拔出 发表于 2025-3-23 13:39:04
Introduction,rent perspectives. The available models for QA are divided into three major categories, namely, TextQA, KBQA, and hybrid QA. This chapter describes the importance of QA systems compared to the search engines and discusses how QA systems can provide the required information for users by short, concreindenture 发表于 2025-3-23 16:13:58
http://reply.papertrans.cn/79/7819/781812/781812_12.png宽大 发表于 2025-3-23 19:33:47
Question Answering Evaluation, structure, and source of best-known TextQA datasets will be discussed in this chapter. The most popular knowledge bases, as well as question sets which have been widely used as a benchmark in many recent works on KBQA, will be introduced and described. The structure of storing and retrieving informHyperopia 发表于 2025-3-23 23:49:05
http://reply.papertrans.cn/79/7819/781812/781812_14.pngIncisor 发表于 2025-3-24 04:50:13
Question Answering over Text,ategories: non-deep learning- based and deep learning-based approaches. A detailed explanation of the main property of each of these categories and available methods in each category will be covered in this chapter. Deep learning-based models will be studied in three different approaches, namely, inBRIDE 发表于 2025-3-24 09:02:21
http://reply.papertrans.cn/79/7819/781812/781812_16.pngPON 发表于 2025-3-24 14:17:20
http://reply.papertrans.cn/79/7819/781812/781812_17.pngDRILL 发表于 2025-3-24 15:20:21
http://reply.papertrans.cn/79/7819/781812/781812_18.pngoutset 发表于 2025-3-24 22:33:37
Future Directions of Question Answering,dataset and are used to answer questions from the same domain and language. Various extensions have also been proposed to build QA systems with more specific features. The recent studies on QA show that still there is room to provide systems with more abilities, e.g., cross-lingual QA systems, expla步履蹒跚 发表于 2025-3-25 00:02:08
http://reply.papertrans.cn/79/7819/781812/781812_20.png