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Register a new userCSDS: A Fine-Grained Chinese Dataset for Customer Service Dialogue Summarization
CSDS: مجموعة بيانات صينية محبوبة من أجل حجز خدمة العملاء
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لفتت تلخيص الحوار اهتماما كبيرا مؤخرا. خاصة في مجال خدمة العملاء، يمكن للوكلاء استخدام ملخصات الحوار للمساعدة في زيادة أعمالهم من خلال معرفة قضايا العملاء بسرعة وتقدم الخدمة. تتطلب هذه التطبيقات ملخصات لاحتواء منظور مكبر صوت واحد ولديك هيكل تدفق موضوع واضح، في حين لا يتوفر في مجموعات البيانات الحالية. لذلك، في هذه الورقة، نقدم مجموعة بيانات صينية جديدة لتلخيص حوار خدمة العملاء (CSDS). يعمل CSDS على تحسين الملخصات الإفراطية في جوانب: (1) بالإضافة إلى الملخص العام للحوار بأكمله، كما يتم تقديم ملخصات الأدوار أيضا للحصول على وجهات نظر مكبرات صوت مختلفة. (2) تلخص جميع الملخصات لكل موضوع بشكل منفصل، وبالتالي تحتوي على هيكل مستوى الموضوع للحوار. نحدد المهام في CSDS كمولية الملخص الشامل والملخصات المختلفة الموجهة نحو الأدوار لحوار معين. بعد ذلك، نقارن العديد من طرق التلخيص على CSDS، وإظهار نتائج التجربة أن الطرق الحالية عرضة لتوليد ملخصات زائدة وغير متماسكة. علاوة على ذلك، يصبح الأداء أسوأ بكثير عند تحليل الأداء في ملخصات الأدوار وهياكل الموضوعات. نأمل أن تتمكن هذه الدراسة من مراجعة تلخيص الحوار الصيني وفائدة المزيد من الدراسات.
Dialogue summarization has drawn much attention recently. Especially in the customer service domain, agents could use dialogue summaries to help boost their works by quickly knowing customer's issues and service progress. These applications require summaries to contain the perspective of a single speaker and have a clear topic flow structure, while neither are available in existing datasets. Therefore, in this paper, we introduce a novel Chinese dataset for Customer Service Dialogue Summarization (CSDS). CSDS improves the abstractive summaries in two aspects: (1) In addition to the overall summary for the whole dialogue, role-oriented summaries are also provided to acquire different speakers' viewpoints. (2) All the summaries sum up each topic separately, thus containing the topic-level structure of the dialogue. We define tasks in CSDS as generating the overall summary and different role-oriented summaries for a given dialogue. Next, we compare various summarization methods on CSDS, and experiment results show that existing methods are prone to generate redundant and incoherent summaries. Besides, the performance becomes much worse when analyzing the performance on role-oriented summaries and topic structures. We hope that this study could benchmark Chinese dialogue summarization and benefit further studies.
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