Automated Text Analysis Based on Skip-Gram Model for Food Evaluation in Predicting Consumer Acceptance

Algorithm 2

Algorithm for relationship analysis.

Algorithm. Relationship_Analysis(cluster_corpus, taste_words, n)

Input: List cluster_corpus and taste_words of n integers.

//cluster_corpus have three types: “powder soup sauce” cluster words, “noodle” cluster words and

//“soup” cluster words and n is number of words in taste_words

Output: List Result of similarities between cluster corpus and taste words

// Result is a list with taste words and similarities of cluster words

Method:

  Begin

    cluster_vector ← VectorRepresentation(cluster_corpus)

    // converting to representation vector

    for ← 0 to

      taste_vector ← word2vec(taste_words[i])

      similarity ← cosine_similarity(taste_vector, taste) //compute similarity

      Result.insert(taste, similarity)

    end

    return Result

  end