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This study aims to overcome the problem of traditional association rules relying almost entirely on expert experience to set relevant interest indexes in mining. Second, this project can effectively solve the problem of four types of rules being present in the database at the same time. The traditional association algorithm can only mine one or two types of rules and cannot fully explore the database knowledge in the decision-making process for library recommendation.

The authors proposed a Markov logic network method to reconstruct association rule-mining tasks for library recommendation and compared the method proposed in this paper to traditional Apriori, FP-Growth, Inverse, Sporadic and UserBasedCF algorithms on two history library data sets and the Chess and Accident data sets.

The method used in this project had two major advantages. First, the authors were able to mine four types of rules in an integrated manner without having to set interest measures. In addition, because it represents the relevance of mining in the network, decision-makers can use network visualization tools to fully understand the results of mining in library recommendation and data sets from other fields.

The time cost of the project is still high for large data sets. The authors will solve this problem by mapping books, items, or attributes to higher granularity to reduce the computational complexity in the future.

The authors believed that knowledge of complex real-world problems can be well captured from a network perspective. This study can help researchers to avoid setting interest metrics and to comprehensively extract frequent, rare, positive, and negative rules in an integrated manner.

The purpose of this paper is to obtain the reasonable dimensioning for each part and a full-dimension model of assembly dimensions.

The relational path graph of assembly dimension, the shortest-path spanning tree of functional dimension and a revised spanning tree are established in this paper.

The proposed method can obtain reasonable dimensioning of parts and establishment of dimension model in an assembly.

The proposed method can easily realise by computer and be more suitable to automatic dimensioning and establishment of dimension model of parts.

This study aims to provide insights into Airbnb’s exit from the China market, specifically from the perspective of platform competition.

Based on the understanding of the evolution and competition of peer-to-peer (P2P) accommodation market in China and the double-edged network effects, this viewpoint article provides an in-depth discussion on Airbnb’s withdrawal from the China market.

This viewpoint paper contends that Airbnb faced increasing challenges in establishing unique competitive advantages against local rivals, who demonstrate a capacity for innovation and maintaining loyal customers in adapting to the market evolution. Consequently, this may inhibit Airbnb from attracting the mainstream market and lead Airbnb into a negative spiral, exacerbated by indirect network effects.

This study offers insights into the failure of an internationalisation process, drawing from an analysis of the competitive environment and the competition strategies of P2P accommodation platforms in China. These findings have practical implications for the implementation of international business strategies in P2P accommodation.

本观点文章旨在基于平台竞争的视角对爱彼迎退出中国的现象进行阐释

基于对中国共享住宿/民宿市场的演变和竞争、双边网络效应的理解, 本文对爱彼迎退出中国进行了深入探讨。

本文提出, 爱彼迎在建立独特竞争优势以应对本地竞争对手方面面临日益严峻的挑战, 因为本地竞争者在适应市场变化方面展现出突出的创新和留客的能力。这可能会阻碍爱彼迎吸引主流市场, 并导致其跌入由间接网络效应加剧的恶性循环中。

基于对中国共享住宿平台的竞争环境和策略的分析, 本文洞悉了一个国际化失败的案例。本文的发现对于共享住宿的国际化策略实施具有实践意义。

Este artículo de opinión pretende aportar ideas sobre la salida de Airbnb del mercado chino, concretamente desde la perspectiva de la competencia entre plataformas.

Basándonos en la comprensión de la evolución y la competencia del mercado de alojamientos P2P en China, así como en los “efectos de red de doble filo”, este artículo de opinión ofrece una discusión en profundidad sobre la retirada de Airbnb del mercado chino.

Este documento sostiene que Airbnb enfrentó desafíos crecientes para establecer ventajas competitivas únicas frente a sus rivales locales, demostrando estos últimos una capacidad de innovación y del mantenimiento de la lealtad de sus clientes al adaptarse a la evolución del mercado. En consecuencia, esto puede inhibir a Airbnb para atraer al mercado principal y llevar a la empresa a una espiral negativa, exacerbada por efectos de red indirectos.

Este estudio ofrece una visión del fracaso de un proceso de internacionalización, a partir de un análisis del entorno competitivo y de las estrategias de competencia de las plataformas de alojamiento P2P en China. Estos resultados tienen implicaciones prácticas para la aplicación de estrategias empresariales internacionales en los alojamientos P2P.