Thanks to the answer of @pcko1, I understand that I should use data augmentation to make my model resilient to order of data points.
Clarification after the answer of @Icrmorin :
My problem is actually more complex than just finding bullets. I also need to find title, order text appropriately (think 2-columns PDF), find header/footer, etc...
I am currently trying a rule-based approach, and it was working well so far. But as the number of PDF format I need to handle grow, the complexity of the code grow as well, and I'm reaching a point where PDF formats have opposite features and can't be handled by the same code.
I was hoping the machine learning approach might solve this issue and works well for any format.
According to the answer of @mariq vlahova, it seems there is no name for this kind of task ? Just use LSTM ?
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I'm looking for the name of a task, in order to search more literature about the subject.
The best I can describe this task is given in the title itself...
Basically I have data points with several features each, and I need to classify each of these data points, but not independently. However the order does not (or should not) matter.
For example I have 3 data points
[D1, D2, D3], and I want to classify is as
[True, False, False].
These data points are dependent, ie changing 1 data point might alter the result of other as well :
[D1, D2', D3] might be classified as
[True, True, True].
Also, the order does not matter (that's why I wrote "without the time dimension"):
[D1, D2, D3] is classified as
[True, False, False],
[D2, D3, D1] should be classified as
[False, False, True].
A bit more context... Basically I want to classify PDF content, as being a bullet point or not.
So I want to parse my PDF file, extract chunks of text along with additional information (font size, position, etc...), and classify these chunks as
But we can't classify each chunk independently. Consider the following example :
...End of previous paragraph 1. This is a title Beginning of next paragraph...
In this case,
1. This is a title should not be classified as
bullet. But :
1. This is a title 2. This is a second title 3. This is a third title
In that case,
1. This is a title should be classified as
I need to find literature about this problem but I don't even know the name of the task...