手法を比較

	Aspect-Based Sentiment Analysis (ABSA)	固有表現抽出（NER）
分野	テキストマイニング	テキストマイニング
系統	Process / pipeline	Process / pipeline
提唱年	2014	—
提唱者	Pontiki et al. (SemEval-2014 Task 4)	—
種類	NLP fine-grained opinion-mining task	NLP sequence-labelling task
原典	Pontiki, M. et al. (2014). SemEval-2014 Task 4: Aspect Based Sentiment Analysis. Proceedings of SemEval 2014, 27-35.	Nadeau, D. & Sekine, S. (2007). A survey of named entity recognition. Lingvisticae Investigationes.
別名	ABSA, aspect-level sentiment analysis, feature-based sentiment analysis, Konu Bazlı Duygu Analizi (ABSA)	NER, entity tagging, Adlandırılmış Varlık Tanıma (NER)
関連	4	3
概要	Aspect-based sentiment analysis (ABSA) is a fine-grained natural-language-processing task that detects sentiment separately for each aspect or feature mentioned in a text — such as a product's quality, price, or service — rather than scoring the document as a whole. It was consolidated as a shared task by Pontiki et al. in SemEval-2014 Task 4.	Named entity recognition (NER) is a natural-language-processing task that automatically detects and labels entities in text — such as people, organisations, locations, and dates. Surveyed by Nadeau and Sekine (2007) and later advanced with neural architectures by Lample et al. (2016), it turns free-running text into tagged spans that downstream tools can use.