Enriching textbooks by Question-Answers using cQA
Shobhan Kumar, Arun Chauhan · 2019
The two major sources of information for the knowledge seekers are the community question answers (cQA) blogs and textbooks. Textbooks play a vital role in any educational system. Many times, the textbooks that are available in the market are not adequate to fulfill the curiosity of the students, they frequently use the online question answering systems to acquire more knowledge. Due to the high volume of data, there will be high variance in the quality of questions and available answers in cQA forums, hence it takes additional effort to go through all possible question-answers for a better insight. To address this issue, this paper presents a technological solution-“A sentence-level text enrichment process” for a textbook with cQA content. We used techniques of natural language processing and data mining to extract the high-quality question-answers (QA) sets and corresponding links of cQA to enrich the textbooks. Experiments were carried out on the National Council of Educational Research and Training (NCERT) textbooks from India and Pattern Recognition and Machine Learning textbook by Christopher M Bishop, proves that we succeed to enrich textbooks on various subjects and across different grades with high-quality reference materials using automated techniques. The performance of the proposed system is evaluated using precision scores states that our method is competitive.