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Unsupervised Extraction of Attributes and Their Values from Product Description
International Joint Conference on Natural Language Processing
This paper describes an unsupervised method for extracting product attributes and their values from an e-commerce product page. Previously, distant supervision has been applied for this task, but it is not applicable in domains where no reliable knowledge base (KB) is available. Instead, the proposed method automatically creates a KB from tables and itemizations embedded in the product's pages. This KB is applied to annotate the pages automatically and the annotated corpus is used to train adblp:conf/ijcnlp/ShinzatoS13 fatcat:3nrl4axi7berzmoo3qauf3u2py