# naive_approach This directory contains the functions necessary to run the Naive Approach. Prerequisites: * the file [emoji_descriptions_preprocessed.csv](../Tools/emoji_descriptions_preprocessed.csv) has to be located in the specified folder [../Tools](../Tools) * pandas has to be installed For testing, import [naive_approach.py](naive_approach.py) and execute the following commands: 1. `prepareData(stem, lower)` * preprocesses the emoji descriptions and returns a dictionary with the indexed emojis * parameters: * `stem`: Apply stemming (default=`True`) * `lower`: Apply lowercasing (default=`True`) 2. `predict(sentence, lookup, emojis_to_consider, criteria, lang, embeddings, n=10, t=0.9)` * evaluates an input sentence and returns a list of predicted emojis * parameters: * `sentence`: Input sentence (required parameter) * `lookup`: dictionary with emoji data (return value of prepareData, required parameter) * `emojis_to_consider`: set of emojis to include in prediction, or `"all"` (default=`"all"`) * `criteria`: criteria to evaluate the values of the description - message matching. * options: `"sum"`, `"mean"`, `"max_val"`, `"threshold"` (default: `"threshold"`) * `lang`: language to use (default: "eng") * `embeddings`: word embeddings * options: `"wordnet"`, `"word2Vec"`, `"fastText"`, default: `"wordnet"` * `n`: number of top ranked emojis to return (default=`10`) * `t`: threshold for the `"threshold"` criteria (default=`0.9`)