Text analysis:
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* Brief description and AI targeted area:

In this project, you will have to deal with a very practical problem, for which you will have to determine the practical applications. 

Here is the problem you are given. You know you have access to thousands of text documents. For a subset of them (but by far not the half of the total number of text files), you know you like them, and for another subset of the documents, you know you dislike them. There are documents which you don't whether you like them or not. But of course you don't want to read all of them to figure out which ones you like and which others you don't, in particular because you don't want to waste time reading texts you don't like.

So instead, you would like to have an automated tool that would tell you which text you are likely to like, and which ones you should avoid. Your goal in this project is to design and implement such a tool.

This project overlaps several sub-domains of AI that you will have to point out. 

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* Description of the objectives and tasks:

By the end of this project, you will have:
- describe in all details the tool you plan to implement, and justify why it will do what it is 	supposed to;
- determine which sub-domains of AI can help in this project;
- explained how such a tool can be useful in real-world applications, and justify why; 
- written a description of your system and its applications: to be handed out to all students in 	 the class; * this document should be ready by the end of week 4 of the project timeline;
- implement your tool (in the programming language of your choice, and you will have to 
	motivate your choice);
- run experiments (justify your test data) and report / analyze the results.

You will also have to write a general report in which you will include:
- an introduction: presenting the problem you plan to address, and explain how you will tackle 		it; explain how it is related to AI and what specific area it is related to;
	include your tutorial about expert systems here;
- the description of your team: names of the students, tasks assignment (contribution of each 		one), timeline of your work;
- the description of your system:
	* which method(s) you used and how you implemented it (justify your choice and make your 		descriptions clear)
	* why it is expected to be efficient;
	* how your system can evolve later; how what you implemented is AI;
- the report of your testing your system:
	* description of your testing, report and analysis of the results;
	* does your system meet your expectations? why?
- a discussion of what went wrong and why: self-criticism;
- a conclusion: synthesis of your work, future work directions (what you would do if you were 		given more time on your project).

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