper article reconstruction using ant colony optimization and bipartite. The primary information units in a newspaper are the articles. Article reconstruction from newspapers including article aggregation and reading order recovery is known to be a quite challenging task due to the complexity of the multi-article page layout. In this paper, we propose a novel approach for article reconstruction using a bipartite graph framework, which models the complex relationships between text blocks as one-to-one correspondences, and accomplishes the task by finding the optimal match on this graph. During the optimization process, various information sources, including geometric layout, linguistic and semantic content, are deeply mined in the bipartite < Final Year Projects > graph model to deal with the wide range of complex newspaper layouts. Moreover, quite different from the existing methods, we perform the two sub-tasks of article reconstruction in reverse order, that is, we detect the reading orders of the text blocks first and then use the reading order to aggregate blocks belonging to the same articles. Experimental results on 3312 newspaper pages with 23184 articles demonstrate that our method outperforms the state-of-the-art methods for newspaper article reconstruction. In addition, this method has been adopted in several large-scale newspaper digitalization projects.

Abstract— Newspaper article reconstruction using ant colony optimization and bipartite.

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