计算机科学 ›› 2022, Vol. 49 ›› Issue (6A): 165-171.doi: 10.11896/jsjkx.210400238
余本功1,2, 张子薇1, 王惠灵1
YU Ben-gong1,2, ZHANG Zi-wei1, WANG Hui-ling1
摘要: 电商平台信息对消费者的商品购买决策有显著影响。基于大体量的店铺与商品信息、在线评论文本进行信息融合并得出在线商品排序辅助消费者进行购买决策,具有重要的研究价值。针对上述问题,提出了一种融合多层次情感和主题信息的TS-AC-EWM在线商品排序方法,充分利用了评分信息与评论内容信息。首先,从计量与内容两个维度设计在线商品排序评价体系,体系包含4个计量指标与3个内容指标;其次,爬取各候选商品的计量指标与在线评论内容;然后,用融合主题与情感信息的TS方法以及基于追加评论的AC方法计算3个内容指标;最后,用熵权法确定指标权重,得出商品评分及排序。以京东微波炉数据集为例进行实验,证明了所提方法的可行性与有效性,因此该排序方法具有一定的现实意义。
中图分类号:
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