Abstract
Nowadays, crossover and convergence between services has become a new phenomenon in service market, especially in China. This work aims at analyzing the inner and external formation mechanism of crossover service, which have great significance to the sustainable development of this new ecosystem. Previously, a traditional concept based knowledge graph extracted from crossover service News was constructed for crossover service event analysis. The crossover modes and the statistics of appearances were found in that experiment. Due to the limitation of motivation analysis of the inference method based on static concept structure, the Event Evolutionary Graph (EEG) is introduced to improve the event analysis, and moreover to achieve the event prediction in this undergoing experiment. Generic EEG can represent the event evolution rules and patterns, but due to the characteristics of crossover services, this experiment will adapt event modeling method and its training method. This work in progress methodology would explain the inner and external formation reason of crossover service, and furthermore achieve the assisted decision-making for potential crossover organizations based on event prediction.
Supervised by Zhongjie Wang, Zhiying Tu.
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Liu, M., Wang, Z., Tu, Z. (2019). Crossover Service Phenomenon Analysis Based on Event Evolutionary Graph. In: Liu, X., et al. Service-Oriented Computing – ICSOC 2018 Workshops. ICSOC 2018. Lecture Notes in Computer Science(), vol 11434. Springer, Cham. https://doi.org/10.1007/978-3-030-17642-6_35
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DOI: https://doi.org/10.1007/978-3-030-17642-6_35
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