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ITECH1400 Fundamentals of Programming Assignment - Sonnets and Doublets, Federation University, Australia
Overview - In this assignment you will have the opportunity to test your Python skills in exploring and manipulating text. Throughout the assignment you are expected to apply the principles of problem solving that we have already discussed in this course.
Learning Outcomes -
1. Identify and use the correct syntax of a common programming language.
2. Recall and use typical programming constructs to design and implement simple software solutions.
3. Explain the importance of programming style concepts (documentation, mnemonic names, indentation).
4. Utilise pseudocode and/or algorithms as a major program design technique.
5. Write and implement a solution algorithm using basic programming constructs.
6. Describe program functionality based on analysis of given program code.
7. Develop self-reliance and judgement in adapting algorithms to diverse contexts.
8. Design and write program solutions to identified problems using accepted design constructs.
Part 1 Sonnets - Background - Your Task - explore possible authorship
Even though we have just become familiar with Python, there are three very simple tests that we can apply to authorship - and we have the means, with lists and strings in Python, to implement them:
1. Count the occurrences of each letter4 in the text.
2. Print the number of one-letter, two-letter, three-letter words and so on.
3. Print the number of occurrences of each different word in the text.
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Solution - Pseudo Code
o for each file in dir
append file to file_list
o return file_list
for each file in file_list
for each line in file
for each word in line
increment counter of len
for each letter in word
increment counter of letter
add word to bag_of_words
merge to form a single feature vector
append to features
o labels = K-means++(features)
o print labels
Brief description of Pseudo code : The sonnets are read one by one from the files serially. Three types of features are extracted from each file, number of occurence of each letter, number of one-letter,two-letter, three-letter ... words, bag of words features. These features are combined to form one single feature vector for each sonnet. Then we have used K-means++ clustering with number of clusters set to 3 to group the documents according to authorship.
Discussion: The problem of identifying authorship is an unsupervised problem. For the purpose of this problem there are various unsupervised algorithms like Clustering available. Clustering itself is a huge area. For this problem we choose K-means since it works fairly well. We experimented with hierarchical as well as spectral clustering but it was not giving satisfactory results. A screenshot of sample run is given below which shows the authorship of each of the sonnets (documents).
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Part 2: Doublets
Doublets (or word ladders) are often found in magazines and newspapers together with cryptic crosswords and other puzzles. The idea is very simple: you might be given two words - often they are antonyms - and your task is to create a ladder of words with these two words at the top and bottom of the ladder.
o read_file("wordlist.txt") // creates a dictionary of words
o Queue = [head]
o for word in head of Queue
scan the words in dictionary for words adjacent to current word.
Add to word ladder
Push word in Queue
o for word in word ladder
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Brief description of Pseudo code and Discussion: We read the words from the file WordList.txt and use a special case of Minimum Spanning Tree when each edge weight is one i.e. Breadth First Search which is implemented using a Queue to find the shortest length word chain between the given head word and tail word.
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