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Register a new userEvent Graph based Sentence Fusion
الحدث الرسم البياني بناء الجملة الانصهار
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الحكم من الانصهار هي مهمة توليد مشروطة تدمج العديد من الجمل ذات الصلة في واحدة متماسكة، والتي يمكن اعتبارها عقوبة ملخص. منذ فترة طويلة تم الاعتراف بأهمية الانصهار منذ فترة طويلة من قبل المجتمعات في توليد اللغة الطبيعية، وخاصة في تلخيص النص. لا يزال يمثل تحديا لنموذج لخصي مخبئي عصبي لإنشاء عقوبة ملخص متكاملة جيدا. في هذه الورقة، نستكشف طريقة انصهار الجملة الفعالة في سياق تلخيص النص. نقترح إنشاء رسم بياني حدث من جمل المدخلات لالتقاط الأحداث ذات الصلة بفعالية وتنظيمها بطريقة منظمة واستخدام الرسم البياني الحدث الذي تم إنشاؤه لتوجيه الانصهار الجملة. بالإضافة إلى الاستفادة من الاهتمام على محتوى الجمل والعقد الرسم البياني، فإننا نضع كذلك آلية انتباه تدفق الرسوم البيانية للتحكم في عملية الانصهار عبر بنية الرسم البياني. عند تقييم بيانات خلطة الجملة التي تم بناؤها من مجموعة بيانات ملخصة، CNN / DALIYMAIL ومتعدد الأخبار، يظهر طرازنا لتحقيق أدائه الحديث من حيث الحزام وغيرها من المقاييس مثل معدل الانصهار والإخلاص.
Sentence fusion is a conditional generation task that merges several related sentences into a coherent one, which can be deemed as a summary sentence. The importance of sentence fusion has long been recognized by communities in natural language generation, especially in text summarization. It remains challenging for a state-of-the-art neural abstractive summarization model to generate a well-integrated summary sentence. In this paper, we explore the effective sentence fusion method in the context of text summarization. We propose to build an event graph from the input sentences to effectively capture and organize related events in a structured way and use the constructed event graph to guide sentence fusion. In addition to make use of the attention over the content of sentences and graph nodes, we further develop a graph flow attention mechanism to control the fusion process via the graph structure. When evaluated on sentence fusion data built from two summarization datasets, CNN/DaliyMail and Multi-News, our model shows to achieve state-of-the-art performance in terms of Rouge and other metrics like fusion rate and faithfulness.
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