کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4943425 1437634 2017 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Word-sentence co-ranking for automatic extractive text summarization
ترجمه فارسی عنوان
واژه یک جمله برای خلاصه کردن متن کامل استخراج خودکار است
کلمات کلیدی
خلاصه خودکار خلاصه استخراج، نمره دهی جمله، رتبه صفحه، یادگیری بی نظیر،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی
Extractive summarization aims to automatically produce a short summary of a document by concatenating several sentences taken exactly from the original material. Due to its simplicity and easy-to-use, the extractive summarization methods have become the dominant paradigm in the realm of text summarization. In this paper, we address the sentence scoring technique, a key step of the extractive summarization. Specifically, we propose a novel word-sentence co-ranking model named CoRank, which combines the word-sentence relationship with the graph-based unsupervised ranking model. CoRank is quite concise in the view of matrix operations, and its convergence can be theoretically guaranteed. Moreover, a redundancy elimination technique is presented as a supplement to CoRank, so that the quality of automatic summarization can be further enhanced. As a result, CoRank can serve as an important building-block of the intelligent summarization systems. Experimental results on two real-life datasets including nearly 600 documents demonstrate the effectiveness of the proposed methods.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 72, 15 April 2017, Pages 189-195
نویسندگان
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