Extractive Document Summarization using Non-negative Matrix Factorization
| Autor: | Vasudha Bhatnagar, Alka Khurana |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Document summarization
050101 languages & linguistics Computer science 05 social sciences Structure (category theory) 02 engineering and technology computer.software_genre Field (computer science) Non-negative matrix factorization Matrix decomposition ComputingMethodologies_PATTERNRECOGNITION 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing 0501 psychology and cognitive sciences Data mining computer |
| Zdroj: | Lecture Notes in Computer Science ISBN: 9783030276171 DEXA (2) |
| DOI: | 10.1007/978-3-030-27618-8_6 |
| Popis: | Effectiveness of Non-negative Matrix Factorization (NMF) in mining latent semantic structure of text has motivated its use for single document summarization. Initial promise shown by the method provokes further research in this field to advance state-of-the-art. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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