Hugo Liu (2002). Semantic Understanding and Commonsense Reasoning in an Adaptive Photo Agent. M.Eng. Thesis, Department of Electrical Engineering and Computer Science, MIT, 160pp.
Liu, H. (2002). Semantic Understanding and Commonsense Reasoning in an Adaptive Photo Agent [Master's thesis, Massachusetts Institute of Technology].
@mastersthesis{liu2002semantic,
author = {Hugo Liu},
title = {Semantic Understanding and Commonsense Reasoning in an Adaptive Photo Agent},
school = {Massachusetts Institute of Technology},
address = {Cambridge, MA},
note = {Department of Electrical Engineering and Computer Science, MIT, 160pp},
url = {https://starheartsong.com/papers/pdf/MEngThesis2002-CSAria.pdf},
year = {2002}
}This master's thesis develops ARIA as an integrated photo-storytelling agent rather than a single retrieval algorithm. WALI turns prose into event structures spanning people, places, times, things, events, and emotions. CRIS compiles about 80,000 Open Mind facts into a weighted network for real-time semantic expansion. PCSL learns personal relations—such as a family connection—from explicit patterns and repeated co-occurrence. Together they let ARIA learn annotations from prose, cross gaps such as bride to wedding, and adapt later searches to its user. The thesis carefully separates demonstration from proof: these new components were not formally user-tested. WALI needed multiple rules for linguistic alternations; the commonsense corpus remained noisy; cold start, collection scale, and controlled comparison were left open.