Automatic generation of portable parallel natural language parsers

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dc.contributor.author Manousopoulou, AG en
dc.contributor.author Manis, G en
dc.contributor.author Tsanakas, P en
dc.contributor.author Papakonstantinou, G en
dc.date.accessioned 2014-03-01T02:41:19Z
dc.date.available 2014-03-01T02:41:19Z
dc.date.issued 1997 en
dc.identifier.issn 10636730 en
dc.identifier.uri https://dspace.lib.ntua.gr/xmlui/handle/123456789/30457
dc.subject Automatic Generation en
dc.subject Coarse Grained en
dc.subject Finite State Machine en
dc.subject Natural Language en
dc.subject Natural Language Parsing en
dc.subject Operating System en
dc.subject Parallel Implementation en
dc.subject Software Platform en
dc.subject.other Computer operating systems en
dc.subject.other Finite automata en
dc.subject.other Parallel processing systems en
dc.subject.other Program compilers en
dc.subject.other Sequential machines en
dc.subject.other Finite state machines en
dc.subject.other Portable parallel natural language parsers en
dc.subject.other Natural language processing systems en
dc.title Automatic generation of portable parallel natural language parsers en
heal.type conferenceItem en
heal.identifier.primary 10.1109/TAI.1997.632252 en
heal.identifier.secondary http://dx.doi.org/10.1109/TAI.1997.632252 en
heal.publicationDate 1997 en
heal.abstract Since natural language parsing is a computationally intensive task, the parallel parsing of natural language seems a promising choice. This work describes both the Eu-PAGE meta-compiler for the Eurotra formalism, a tool that automatically generates parallel natural language parsers, and the Dialogos parser, a parallel parser for the Greek language generated by Eu-PAGE. Parallel parsers generated by Eu-PAGE are based on finite state machines, employ coarse grained parallelism, and are portably implemented on top of two parallel software platforms: PVM and Orchid. Orchid uses light weight processes as the basic unit of parallelism, enhanced with advanced operating system facilities. The collected experimental results so far demonstrate satisfactory speed-ups of the parallel implementations compared to the sequential one. en
heal.publisher IEEE, Piscataway, NJ, United States en
heal.journalName Proceedings of the International Conference on Tools with Artificial Intelligence en
dc.identifier.doi 10.1109/TAI.1997.632252 en
dc.identifier.spage 174 en
dc.identifier.epage 177 en

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