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Register a new userProfiling News Discourse Structure Using Explicit Subtopic Structures Guided Critics
هيكل خطاب أخبار التنميط باستخدام هياكل SubStopic صريحة
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نقدم إطار منتقدي الممثل للحث على الهياكل الفرعية في مقال إخباري لمجموع خطاب الأخبار.يستخدم النموذج منتقدين متعددين يتصرفون وفقا لهياكل رشية معروفة بينما يهدف الممثل إلى تفوقها.تشكل هياكل المحتوى جمل تمثل حدود رائعة كامنة.ثم، نقدم شبكة عصا هرمية تستخدم الجمل الحدودية الرواعية المحددة إلى نموذج التفاعل متعدد المستويات بين الجمل والسلطة الفرعية والوثيقة.يظهر النتائج التجريبية والتحليلات في Corpiscours على أن نموذج الممثل يتعلم بتفصيل وثيقة بفعالية وثيقة إلى فرعية وتحسين أداء النموذج الهرمي في مهمة تنميط الخطاب الأخبار.
We present an actor-critic framework to induce subtopical structures in a news article for news discourse profiling. The model uses multiple critics that act according to known subtopic structures while the actor aims to outperform them. The content structures constitute sentences that represent latent subtopic boundaries. Then, we introduce a hierarchical neural network that uses the identified subtopic boundary sentences to model multi-level interaction between sentences, subtopics, and the document. Experimental results and analyses on the NewsDiscourse corpus show that the actor model learns to effectively segment a document into subtopics and improves the performance of the hierarchical model on the news discourse profiling task.
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