الصفحة 1
الصفحة 1
Deep learning approach for text summarization
Machine learning and deep learning, as we know, have started ruling over almost every field in the computing industry and so, has revolutionized the process of text summarization too. Automatic text summarization is an advancing realm of the natural language processing research in which concise textual summaries are generated from lengthy input documents. Extensive research has been carried out on how automatic summarization can be prosecuted through various extractive and abstractive techniques. In this paper, we address all the approaches to text summarization and present the modus operandi of an Architecture called Encoder Decoder, under the machine learning approach.
Computational Processing of the Portuguese Language ; 7th International Workshop, PROPOR 2006, Itatiaia, Brazil, May 13-17, 2006, Proceedings
Since 1993, PROPOR Workshops have become an important forum for - searchers involved in the Computational Processing of Portuguese,both written and spoken. The workshop and this book were structured around the following main t- ics, seven for full papers: (i) automatic summarization; (ii) resources; (iii) au- matic translation; (iv) named entity recognition; (v) tools and frameworks; (vi) systems and models; and another ?ve topics for short papers; (vii) information extraction; (viii) speech processing; (ix) lexicon; (x) morpho-syntactic studies; (xi) web, corpus and evaluation.
