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- W2285202296 abstract "The purpose of this research is to design andimplement a new methodology that captures thenatural languageunderstanding of events from English natural language text andmodel it using StochasticPetri Nets. To establish a baseline ofrecent natural language processing (NLP) and understanding(NLU)research, two surveys are presented. One is a general surveyin NLP and NLU methodologies forprocessing multi-documents. Itsummarizes and presents methodologies in terms of theirfeatures,capabilities, and maturity. The second survey focuses ongraph-based methods for NL text processing andunderstanding andanalyzes them in terms of their functional descriptions,capabilities and maturities. Inrecent years, NLP/NLU researchershave narrowed their domain to graph methodologies due toimprovedefficiency over older methods. Thus, to accomplish ourgoal, we firstly implemented a NL text to graphconversion method.This method extracts events in terms of their agents, actions, andpatients from subjectnouns, verbs, and object nouns within eachphrase and sentence of a text and produces a graph consistingofnodes representing nouns and verbs and edges representing theirrelations. A significant effort went intohandling complex sentencesconsisting of multiple phrases, active and passive sentences, andmultipleagents, actions, and patients. The graph provides abaseline implementation, which we could relate to othergraphmethodologies and provide a structured approach to NLP and NLU fromtext. Next, we embedded anew NL text-graphs to Stochastic Petri Net(SPN) graph conversion methodology into our model torepresentevents associated with NL text. SPN graphs provide not only astructured representation thatgraphs provide, but also othercapabilities, such as representing and adjusting timing using itstransitioncomponents, constraining flow with its inhibiting places,stochastic behavior of its markings, and colormarkings [89, 90]. Weuse these added capabilities from SPN modeling to capture new NLUcapabilitiesof events from NL text. We demonstrated sentencedisambiguation of events." @default.
- W2285202296 created "2016-06-24" @default.
- W2285202296 creator A5038693630 @default.
- W2285202296 date "2013-01-01" @default.
- W2285202296 modified "2023-09-27" @default.
- W2285202296 title "Natural Language Document and Event Association Using Stochastic Petri Net Modeling" @default.
- W2285202296 hasPublicationYear "2013" @default.
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