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Register a new userAspect-Controllable Opinion Summarization
تلخيص رأي قابل للتحكم في الجوانب
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ينتج العمل الأخير بشأن تلخيص الرأي ملخصات عامة بناء على مجموعة من مراجعات المدخلات وشعبية الآراء المعبر بها فيها.في هذه الورقة، نقترح نهج يسمح بتوليد ملخصات مخصصة بناء على استفسارات الجانب (E.G.، ووصف موقع وغرفة فندق).باستخدام مراجعة Corpus، نقوم بإنشاء مجموعة بيانات تدريبية صناعية من (مراجعة، ملخص) أزواج مخصبة بوحدات التحكم في الارتفاع التي يسببها نموذج تعليمي متعدد الأمثلة يتنبأ بجوانب وثيقة على مستويات مختلفة من الحبيبية.نحن نغلق نموذج مسبق باستخدام مجموعة البيانات الاصطناعية لدينا وإنشاء ملخصات محددة من جانب جانب من خلال تعديل وحدات التحكم في الجانب.تشير التجارب في معيارين إلى أن نموذجنا يفوق على الحالة السابقة من الفن ويولد ملخصات شخصية عن طريق التحكم في عدد الجوانب التي تمت مناقشتها فيها.
Recent work on opinion summarization produces general summaries based on a set of input reviews and the popularity of opinions expressed in them. In this paper, we propose an approach that allows the generation of customized summaries based on aspect queries (e.g., describing the location and room of a hotel). Using a review corpus, we create a synthetic training dataset of (review, summary) pairs enriched with aspect controllers which are induced by a multi-instance learning model that predicts the aspects of a document at different levels of granularity. We fine-tune a pretrained model using our synthetic dataset and generate aspect-specific summaries by modifying the aspect controllers. Experiments on two benchmarks show that our model outperforms the previous state of the art and generates personalized summaries by controlling the number of aspects discussed in them.
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