论文标题
产品类型的积极学习在电子商务中增强
Active Learning for Product Type Ontology Enhancement in E-commerce
论文作者
论文摘要
基于实体的语义搜索已在现代搜索引擎中广泛采用，以通过了解用户的意图来提高搜索准确性。在电子商务中，准确而完整的产品类型（PT）本体论对于识别查询中的产品实体并从目录中检索相关产品至关重要。但是，由于它可能涉及的大量人类努力，寻找产品类型（PTS）通常是昂贵的。在这项工作中，我们提出了一个积极的学习框架，该框架有效利用领域专家的知识来发现。我们还显示了实验结果中所得PT的质量和覆盖范围。
Entity-based semantic search has been widely adopted in modern search engines to improve search accuracy by understanding users' intent. In e-commerce, an accurate and complete product type (PT) ontology is essential for recognizing product entities in queries and retrieving relevant products from catalog. However, finding product types (PTs) to construct such an ontology is usually expensive due to the considerable amount of human efforts it may involve. In this work, we propose an active learning framework that efficiently utilizes domain experts' knowledge for PT discovery. We also show the quality and coverage of the resulting PTs in the experiment results.
