Is there a better way to improve the complexity of a algorithm that includes multiple arrays in an object

Question

I am working on a project that is using the google cloud speech-to-text api. The result from the api returns an object that has multiple arrays of transcript and each array contains an array for each word and their properties, which is an object. I want to filter through every words in the transcript, and see if it matches another array of words I want to filter out.

Here's a simplified example if it sounds confusing.

resultFromApi = {
   results:[
      [{word:"hello", startTime:"00:00:00",endTime:"00:00:02"},...],
      [{word:"world", startTime:"00:00:02",endTime:"00:00:04"},...]
   ]
}
wordsToFilter = ["hello", "there", "this", "is", "a", "test"]

My question is, is there a faster way other than something like this?

resultFromApi.results.forEach((result) => {
   result.forEach((e) => {
      if(wordsToFilter.includes(e.word)){
         ...
      }
   })
});

Edit: Syntax problem

Yes, I edited it. Sorry for the inconvenience.

hkisthebest
– hkisthebest

2019-11-29 07:43:43 +00:00
Commented Nov 29, 2019 at 7:43 — hkisthebest
– hkisthebest, Commented Nov 29, 2019 at 7:43

CertainPerformance · Accepted Answer · 2019-11-29 07:43:19Z

2

At the minimum, one thing you can do to improve the computational complexity of the code would be to change the wordsToFilter array to a Set. The complexity of Array.prototype.includes is O(n), but the complexity of Set.prototype.has is O(1). So if

if(wordsToFilter.includes(e.word)){

is your current code, and it works for you, you can change the code to

const wordsToFilter = new Set(["hello", "there", "this", "is", "a", "test"]);
// ...
if(wordsToFilter.has(e.word)){

to decrease the computational complexity by a factor of n, from O(n^3) overall to O(n^2).

You have an array of arrays of objects, and you need to iterate over all objects, so you have to use a nested loop to iterate, which is O(n ^ 2), so after that, there's no way to fundamentally improve the computational complexity.

edited Nov 29, 2019 at 7:43

answered Nov 29, 2019 at 7:28

CertainPerformance

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1 Comment

hkisthebest Over a year ago

Thanks for answering, I will take a look into Set, and how it achieves O(1) when searching.

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