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| import re | |
| from colorama import Fore | |
| problem_pattern = r"(problem|issue|challenge)" | |
| importance_pattern = r"\b(important|challenging|crucial|critical|vital|significant)\b" | |
| interesting_pattern = r"\b(interesting|fascinating|intriguing|exciting)\b" | |
| novel_pattern = r"\b(novel|new|original|innovative|creative)\b" | |
| model_pattern = r"(model|architecture|method|approach|framework)" | |
| experiment_pattern =r"\b(evaluate|evaluation|comparison|result|experiment[s])\b|\b(analysis|analyses)\b" | |
| result_pattern = r"\b(result|performance|metric|score)\b" | |
| insight_pattern = r"\b(insight|observation|finding|trend)\b" | |
| limitation_pattern = r"(limitation|drawback|weakness|challenge)" | |
| scalability_pattern = r"\b(complexity|scalability|scalable)\b" | |
| real_world_pattern = r"realistic|real\-world|practical" | |
| theoretical_pattern = r"\b(math|theoretical|justification|justify|foundation|theory)\b" | |
| def text_match_problem(text): | |
| """Regex patterns to search for problem-related and importance-related keywords""" | |
| # Check if both patterns are found in the text | |
| return re.search(problem_pattern, text, re.IGNORECASE) and (re.search(importance_pattern, text, re.IGNORECASE) | |
| or re.search(interesting_pattern, text, re.IGNORECASE)) | |
| def text_match_dataset(text): | |
| """ | |
| Check if the strengths mentioned by reviewers contains the word "dataset" or "data set". | |
| """ | |
| return re.search(r"\b(dataset|data set)\b", text, re.IGNORECASE) | |
| def text_match_model(text): | |
| """ | |
| Check if the strengths mentioned by reviewers contains the word "model". | |
| """ | |
| return re.search(model_pattern, text, re.IGNORECASE) | |
| def text_match_experiment(text): | |
| """ | |
| Check if the strengths mentioned by reviewers contains the word "experiment". | |
| """ | |
| return re.search(experiment_pattern, text, re.IGNORECASE) or re.search(result_pattern, text, re.IGNORECASE) | |
| def text_match_real_world(text): | |
| """ | |
| Check if the strengths mentioned by reviewers contains the word "model". | |
| """ | |
| return re.search(real_world_pattern, text, re.IGNORECASE) | |
| def text_match_theoretical(text): | |
| """ | |
| Check if the strengths mentioned by reviewers are related to theoretical analysis / foundation. | |
| """ | |
| return re.search(theoretical_pattern, text, re.IGNORECASE) | |
| def text_match_scalability(text): | |
| """ | |
| Check if the strengths mentioned by reviewers are related to scalability or time/space complexity. | |
| """ | |
| return re.search(scalability_pattern, text, re.IGNORECASE) | |
| def match_strengths(text): | |
| """ | |
| Check if the strengths mentioned by reviewers contains the word "model". | |
| """ | |
| for category, f in {"problem": text_match_problem, | |
| "dataset": text_match_dataset, | |
| "model": text_match_model, | |
| "limitation": text_match_limitation, | |
| "experiment": text_match_experiment, | |
| "theoretical-analysis": text_match_theoretical, | |
| "scalability": text_match_scalability, | |
| }.items(): | |
| if f(text): | |
| return category | |
| print( | |
| Fore.RED | |
| + f"No category found for weaknesses: {text}" | |
| + Fore.BLACK | |
| ) | |
| def match_weaknesses(text): | |
| for category, f in {"problem": text_match_problem, | |
| "dataset": text_match_dataset, | |
| "model": text_match_model, | |
| "limitation": text_match_limitation, | |
| "experiment": text_match_experiment, | |
| "real-world": text_match_real_world, | |
| "theoretical-analysis": text_match_theoretical, | |
| "scalability": text_match_scalability, | |
| }: | |
| if f(text): | |
| return category | |
| print( | |
| Fore.RED | |
| + f"No category found for weaknesses: {text}" | |
| + Fore.BLACK | |
| ) | |
| return None | |
| raise ValueError(f"No category found for weaknesses: {text}") | |
| def text_match_limitation(text): | |
| """ | |
| Check if the strengths mentioned by reviewers contains the word "model". | |
| """ | |
| return re.search(limitation_pattern, text, re.IGNORECASE) |