RT Journal Article
T1 Local-based semantic navigation on a networked representation of information
A1 Capitán, José A.
A1 Borge-Holthoefer, Javier
A1 Gómez, Sergio
A1 Martínez-Romo, Juan
A1 Araujo, Lourdes
A1 Cuesta, José A.
A1 Arenas, Alex
AB The size and complexity of actual networked systems hinders the access to a global knowledge of their structure. This fact pushes the problem of navigation to suboptimal solutions, one of them being the extraction of a coherent map of the topology on which navigation takes place. In this paper, we present a Markov chain based algorithm to tag networked terms according only to their topological features. The resulting tagging is used to compute similarity between terms, providing a map of the networked information. This map supports local-based navigation techniques driven by similarity. We compare the efficiency of the resulting paths according to their length compared to that of the shortest path. Additionally we claim that the path steps towards the destination are semantically coherent. To illustrate the algorithm performance we provide some results from the Simple English Wikipedia, which amounts to several thousand of pages. The simplest greedy strategy yields over an 80% of average success rate. Furthermore, the resulting content-coherent paths most often have a cost between one- and threefold compared to shortest-path lengths.
PB Plos
SN 1932-6203
YR 2012
FD 2012-08-24
LK https://hdl.handle.net/10016/19000
UL https://hdl.handle.net/10016/19000
LA eng
NO The authors acknowledge financial support through Grant No. FIS2008-01240, FIS2009-13364-C02-01, Holopedia (Grant No. TIN2010-21128-C02-01), MOSAICO (Grant No. FIS2006-01485), PRODIEVO (Grant No. FIS2011-22449), and Complexity-NET RESINEE, all of them from Ministerio de Educacion y Ciencia inSpain, as well as support from Research Networks MODELICO-CM (Grant No. S2009/ESP-1691) and MA2VICMR (Grant Nº. S2009/TIC-1542) from Comunidad de Madrid, and Network 2009-SGR-838 from Generalitat de Catalunya. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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RD 1 sept. 2024