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Register a new userUnsupervised Approach to Multilingual User Comments Summarization
نهج غير منشأة لتلخيص تعليقات المستخدم المتعدد اللغات
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تعليق المستخدم هو ميزة قيمة للعديد من المنافذ الإخبارية، مما يتيح لهم اتصال مع القراء وتمكين القراء للتعبير عن رأيهم، وتوفير وجهات نظر مختلفة، وحتى المعلومات التكميلية. ومع ذلك، من الصعب تصفية كميات كبيرة من تعليقات المستخدمين، ناهيك عن قراءة واستخراج المعلومات ذات الصلة. لا يزال البحث في تلخيص تعليقات المستخدمين في مهده، ومجموعات بيانات التلخيص التي تم إنشاؤها الإنسان نادرة، خاصة بالنسبة لغات أقل الموارد. لمعالجة هذه المشكلة، نقترح نهج غير مدعوم لتلخيص تعليقات المستخدم، والذي يستخدم تمثيل حديث متعدد اللغات للجمل جنبا إلى جنب مع تقنيات تلخيص الاستخراج القياسية. تقارننا مناهج تمثيل الجملة المختلفة مقترن بنهج تلخيص مختلفة يدل على أن أكثر المجموعات ناجحة هي نفسها في الأخبار وتلخيص التعليق. النتائج التجريبية وعرضت تصور تظهر فائدة المنهجية المقترحة لعدة لغات.
User commenting is a valuable feature of many news outlets, enabling them a contact with readers and enabling readers to express their opinion, provide different viewpoints, and even complementary information. Yet, large volumes of user comments are hard to filter, let alone read and extract relevant information. The research on the summarization of user comments is still in its infancy, and human-created summarization datasets are scarce, especially for less-resourced languages. To address this issue, we propose an unsupervised approach to user comments summarization, which uses a modern multilingual representation of sentences together with standard extractive summarization techniques. Our comparison of different sentence representation approaches coupled with different summarization approaches shows that the most successful combinations are the same in news and comment summarization. The empirical results and presented visualisation show usefulness of the proposed methodology for several languages.
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