What if the political spheres can see close to the problematic of the community with a magnified glass and tackle with success these issues.
Wordspeech software is trying to show how we can embed resources from every source, corner recorded in datasets from topics such as community, economics, infracstruscture, health, finance and defense.
Helping the future of speech to be acculturated, intelligent, assertive, dynamic and more important that could touch million of people with a successful speech.
Wordspeech helps to embed this source of information fast and intelligent with the aid of historical data.
For this project we have take one of the most successful topics in political history in Australia Private Health Cover and on of the best speech that made this in today time a success idea for the Australia community.
Matching resources and algorithms for a clever result. We have used classical approach methods such as algorithms like Karatsuba to divide a problem into three problems of half the size.
The recursive structure of Karatsuba lends itself to a simple detection. But about is we could implement one of the powerful algorithms in the world to do this even better.
PageRank algorithm works fine for this, it could work continuously with machine learning. The number and quality of words frequently used in political speech recorded embed with the datasets Australia Research Data Commons can offer but not limited with other arches such articles.
I believe for this project we have simplified all context and demonstrate the possibilities of good algorithmic methods and aid of well recorded information to produce results not a solution.
Description of Use
This dataset is been used as vocabulary memory for this project.
The user select the topic e.g. Health in the tree directory and the widget shows a vocubulary in the fiels selected by the user as result
"Health Policy Economic Outcomes"
In times of crisis words can inspire and unite us, but they can also provoke division and conflict. How has the language of Australia’s leaders changed over time? How can we represent these changes in public discourse within a historical timeline?