The TransR model solves the problem that TransE and TransH models are not sufficient for modeling in public spaces, and is considered a highly potential knowledge representation model. However, TransR still adopts the translation principles based on the TransE model, and the constraints are too strict, which makes the model’s ability to distinguish between very similar entities low. Therefore, we propose a representation learning model TransR* based on flexible translation and relational matrix projection. Firstly, we separate entities and relationships in different vector spaces; secondly, we combine our flexible translation strategy to make translation strategies more flexible. During model training, the quality of generating negative triples is improved by replacing semantically similar entities, and the prior probability of the relationship is used to distinguish the relationship of similar coding. Finally, we conducted link prediction experiments on the public data sets FB15K and WN18, and conducted triple classification experiments on the WN11, FB13, and FB15K data sets to analyze and verify the effectiveness of the proposed model. The evaluation results show that our method has a better improvement effect than TransR on Mean Rank, Hits@10 and ACC indicators.

This paper presents an in-depth analysis and study of the diagnostic effectiveness of EUS-RTE in giant cystic tumours of the oesophagus utilizing cluster analysis. A new form of interval data expression was designed based on the cluster analysis algorithm, as well as a new way of updating the cluster radius and cluster centre. Feature triads are defined, eliminating the need to access all historical data at the time of update. It also prevents the case of overfusion of clusters and outputting only one cluster. If there exist a very low number of clusters, the newly merged clusters are reclustered according to the density clustering method for the internal data objects based on the cluster segmentation so that the data objects in the same cluster have a high similarity as possible. All accumulated electronic files of oesophageal cancer cases were collected and comprehensively organized, and all clinical data of 129 eligible cases with a total of 356 consultations were screened in strict accordance with inclusion and exclusion criteria. A database of oesophageal cancer cases was established using Visual FoxPro software, and frequency distribution, cluster analysis, association rule, and chi-square test were used to focus on mining the association between symptoms, disease mechanisms, prescriptions, and medications. The results were analysed and summarized. Overall, the therapeutic efficacy and safety of the three groups of treatment modalities for gastric mesenchymal tumours were positive, and the preoperative endoscopic treatment modalities should be selected based on the EUS-RTE characteristics of the tumour, the site, and the operator’s skill level in a comprehensive manner.

The main exploitation strategies in southeast Sulige gas field of Ordors Basin are hydraulic fracturing and downhole throttling are mainly adopted. Fractured wells in southeast Sulige gas field have no real stable production process, and the production is constantly decreasing. Fitting effect of adopting one decreasing method to investigate production decline is poor, such as Arps decline, SEPD decline and Duong decline methods. Because of such problems and production characteristics of southeast Sulige, a three-stage decline law study is put forward. The early production decline of gas well belongs to exponential decline, the middle stage belongs to exhaustion decline, and the intermittent exploitation stage belongs to linear decline mode. Most of the production of gas well comes from early and middle production. The study of decline law could provide certain guidance for the evaluation of recoverable reserves and development strategy.

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