Does anybody know if there is any design document of Text2Onto? I am trying to study its source code. It would be very helpful if there is any documentation about the code.
there isnt much on Text2Onto. Not exactly a design doc but here are a few links you can refer to
Algorithms for Classifying Concepts in Text2Onto
Concept and Instance Extraction Algorithms in Text2Onto
SubcatRelationExtraction Algorithm
Related
I am exploring the method and code to construct the Bayesian network for information retrieval using a data-driven approach. I do find very old papers where the dataset or code are not available. I am new and exploring this field.
Please, if anyone can provide the code link or suggestion of latest papers that can help to give the implementation touch for Bayesian network construction.
Can anyone suggest me a good source to learn?
I am a newbie in ML
As I am a newbie, I have not done anything in this.
This might be an excellent place to start. You can create a new kernel straight from the dataset page, and the data will be ready for you when you enter the kernel. You can also look at other people's kernels who have used that dataset, and I bet you'll find plenty of helpful examples.
You'll get lots of hate for asking this kind of question, since it doesn't fit in S.O. question parameters, but I prefer to be a useful human.
I am trying to Code a genetic algorithm in Matlab but really dont know how it works in images and how to proceed? Is there any basic tutorial that can help me understand how to apply GA on images (starting from 2d to multidimentional images ).
That will be a great help for me.
Thanking everyone in anticipations.
Kind Regards.
For GA you need two things: a fitness function that can evaluate any solution and tell how good it is, and a representation of your solution so that you can do crossover and mutation. Once you have these, you are good to go. I'm not an expert on image processing so I can't help you with that exactly.
Look at the book Essentials of metaheuristics which is a very good resource for start with evolutionary computation (and not only that) in general. It's free.
There is a paper on this subject which you can find at the IEEE library. I believe it solves the problem you vaguely describe.
I am working with OpenCV for a project used for recognition and I had a general question regarding the API and it's terms. I've looked online and couldn't find anything specific to this but I was wondering what the differences were regarding the Discrete Adaboost, Real AdaBoost, LogitBoost, and Gentle AdaBoost. If anyone could direct me to a pros v cons or a general description about these so that I may research which would be useful.
Update
I have added a link to a powerpoint file that goes over the different variations of the Boosting techniques. Hope this hopes someone else out there.
Adaboost powerpoint
Thanks in advance
There isn't really a simple "always use technique X" otherwise there wouldn't be a need for all the others . You really have to understand the details and experiment.
see The opencv discussion and A list of papers and technical summaries
I'm looking for good research papers and tutorials for creation of image processing tool/application which are free. They may not have full-blown description. Papers and tutorials dedicated to a single feature are good enough. Thanks in advance.
There's not any papers for it, but if you take a look at the source code for AForge.NET you will be able to see how several image processing algorithms are implemented.
The project comprises of the core library and a GUI application that lets you try out the filters. So it will give you and idea of what is involved.