Keyword Analysis For Reviews

No algorithm description given

This algorithm can be used to identify the important terms that differentiate good reviews from bad reviews. It is based on tf-idf scoring (a version of which is implemented for general multiple-document keyword identification in /nlp/KeywordsForDocumentSet ), but unlike these, it calculates term frequencies for the entire set of reviews sharing a given rating. It takes as input The set of reviews (as a String[]) The ratings of each review (as Integer[]). The i-th review in the first argument corresponds to the i-th rating in the second. The number of rating options (general 5, for a 1-5 star system) The maximum number of keywords to return for each rating. It returns the set of keywords corresponding to weighting in order, from lowest rating to highest rating. Terms that appear frequently across all rating classes will be assigned low weight and thus will not likely appear as keywords.

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This algorithm has permission to call other algorithms which may incur separate royalty and usage costs.

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Calls other algorithms

This algorithm has permission to call other algorithms. This allows an algorithm to compose sophisticated functionality using other algorithms as building blocks, however it also carries the potential of incurring additional royalty and usage costs from any algorithm that it calls.


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1. Type your input

2. See the result

Running algorithm...

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/KeywordAnalysisForReviews/0.1.0
View cURL Docs
algo auth
# Enter API Key: YOUR_API_KEY
algo run algo://nlp/KeywordAnalysisForReviews/0.1.0 -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/KeywordAnalysisForReviews/0.1.0");
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/KeywordAnalysisForReviews/0.1.0")
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/KeywordAnalysisForReviews/0.1.0")
           .pipe(input)
           .then(function(output) {
             console.log(output);
           });
View Javascript Docs
var input = {{input | formatInput:"javascript"}};
Algorithmia.client("YOUR_API_KEY")
           .algo("algo://nlp/KeywordAnalysisForReviews/0.1.0")
           .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/KeywordAnalysisForReviews/0.1.0')
print algo.pipe(input)
View Python Docs
library(algorithmia)

input <- {{input | formatInput:"r"}}
client <- getAlgorithmiaClient("YOUR_API_KEY")
algo <- client$algo("nlp/KeywordAnalysisForReviews/0.1.0")
result <- algo$pipe(input)$result
print(result)
View R Docs
require 'algorithmia'

input = {{input | formatInput:"ruby"}}
client = Algorithmia.client('YOUR_API_KEY')
algo = client.algo('nlp/KeywordAnalysisForReviews/0.1.0')
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/KeywordAnalysisForReviews/0.1.0');
let response = algo.pipe(input);
View Rust Docs
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