Each element should be followed by the punctuation mark shown here. Earlier editions of the handbook included the place of publication and required different punctuation such as journal editions in parentheses and colons after issue numbers. In the current version, punctuation is simpler only commas and periods separate the elementsand information about the source is kept to the basics. End this element with a period.
Of primary importance is the 'synopses' list; 'titles' is mostly used for labeling purposes. Stop words are words like "a", "the", or "in" which don't convey significant meaning. I'm sure there are much better explanations of this out there. Stemming is just the process of breaking a word down into its root.
Guess what, I do want to do that! The benefit of this is it provides an efficient way to look up a stem and return a full token. The downside here is that stems to tokens are one to many: For my purposes this is fine--I'm perfectly happy returning the first token associated with the stem I need to look up.
I could clean it up, but there are only items in the DataFrame which isn't huge overhead in looking up a stemmed word based on the stem-index.
To get a Tf-idf matrix, first count word occurrences by document. This is transformed into a document-term matrix dtm. This is also just called a term frequency matrix. An example of a dtm is here at right.
Then apply the term frequency-inverse document frequency weighting: A couple things to note about the parameters I define below: Here I pass 0. Cosine similarity is measured against the tf-idf matrix and can be used to generate a measure of similarity between each document and the other documents in the corpus each synopsis among the synopses.
Subtracting it from 1 provides cosine distance which I will use for plotting on a euclidean 2-dimensional plane. Note that with dist it is possible to evaluate the similarity of any two or more synopses.
Using the tf-idf matrix, you can run a slew of clustering algorithms to better understand the hidden structure within the synopses. I first chose k-means. K-means initializes with a pre-determined number of clusters I chose 5.
Each observation is assigned to a cluster cluster assignment so as to minimize the within cluster sum of squares. Next, the mean of the clustered observations is calculated and used as the new cluster centroid. Then, observations are reassigned to clusters and centroids recalculated in an iterative process until the algorithm reaches convergence.
I found it took several runs for the algorithm to converge a global optimum as k-means is susceptible to reaching local optima. I convert this dictionary to a Pandas DataFrame for easy access.
I'm a huge fan of Pandas and recommend taking a look at some of its awesome functionality which I'll use below, but not describe in a ton of detail. This gives a good sense of the main topic of the cluster. Casablanca, Psycho, Sunset Blvd.
I won't pretend I know a ton about MDS, but it was useful for this purpose. Another option would be to use principal component analysis. First I define some dictionaries for going from cluster number to color and to cluster name.
I based the cluster names off the words that were closest to each cluster centroid. I won't get into too much detail about the matplotlib plot, but I tried to provide some helpful commenting.The Maltese Falcon () is one of the most popular and best classic detective mysteries ever made, and many film historians consider it the first in the dark film noir genre in Hollywood.
It leaves the audience with a distinctly down-beat conclusion and bitter taste. The Maltese Falcon has one plot—find the dang Falcon. That doesn't mean it's a simple one, though. With characters double-crossing and backstabbing one another (if you double-cross and backstab.
Gahan of Gathol wore a jewel-encrusted harness in the beginning of Edgar Rice Burroughs's Chessmen of Mars.; The eponymous Macguffin of The Maltese Falcon (and its real-life inspiration, the Kniphausen Hawk) is a gem-covered statue of a falcon that was later covered with black enamel to hide its value.; In Robert E.
Howard's Conan . Today, Peregrine Falcons are making a comeback in New York City. We currently know of 16 falcon couples, or 32 falcons total, that live year-round in unique places throughout the City such as on top of bridges, church steeples and high-rise buildings. While this comeback has been years in the making.
A Better Appreciation.
Why do some stories last forever while others fade the moment the curtain falls? Performance and presentation certainly plays a role, but in the final analysis it is the existence of an identifiable Storyform that truly determines the lifespan of a particular work of fiction..
A Storyform maintains the thematic explorations of a story. The Purdue University Online Writing Lab serves writers from around the world and the Purdue University Writing Lab helps writers on Purdue's campus.