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|  | # naive_approach # | ||||||
|  |  | ||||||
|  | This directory contains the functions necessary to run the Naive Approach. | ||||||
|  |  | ||||||
|  | Prerequisites: | ||||||
|  | 	# the file "emoji_descriptions_preprocessed.csv" has to be located in the specified folder ("../Tools") | ||||||
|  | 	# pandas has to be installed | ||||||
|  |  | ||||||
|  | For testing, import 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) | ||||||
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