Under Supervision Of Prof
نویسندگان
چکیده
The objective of this project is to identify and label spatial keywords in the given corpus. Instead of using any parser based method, our approach is based on word vector models. We use Google’s Word2Vec for creating word vectors. We train a backpropagation neural network to extract the relationship between three important spatial aspects, that is, trajectors, landmarks and spatial indicators. Given a pair of a trajector and a landmark, we try to predict a spatial indicator best describing the relationship between the given trajector and landmark.
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