Temporal Sequencing of Documents
Michael Gervers Gelila Tilahun
We outline an unsupervised method for temporal rank ordering of sets of
historical documents, namely American State of the Union Addresses and DEEDS, a
corpus of medieval English property transfer documents. Our method relies upon
effectively capturing the gradual change in word usage via a bandwidth estimate
for the non-parametric Generalized Linear Models (Fan, Heckman, and Wand,
1995). The number of possible rank orders needed to search through possible
cost functions related to the bandwidth can be quite large, even for a small
set of documents. We tackle this problem of combinatorial optimization using
the Simulated Annealing algorithm, which allows us to obtain the optimal
document temporal orders. Our rank ordering method significantly improved the
temporal sequencing of both corpora compared to a randomly sequenced baseline.
This unsupervised approach should enable the temporal ordering of undated
document sets.