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صفحه اصلی
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اولین همایش بین المللی هوش مصنوعی
Computational Complexity of Sentiment Analysis Algorithms in Natural Language Processing
نویسندگان :
Kiana Karimifard
1
Mohammad Ghasemzadeh
2
1- یزد
2- یزد
کلمات کلیدی :
Sentiment Analysis،Computational Complexity،Machine Learning
چکیده :
The main focus of this project is to investigate the computational complexity of sentiment analysis algorithms in the field of Natural language processing. Sentiment analysis is an important classification task that aims to identify whether user opinions about a specific topic are positive, negative, or neutral. With various classification methods available, different algorithms have been developed, each of which involve various resource requirements. The main objective of this research is to compare and evaluate the computational complexity of different sentiment analysis algorithms and to suggest optimization strategies for improving their performance under different conditions. The results of this project can assist in selecting more efficient algorithms and enhancing the performance of sentiment analysis systems.
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بیشتر
ثمین همایش، سامانه مدیریت کنفرانس ها و جشنواره ها - نگارش 41.1.5