পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| ভাষা শনাক্তকরণ (LID)× | অনুভূতি বিশ্লেষণ× | |
|---|---|---|
| ক্ষেত্র | টেক্সট খনন | টেক্সট খনন |
| পরিবার | Process / pipeline | Process / pipeline |
| উদ্ভবের বছর | — | — |
| প্রবর্তক | — | — |
| ধরন | NLP text-classification task | NLP text-classification task |
| মৌলিক উৎস≠ | Lui, M. & Baldwin, T. (2012). langid.py: An Off-the-shelf Language Identification Tool. Proceedings of the ACL 2012 System Demonstrations. link ↗ | Pang, B. & Lee, L. (2008). Opinion Mining and Sentiment Analysis. Foundations and Trends in Information Retrieval, 2(1-2), 1-135. DOI ↗ |
| অপর নাম | language detection, LID, Dil Tanımlama (Language Identification) | opinion mining, polarity detection, duygu analizi |
| সম্পর্কিত≠ | 4 | 3 |
| সারসংক্ষেপ≠ | Language identification is a natural-language-processing task that automatically detects which language a piece of text is written in. Building on off-the-shelf tools such as langid.py (Lui & Baldwin, 2012) and the efficient classifiers of Joulin et al. (2017), it is widely used to preprocess and filter multilingual data sets. | Sentiment analysis, also called opinion mining, is a natural-language-processing task that detects the emotional tone of text — typically classifying it as positive, negative, or neutral. It turns unstructured opinion text into structured, quantifiable polarity signals using one of three families of approaches: sentiment lexicons, trained machine-learning classifiers, or pretrained transformer models. |
| ScholarGateডেটাসেট ↗ |
|
|