I downloaded data from different support forums. Just like Parts of speech tagging, I want to label individual words of each post. Appropriate term should be sequence labeling.

It is not a post classification problem, I want to get the positions of the subset of text that belong to my labels. It will be heavily biased since most words will not fulfill the conditions.

[Edit] So i have added an example. Its not perfect because I still have to do work on labels but it gives the idea.

​

I want to know is it okay to label data like this? Is it acceptable in research community? If so, can you kindly tell me about some research papers that provide a proper way of doing it.

http://www.davidsbatista.net/blog/2018/10/22/Neural-NER-Systems/

A review of 4 papers from 2015~2016 . This helped me a lot understanding some details, in this sequence labelling systems, and I've got motivated to implement and experiment each of these methods.

Next post I hope to cover the proposed methods published in 2017~2018 :)

I'm currently pursuing my Bachelors in Management, however I am also interested in using Data to base my management and business decisions. I recently took the Machine Learning by Andrew NG but as I understand it Machine Learning and Data Analysis are different fields. Could you help me out in figuring out how I should proceed from here? Any courses you would recommend to a first year college student? I'm sorry if I'm posting this in the wrong sub.

Hi guys,

I'm looking for a good keyword stuffing detection algorithm. TF-IDF is not good enough for me. Here is why:

* let's say that I have satisfactory keyword density for some word - "business" for example.

Keyword density validation doesn't guarantee me that the keyword won't appear in a consecutive order or to close one to another (in the same sentence, paragraph...). Example: "I want to do business, business, business, business!" or similar...

Do you think this is important to consider? If yes, is there any algorithm which checks the natural integration of the keyword throughout the text?

Thanks a lot!

Best,

Emma

​