Keywords For Document Set

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Given a set of documents (represented as a List<String>) and a maximum number of keywords to return per document, returns a list, each entry of which contains the most relevant (as measured by weight) keywords for the respective  document.  How it works: In a given document, a keyword receives a higher weight for the number of times it appears in the document and a lower weight for the number of other documents it appears in. This is a simple implementation of  tf-idf scoring . Input format: A set of documents (represented as a List<String>) and a maximum number of keywords to return per document: e.g. [["word1 word2 word3", "word4 word5", "word2 word5"], 2] Output format: An ordered list (with respect to the input order) with keywords that are the most relevant for each document.

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1. Type your input

2. See the result

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3. Use this algorithm

curl -X POST -d '{{input | formatInput:"curl"}}' -H 'Content-Type: application/json' -H 'Authorization: Simple YOUR_API_KEY' https://api.algorithmia.com/v1/algo/nlp/KeywordsForDocumentSet/0.1.7
View cURL Docs
algo auth
# Enter API Key: YOUR_API_KEY
algo run algo://nlp/KeywordsForDocumentSet/0.1.7 -d '{{input | formatInput:"cli"}}'
View CLI Docs
import com.algorithmia.*;
import com.algorithmia.algo.*;

String input = "{{input | formatInput:"java"}}";
AlgorithmiaClient client = Algorithmia.client("YOUR_API_KEY");
Algorithm algo = client.algo("algo://nlp/KeywordsForDocumentSet/0.1.7");
AlgoResponse result = algo.pipeJson(input);
System.out.println(result.asJsonString());
View Java Docs
import com.algorithmia._
import com.algorithmia.algo._

val input = {{input | formatInput:"scala"}}
val client = Algorithmia.client("YOUR_API_KEY")
val algo = client.algo("algo://nlp/KeywordsForDocumentSet/0.1.7")
val result = algo.pipeJson(input)
System.out.println(result.asJsonString)
View Scala Docs
var input = {{input | formatInput:"javascript"}};
Algorithmia.client("YOUR_API_KEY")
           .algo("algo://nlp/KeywordsForDocumentSet/0.1.7")
           .pipe(input)
           .then(function(output) {
             console.log(output);
           });
View Javascript Docs
var input = {{input | formatInput:"javascript"}};
Algorithmia.client("YOUR_API_KEY")
           .algo("algo://nlp/KeywordsForDocumentSet/0.1.7")
           .pipe(input)
           .then(function(response) {
             console.log(response.get());
           });
View NodeJS Docs
import Algorithmia

input = {{input | formatInput:"python"}}
client = Algorithmia.client('YOUR_API_KEY')
algo = client.algo('nlp/KeywordsForDocumentSet/0.1.7')
print algo.pipe(input)
View Python Docs
library(algorithmia)

input <- {{input | formatInput:"r"}}
client <- getAlgorithmiaClient("YOUR_API_KEY")
algo <- client$algo("nlp/KeywordsForDocumentSet/0.1.7")
result <- algo$pipe(input)$result
print(result)
View R Docs
require 'algorithmia'

input = {{input | formatInput:"ruby"}}
client = Algorithmia.client('YOUR_API_KEY')
algo = client.algo('nlp/KeywordsForDocumentSet/0.1.7')
puts algo.pipe(input).result
View Ruby Docs
use algorithmia::*;

let input = {{input | formatInput:"rust"}};
let client = Algorithmia::client("YOUR_API_KEY");
let algo = client.algo("nlp/KeywordsForDocumentSet/0.1.7");
let response = algo.pipe(input);
View Rust Docs
import Algorithmia

let input = "{{input | formatInput:"swift"}}";
let client = Algorithmia.client(simpleKey: "YOUR_API_KEY")
let algo = client.algo(algoUri: "nlp/KeywordsForDocumentSet/0.1.7") { resp, error in
  print(resp)
}
View Swift Docs
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