📔 Trade paperback detection 1st draft

src/client/shared/utils/tradepaperback.utils.ts

@@ -1,36 +1,20 @@
-const TrainingSet = require("./trainingData.json");
-const natural = require("natural");
-const BrainJs = require("brain.js");
+import { compact, isNil } from "lodash";
 
-function buildWordDictionary(trainingData) {
-  const tokenisedArray = trainingData.map((item) => {
-    const tokens = item.phrase.split(" ");
-    return tokens.map((token) => natural.PorterStemmer.stem(token));
-  });
-
-  const flattenedArray = [].concat.apply([], tokenisedArray);
-  return flattenedArray.filter((item, pos, self) => self.indexOf(item) == pos);
-}
-
-const dictionary = buildWordDictionary(TrainingSet);
-
-function encode(phrase) {
-  const phraseTokens = phrase.split(" ");
-  const encodedPhrase = dictionary.map((word) =>
-    phraseTokens.includes(word) ? 1 : 0,
-  );
-
-  return encodedPhrase;
-}
-
-const encodedTrainingSet = TrainingSet.map((dataSet) => {
-  const encodedValue = encode(dataSet.phrase);
-  return { input: encodedValue, output: dataSet.result };
-});
-
-const network = new BrainJs.NeuralNetwork();
-network.train(encodedTrainingSet);
-
-const encoded = encode("Im so happy to have cake");
-console.log(network.run(encoded));
-export const detectTradePaperbacks = (deck: string): any => {};
+export const detectTradePaperbacks = (deck): any => {
+  const paperback = [
+    /((trade)?\s?(paperback)|(tpb))/gim, // https://regex101.com/r/FhuowT/1
+    /(hard\s?cover)\s?(collect((ion)|(ed)|(ing)))/gim, //https://regex101.com/r/eFJVRM/1
+    /(collected\s?editions)/gim, // https://regex101.com/r/40pAm5/1
+  ];
+  const matches = paperback
+    .map((regex) => {
+      return deck.match(regex);
+    })
+    .map((item) => {
+      if (item !== undefined) {
+        return item;
+      }
+    });
+  console.log(compact(matches));
+  return compact(matches);
+};