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