公开(公告)号：US20190278835A1

公开(公告)日：2019-09-12

申请号：US15915775

申请日：2018-03-08

Applicant: Adobe Inc.

Inventor： Arman Cohan ,  Walter W. Chang ,  Trung Huu Bui ,  Franck Dernoncourt ,  Doo Soon Kim

IPC: G06F17/22 ,  G06N3/04 ,  G06F17/30 ,  G06F17/27

Abstract: Techniques are disclosed for abstractive summarization process for summarizing documents, including long documents. A document is encoded using an encoder-decoder architecture with attentive decoding. In particular, an encoder for modeling documents generates both word-level and section-level representations of a document. A discourse-aware decoder then captures the information flow from all discourse sections of a document. In order to extend the robustness of the generated summarization, a neural attention mechanism considers both word-level as well as section-level representations of a document. The neural attention mechanism may utilize a set of weights that are applied to the word-level representations and section-level representations.

公开(公告)号：US11170158B2

公开(公告)日：2021-11-09

申请号：US15915775

申请日：2018-03-08

Applicant: Adobe Inc.

Inventor： Arman Cohan ,  Walter W. Chang ,  Trung Huu Bui ,  Franck Dernoncourt ,  Doo Soon Kim

IPC: G06F40/14 ,  G06F40/146 ,  G06N3/04 ,  G06F16/93 ,  G06F16/34 ,  G06F40/30 ,  G06F40/56 ,  G06F40/274 ,  G06F40/289

Abstract: Techniques are disclosed for abstractive summarization process for summarizing documents, including long documents. A document is encoded using an encoder-decoder architecture with attentive decoding. In particular, an encoder for modeling documents generates both word-level and section-level representations of a document. A discourse-aware decoder then captures the information flow from all discourse sections of a document. In order to extend the robustness of the generated summarization, a neural attention mechanism considers both word-level as well as section-level representations of a document. The neural attention mechanism may utilize a set of weights that are applied to the word-level representations and section-level representations.