自然言語処理タスク
32 の手法がこの系統にあります。
注目
Aspect-Based Sentiment Analysis (ABSA)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チャンキングChunking, also called shallow parsing, is a natural-language-processing task introduced by Steven Abney in 1991 that divides text into grammatical pieces — such as noun phrases and構成素解析Constituency parsing is a natural-language-processing task that represents a sentence as a tree of recursively nested phrase-structure constituents — for example S → NP + VP. Build依存構造解析Dependency parsing is a natural-language-processing task that reveals the syntactic dependency relations between the words of a sentence as a tree structure. Surveyed in the depend対話行為分類Dialogue act classification is a natural-language-processing task that automatically labels the communicative function of each utterance in a conversation — such as question, answe談話解析Discourse parsing is a natural-language-processing task that models the rhetorical relations between sentences and paragraphs of a text — relations such as cause, contrast, and ela
学びの道筋
このトピックで最も多く参照される基礎的な手法を、発展してきた順に並べました — はじめての方はここから読み始めてください。
すべての手法 32
Aspect-Based Sentiment Analysis (ABSA)チャンキング構成素解析依存構造解析対話行為分類談話解析テキストにおける感情検出エンティティリンキング偽ニュース検出Few-Shot Text Classificationフレーム解析暗黙的感情分析意図検出辞書ベース感情分析機械読解 (MRC)機械翻訳複数文書要約固有表現抽出（NER）意見マイニング品詞タグ付け（POSタグ付け）質問応答 (QA)意味解析述語項関係付与（SRL）感情分析スタンス検出構造化テキスト抽出主観性検出Temporal Expression Extraction (TIMEX)テキスト分類テキスト要約単語の意味曖昧性解消 (WSD)ゼロショット分類