本頁只刊出中文翻譯與中文說明；英文原文請見下方原文連結。
原文連結
論文資訊
- 類型：已發表論文
- 日期：2022-02-12
摘要
Online product reviews are ubiquitous and helpful sources of 資訊 available to consumers for making purchase decisions. Consumers rely on both the quantitative aspects of reviews such as valence and volume as well as textual descriptions to learn about product quality and fit. In this paper we show how new achievements in natural 語言 process-ing can provide an important assist for different kinds of review-related writing tasks. Working in the interesting context of wine reviews, we demonstrate that machines are capable of performing the critical marketing task of writing expert reviews directly from a fairly small amount of product attribute data (metadata). We conduct a kind of "Turing Test" to evaluate human response to our machine-written reviews and show strong support for the assertion
※ 此為已發表論文，全文需透過期刊付費取得