Advanced product review summarization in e-commerce marketplaces: elevating beyond tf-idf and lexrank method - Anggraeni, Rita Melina; Ismi, Dewi Pramudi (Science in Information Technology Letters, 2022)
In the fiercely competitive domain of online product sales, wherein engendering trust among prospective buyers assumes paramount significance, the role of product reviews cannot be understated. However, a prevailing issue in online marketplaces resides in the presence of product reviews that do not consistently align with the overall product rating. Furthermore, the sheer abundance of comments often leads potential consumers to confine their scrutiny to the initial comments, thus leaving a substantial volume of reviews unexplored. To rectify this challenge, this study introduces an automated text summarization system for product reviews, leveraging the LexRank methodology. This system underwent rigorous evaluation using the Rouge metric, with results manifesting substantial promise. At a threshold of 0.1, Rouge-1 exhibited an accuracy of 16.67%, while Rouge-2 scored 3.01%, and Rouge-L reached 16.50%. At a threshold of 0.2, Rouge-1 yielded a score of 16.08%, Rouge-2 registered 2.64%, and Rouge-L scored 16.57%. The second evaluation, performed with a distinct test dataset, notably excelled, emphasizing the system's competence. Specifically, at the 0.2 threshold, the system displayed superior performance, underscoring its efficacy in refining product review summarization within online marketplaces