That’s neat. But what if your Copier is only black-and-white, and your Printer can handle color, too? Isn’t Printer in t

There is a reason why similar results are returned… they best represent the document! If we were to diversify the keywords/keyphrases then they are less likely to represent the document well as a collective.

The more you use inheritance, the more maintenance you potentially have to do. So even though reusing code seems very efficient in the short term, it can get costly in the long run.

Except for the fact that this class may actually be a subclass of another class, so now you need to include the parent class too. Then you realize that the parent class depends on other classes as well, and you end up including heaps of code.

It seems that we get keyphrases instead of keywords now! These keyphrases, by themselves, seem to nicely represent the document. However, I am not happy that all keyphrases are so similar to each other.

Well, you can’t do it. At least not in an elegant way. Consider for example the class Copier. (I borrowed this example, as well as some info about the problems presented here, from Charles Scalfani’s viral story Goodbye, Object Oriented Programming.) A copier scans the content of a document and prints it on an empty sheet. So should it be the subclass of Scanner, or of Printer?

It can corrupt your entire code. You might not even have touched it. But one day your project works like a charm, the next day it doesn’t because somebody changed a minor detail in the base class that ends up being crucial for your project.

The maximum sum distance between pairs of data is defined as the pairs of data for which the distance between them is maximized. In our case, we want to maximize the candidate similarity to the document whilst minimizing the similarity between candidates.

In the diamond problem, the question was which class Copier is a subclass of. But I lied to you — there is a neat solution. Let Copier be the parent class, and Scanner and Printer be subclasses that only inherit a subset of the properties. Problem fixed!

Since transformer models have a token limit, you might run into some errors when inputting large documents. In that case, you could consider splitting up your document into paragraphs and mean pooling (taking the average of) the resulting vectors.

Inheritance is this cute little thing where we can take properties of one class and transfer it to others. But what if you want to mix the properties of two different classes?

NOTE: There are many pre-trained BERT-based models that you can use for keyword extraction. However, I would advise you to use either distilbert — base-nli-stsb-mean-tokens or xlm-r-distilroberta-base-paraphase-v1 as they have shown great performance in semantic similarity and paraphrase identification respectively.

The problem with object-oriented languages is they’ve got all this implicit environment that they carry around with them. You wanted a banana but what you got was a gorilla holding the banana and the entire jungle.

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to be concentrated in specific cities, which might require a move to get into a new industry. If that’s not an option, there may be a remote opportunity in another industry. 2020 may be a hot mess, but if it’s brought us anything positive, telework options are definitely on the list.

In the final step, we want to find the candidates that are most similar to the document. We assume that the most similar candidates to the document are good keywords/keyphrases for representing the document.

“Well I’ve done a Vipassana silent retreat. You go to this remote place with a group of people, and you meditate everyday, in total silence, for hours at a time, for 10 days straight.”