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Register a new userAnswering Product-Questions by Utilizing Questions from Other Contextually Similar Products
الإجابة على أسئلة المنتج عن طريق الاستفادة من الأسئلة من المنتجات الأخرى المماثلة للسياق
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إن التنبؤ بإجابة سؤال متعلقة بالمنتج هو مجال ناشئ من البحوث وجذب مؤخرا الكثير من الاهتمام. الإجابة على الأسئلة الذاتية والقائمة على الرأي هي الأكثر تحديا بسبب الاعتماد على المحتوى الذي تم إنشاؤه العملاء. يعمل السابق في الغالب على التنبؤ بالإجابة على مراجعة الاستعراض؛ ومع ذلك، فإن هذه الأساليب تفشل في منتجات جديدة أو غير شعبية، بعد مراجعات (أو قليلة فقط) في متناول اليد. في هذا العمل، نقترح نهج رواية ومكملة للتنبؤ بإجابة هذه الأسئلة، بناء على إجابات أسئلة مماثلة تم طرحها على منتجات مماثلة. نقيس التشابه السياقي بين المنتجات بناء على الإجابات التي توفرها لنفس السؤال. يستخدم إطار خبير في الخبراء للتنبؤ بالإجابة عن طريق تجميع الإجابات من المنتجات المماثلة للسياق. توضح النتائج التجريبية أن نموذجنا يتفوق على خطوط أساسية قوية في بعض شرائح الأسئلة، أي تلك التي لها ما يقرب من عشرة أسئلة واحدة أو أكثر مماثلة في الجور. بالإضافة إلى ذلك نشر مجموعات بيانات واسعة النطاق المستخدمة في هذا العمل، أحد أزواج أسئلة مماثلة، والثاني هو أزواج الإجابة على الأسئلة.
Predicting the answer to a product-related question is an emerging field of research that recently attracted a lot of attention. Answering subjective and opinion-based questions is most challenging due to the dependency on customer generated content. Previous works mostly focused on review-aware answer prediction; however, these approaches fail for new or unpopular products, having no (or only a few) reviews at hand. In this work, we propose a novel and complementary approach for predicting the answer for such questions, based on the answers for similar questions asked on similar products. We measure the contextual similarity between products based on the answers they provide for the same question. A mixture-of-expert framework is used to predict the answer by aggregating the answers from contextually similar products. Empirical results demonstrate that our model outperforms strong baselines on some segments of questions, namely those that have roughly ten or more similar resolved questions in the corpus. We additionally publish two large-scale datasets used in this work, one is of similar product question pairs, and the second is of product question-answer pairs.
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