CSci4152 Student Presentations
CSci4152: Statistical Natural Language Processing
Student Presentations
Comparison of algorithms for keyphrase extraction
by
Atreya Basu
In my project I compare; Microsoft Word's AutoSummarize feature, the NRC's
Extractor algorithm, Teranet Software's Metabot program, the KEA program
from the University of Waikato, and an algorithm of my own, to see how they
perform based on the following three measures: Precision, recall and
F-measure. The algorithms are tested with the text of two engineering
books, and marked by its author.
Discovering Rules For The Use Of Locative Prepositions
by
Matthew Hogg
My project will be an attempt to discover instances of locative
prepositions (on, at, in) and the words they reference. I will be
restricted to the prepostion "on" in specific cases. Once the table of
occurences of "on" is found, I will use similarity measures described in
the book to classify these occurences of "on". Possible applications of
this knowledge are in developing a less naive translation system where
locative prepositions are involved.
Application of Non-Linear Auto-Associative
Neural Networks to Discovering Word Similarity
by
Chris Maxwell
The objective of my project is to explore the effect of a non-linear
transfer function on the efficacy of an Autoassociative Neural Network
in discovering similarities in words. The original inspiration was
that Latent Semantic Indexing, equivalent in some ways to a linear
autoassociater, can be thought to squeeze similar words together to achieve
its results, hence brief mention will be made of this concept also.
Word Sense Disambiguation (and Synonym Retrieval) Using WordNet
by
Adam Nickerson
The WordNet API is used to implement a dictionary-based word sense
disambigution method (Lesk, 86). The goal of this project is to obtain a
faster synonym retrieval time than previous work (MacCara, 99) by
directly accessing the WordNet API rather than calling the command line
version. Such dictionary-based methods often yield mediocre results;
however, if they can be preformed quick enough, they may make a
worthwhile contribution to a combined method approach (Stevenson &
Wilks, 99)