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| Phân cụm tài liệu× | GloVe Embeddings× | Phân loại văn bản× | |
|---|---|---|---|
| Lĩnh vực | Khai phá văn bản | Khai phá văn bản | Khai phá văn bản |
| Họ | Process / pipeline | Process / pipeline | Process / pipeline |
| Năm ra đời≠ | — | 2014 | — |
| Người khởi xướng≠ | — | Pennington, Socher & Manning | — |
| Loại≠ | Unsupervised text-mining task | Static word-embedding model | Supervised NLP classification task |
| Công trình gốc≠ | Aggarwal, C. C. & Zhai, C. (2012). Mining Text Data. Springer. ISBN: 9781461432227 | Pennington, J., Socher, R. & Manning, C. D. (2014). GloVe: Global Vectors for Word Representation. EMNLP. DOI ↗ | Joachims, T. (1998). Text Categorization with Support Vector Machines: Learning with Many Relevant Features. ECML 1998. Lecture Notes in Computer Science, vol 1398. Springer. DOI ↗ |
| Tên gọi khác≠ | text clustering, unsupervised text grouping, Belge Kümeleme (Document Clustering) | GloVe, global vectors, GloVe Kelime Gömülmeleri | text categorization, document classification, topic classification, metin sınıflandırma |
| Liên quan≠ | 4 | 3 | 4 |
| Tóm tắt≠ | Document clustering is an unsupervised text-mining task that groups documents with similar content together without using any labels. It is used to organise large collections and for exploratory analysis, drawing on the body of text-mining techniques consolidated by Aggarwal and Zhai (2012) and compared empirically by Steinbach, Karypis and Kumar (2000). | GloVe (Global Vectors for Word Representation) is a static word-embedding model introduced by Pennington, Socher and Manning (2014) that learns word vectors directly from global word-word co-occurrence statistics gathered across an entire corpus. The resulting vectors place semantically related words close together and perform strongly on semantic analogy tasks. | Text classification, also called text categorization, is a supervised natural-language-processing task that automatically assigns documents to predefined categories. Building on the support-vector-machine approach to text categorization established by Joachims (1998) and consolidated in the text-mining literature by Aggarwal and Zhai (2012), it powers tasks such as spam detection and topic classification by learning from labelled examples. |
| ScholarGateBộ dữ liệu ↗ |
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