Mining product textual data for recommendation explanations

• Main Author: LE TRUNG HOANG
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2022
• Subjects: Recommender Systems; Recommendation Explanations; Aspect-Level Sentiment; Review-Level Explanation; Question-Level Explanation; Evaluative Recommendation Explanation; Comparative Recommendation Explanations; Review Selection; Review Sets Selection; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/etd_coll/450; https://ink.library.smu.edu.sg/context/etd_coll/article/1448/viewcontent/GPIS_AY2017_PhD_LE_Trung_Hoang.pdf
• Institution: Singapore Management University

Recommendation explanations help to make sense of recommendations, increasing the likelihood of adoption. Here, we are interested in mining product textual data, an unstructured data type, coming from manufacturers, sellers, or consumers, appearing in many places including title, summary, descriptio...