Semantic Matching Efficiency of Supply and Demand Texts on Online Technology Trading Platforms: Taking the Electronic Information of Three Platforms as an Example

Highlights：

• We measured the SDME of the three representative OTTPs. The three OTTPs are sorted by the SDME from high to low: Zhejiang Market (Government-Owned, Government-Operated, GOGO), Technology E Market (Government-Owned, Contractor-Operated, GOCO) and Keyi Market (Market-Owned, Market-Operated, MOMO), indicating that government plays an important role in promoting the SDME by attracting effective technology suppliers and demanders to participate in online trade and standardizing information expression. By comparing the SDME and the newly announced signing rate of each OTTP, we found that the OTTP with high SDME also has high signing rate, and the changing trend of the two is consistent.

• We analyzed the topic distribution of technology supply and demand of OTTPs with TextRank and Latent Dirichlet Allocation (LDA), and calculated the topic differences of each OTTP. The Technology E Market and Zhejiang Market have low topic differences and high SDME, while Keyi Market has high topic differences and low SDME, which indicated that the topic differences have a negative effect on SDME.

摘要

•We proposed a new index named Supply-Demand Matching Efficiency (SDME) to measure the supply and demand matching efficiency for online technology trading platforms (OTTPs). Technically, it is based on semantic similarity of technology supply and demand texts with Word2Vec and Cosine similarity algorithms, which fully excavated semantic features of technology supply and demand texts, thus providing ideas for tacit knowledge mining and knowledge matching of technology supply and demand texts. Moreover, it provided ideas for estimating the trade possibility of technology supply and demand on OTTPs before technology trade occurs.•We measured the SDME of the three representative OTTPs. The three OTTPs are sorted by the SDME from high to low: Zhejiang Market (Government-Owned, Government-Operated, GOGO), Technology E Market (Government-Owned, Contractor-Operated, GOCO) and Keyi Market (Market-Owned, Market-Operated, MOMO), indicating that government plays an important role in promoting the SDME by attracting effective technology suppliers and demanders to participate in online trade and standardizing information expression. By comparing the SDME and the newly announced signing rate of each OTTP, we found that the OTTP with high SDME also has high signing rate, and the changing trend of the two is consistent.•We analyzed the topic distribution of technology supply and demand of OTTPs with TextRank and Latent Dirichlet Allocation (LDA), and calculated the topic differences of each OTTP. The Technology E Market and Zhejiang Market have low topic differences and high SDME, while Keyi Market has high topic differences and low SDME, which indicated that the topic differences have a negative effect on SDME.