@InProceedings{PauRiba2017,
author="Pau Riba
and Anjan Dutta
and Josep Llados
and Alicia Fornes
and Sounak Dey",
title="Improving Information Retrieval in Multiwriter Scenario by Exploiting the Similarity Graph of Document Terms",
booktitle="14th International Conference on Document Analysis and Recognition",
year="2017",
pages="475--480",
optkeywords="document  terms",
optkeywords="information  retrieval",
optkeywords="affinity graph",
optkeywords="graph  of  document  terms",
optkeywords="multiwriter",
optkeywords="graph  diffusion",
abstract="Information Retrieval (IR) is the activity of obtaining  information  resources  relevant  to  a  questioned  information. It  usually  retrieves  a  set  of  objects  ranked  according  to  the relevancy  to  the  needed  fact.  In  document  analysis,  information retrieval  receives  a  lot  of  attention  in  terms  of  symbol  and word spotting. However, through decades the community mostly focused either on printed or on single writer scenario, where thestate-of-the-art results have achieved reasonable performance on the available datasets. Nevertheless, the existing algorithms do not perform accordingly on multiwriter scenario. A graph representing  relations  between  a  set  of  objects  is  a  structure  where  each node delineates an individual element and the similarity between them  is  represented  as  a  weight  on  the  connecting  edge.  In  this paper, we explore different analytics of graphs constructed from words or graphical symbols, such as diffusion, shortest path, etc. to improve the performance of information retrieval methods in multiwriter  scenario",
optnote="DAG; 600.097; 601.302; 600.121",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=3053), last updated on Mon, 07 Dec 2020 14:29:40 +0100",
file=":http://refbase.cvc.uab.es/files/.pdf:PDF"
}