
## 1.7 Our Platform For Analysis Of Semantics Correspondence Analysis Supports The Following:

- analysis of multivariate, mixed numerical/symbolic data - web of interrelationships
- evolution of relationships over time Correspondence Analysis is in practice *a tale of three metrics* [7]. The analysis is based on embedding a cloud of points from a space governed by one metric into another. Furthermore the cloud offers vantage points of both observables and their characterizations, so - in the case of film script - for any one of the metrics we can effortlessly pass between the space of filmscript scenes and attribute set. The three metrics are as follows.

- Chi squared, χ 2, metric - appropriate for profiles of frequencies of occurrence.

- Euclidean metric, for visualization, and for static context.

- Ultrametric, for hierarchic relations and, as we use it in this work, for dynamic context.
In the analysis of semantics, we distinguish two separate aspects.

1. Context - the collection of all interrelationships.

- The Euclidean distance makes a lot of sense when the population is homogeneous.

- All interrelationships together provide context, relativities - and hence meaning.
2. Hierarchy tracks anomaly.

- Ultrametric distance makes a lot of sense when the observables are heterogeneous, discontinuous.

- The latter is especially useful for determining: anomalous, atypical, innovative cases.

## 2 Deeper Look At Semantics Of Casablanca 2.1 Text Data Mining

The Casablanca script has 77 successive scenes. In total there are 6710 words in these scenes. We define words as consisting of at least two letters. Punctuation is first removed. All upper case is set to lower case. We use from now on all words. We analyze frequencies of occurrence of words in scenes, so the input is a matrix crossing scenes by words.