| Model | P | R | F1 | |---------------------------|--------|--------|--------| | RAKE | 0.42 | 0.35 | 0.38 | | mBERT NER | 0.65 | 0.58 | 0.61 | | YAKE (multi) | 0.51 | 0.48 | 0.49 | | Proposed Hybrid | 0.76 | 0.72 | 0.74 |
The hybrid model significantly improves recall by correctly identifying multi-word Hinglish keyphrases (e.g., "superhit picture", "time waste movie"). extraction2020720phindienglishvegamoviesn hot
Assuming Vegamovies had a considerable database: | Model | P | R | F1
The rise of digital platforms has revolutionized the way we consume media, including movies. Platforms focusing on specific genres or types of content, such as Vegamovies, have gained popularity. However, there's limited information on what such platforms offer, especially concerning specific language preferences like Hindi and English. Typical commands:
(If the goal is to extract subtitles, translate, or analyze audio from a legitimate copy)
The global movie industry has seen a significant shift towards online streaming services. Platforms like Netflix, Amazon Prime, and Disney+ Hotstar have become household names. Alongside these, niche platforms focusing on specific dietary preferences or cultural content have also emerged.
Precision (P), Recall (R), F1-score at the keyphrase level (exact match).