Computer Science Term Paper Ideas?

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SUMMARY

This forum discussion centers on potential term paper topics in computer science, specifically for Visual Basic. Key suggestions include "Sorting Efficiency" focusing on algorithms like Bubble, Shell, Quick, Heap, and Radix; "Trees" covering balancing, branching, traversing, and sorting; "Artificial Intelligence" with an emphasis on data mining, expert systems, and neural networks; and "Data Compression" involving matrix decomposition and pattern recognition. Participants recommend data compression as a practical and interesting topic due to its experimental applications, while also discussing the theoretical limitations of AI.

PREREQUISITES
  • Understanding of algorithm complexity and Big O notation
  • Familiarity with data structures, particularly trees
  • Knowledge of artificial intelligence concepts, including neural networks
  • Basic principles of data compression techniques
NEXT STEPS
  • Research "Data Compression Algorithms" and download source code for practical experimentation
  • Explore "Neural Networks" and their applications in AI
  • Study "Sorting Algorithms" and their efficiency comparisons
  • Investigate "Turing Machines" and their theoretical implications in computer science
USEFUL FOR

Students in computer science, particularly those writing term papers, as well as educators and researchers interested in algorithm efficiency, data structures, artificial intelligence, and data compression techniques.

SDNess
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For visual basic I need to write a term paper on any topic in computer science that is in depth enough to last four pages. Any interesting ideas?
 
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Here are some ideas:

1. Sorting Effienciency (Big O) - Compare Bubble, shell, quick, heap, radix, etc

2. Trees - Balancing, Branching, Traversing, Sorting, etc

3. Artificial Intellegence - Data Mining, Expert Systems, Neural Networks

4. Data Compression - Matrix Decomposition, Pattern Recognition.
 
Could you give a little summary for each of the topics in 3 and 4?
 
Originally posted by SDNess
Could you give a little summary for each of the topics in 3 and 4?

O come on, can't you put in atleast a little effort trying to look these things up on google or something.

Here's a good intro to data compression, both lossy and lossless:

http://www.stanford.edu/~udara/SOCO/overview/index.htm

I would suggest doing the paper on data compression. Not only is it a very interesting field, but it has many application that you can actually experiment with.
Download the sourcecode for various compression algorthims and test them out.

Artificial Intelligence is only good if you want to talk about theory and nothing else. You can't really test out many things, as the algorithm complexity escalates at a tremendous rate.
 
Last edited by a moderator:
Originally posted by dduardo
Artificial Intelligence is only good if you want to talk about theory and nothing else. You can't really test out many things, as the algorithm complexity escalates at a tremendous rate.

Not so. There are plenty of practical, implementable topics in AI. Neural networks of a reasonable size are certainly testable. Other topics such as evolutionary computation (eg. genetic algorithms), vision, and planning & constraint satisfaction are not limited to theory, as well.
 
Alright, thanks.

I'm going with Data compression or quantum computing I think.
 
Originally posted by SDNess
Alright, thanks.

I'm going with Data compression or quantum computing I think.

Hmm...that's good, if you want you can also try Automata, or Turing Machine :)
 
@moni: could you please tell abt how i can do a paper on turing machine ?
 
Um, Moni made that post six and a half years ago.

As for "how do I write a paper on X", whether X is Turing machines or anything else, I would say the general procedure is to first do a Web search to find out what material is out there in general. I would avoid using Web pages as actual sources for your paper, unless you find a site that is clearly authoritative (i.e. written by an identifiable person who is an actually an authority on the subject, and is referred to by many other sites). Instead, look for references to books, or articles in professional journals, and then find them in a library. (Some journals do post articles online.)

Of course, what kind of sources are acceptable depends on what level you are working at. A paper for a high school class is one thing. A paper for a university computer science course is another (more rigorous) thing.
 

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