Fiction authors rarely provide detailed descriptions of scenes, preferring the reader to fill in the details using their imagination. Therefore, to perform detailed text-to-scene conversion from books, we need to not only identify explicit objects but also infer implicit objects. In this paper, we describe an approach to inferring objects using Wikipedia and WordNet. In our experiments, we are able to infer implicit objects such as monitor and computer by identifying explicit objects such as keyboard.
@InProceedings{cropper:OASIcs.ICCSW.2014.19, author = {Cropper, Andrew}, title = {{Identifying and inferring objects from textual descriptions of scenes from books}}, booktitle = {2014 Imperial College Computing Student Workshop}, pages = {19--26}, series = {Open Access Series in Informatics (OASIcs)}, ISBN = {978-3-939897-76-7}, ISSN = {2190-6807}, year = {2014}, volume = {43}, editor = {Neykova, Rumyana and Ng, Nicholas}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICCSW.2014.19}, URN = {urn:nbn:de:0030-drops-47690}, doi = {10.4230/OASIcs.ICCSW.2014.19}, annote = {Keywords: Text-to-Scene Conversion, Natural Language Processing, Artificial Intelligence} }
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