| 摘要 |
Documents are collected from a variety of publicly available sources that contain product data including product reviews, product specifications, price information and the like. Snippets of text obtained from the documents are analyzed for relevance, sentiment, credibility and other aspects that help evaluate the quality of a product. Feature vectors are computed for snippets to analyze relevance, sentiment, or credibility. Statistical analysis is performed on the feature vectors to estimate a measure of the relevance, sentiment, or credibility. Factors associated with various snippets are aggregated to compute a quality score for a product or a particular aspect of product including product features, attributes, usages, or user personas. Information is displayed on a user interface that allows the user to examine the details relevant to computation of the quality score. |
