To address the challenge that the existing methods struggle to balance solution efficiency， assignment quality， and generalization in airport gate pre-assignment at large hub airports under dynamic changes in flight number， gate layout， and assignment rules， an airport gate assignment algorithm based on node prediction in conflict graph of assigned activities was proposed. Firstly， an airport gate assignment model was established with the objectives of maximizing gate assignment rate and cumulative soft preference. Secondly， the feasible airport gate assignment activities were screened through an airfield zoning strategy， the corresponding conflict graph of assignment activities was constructed， the Node-Edge Collaborative Updating Graph Neural Network （NECU-GNN） was designed， and the NECU-GNN for Node Prediction model （NECU-GNN4NP） was developed. Finally， the NECU-GNN4NP-guided ranking-based Max Weighted Independent Set Algorithm （MWISA） was proposed on the basis of NECU-GNN4NP， so as to solve the optimal set of assignment activities for the conflict graph of assignment activities and obtain the airport gate assignment scheme. Experimental results based on Shenzhen Bao’an International Airport data show that compared with the current optimal assignment scheme at Shenzhen Bao’an International Airport， the proposed algorithm increases the gate assignment rate by 4.2， 4.3， and 3.1 percentage points， respectively， improves the cumulative soft preference by 38.1%， 30.3%， and 42.8%， respectively， and reduces the solution time by 65.3%， 39.1%， and 41.4%， respectively， in low-peak， normal， and high-peak scenarios. In addition， migration experimental results based on Yinchuan Hedong International Airport data demonstrate that the proposed algorithm can be adapted and applied to other airports rapidly. It can be seen that the proposed algorithm not only has good generalization but also enables efficient and high-quality airport gate assignment.

With the continuous development of knowledge graph technology， knowledge information management driven by knowledge graph has been widely applied in multiple domains， so the efficiency of distributed Simple Protocol and Resource description framework Query Language （SPARQL） query for knowledge graph is particularly important. Firstly， a detailed investigation on the existing Spark-based and Random Access Memory （RAM）-based distributed RDF systems was conducted. Secondly， query performance evaluation of eight representative systems selected from the above systems was performed， thereby comparing query performance differences between Spark-based and RAM-based systems with different query types， query diameters and datasets. Thirdly， the query performance of Spark-based and RAM-based systems was evaluated by analyzing the experimental results comprehensively. Finally， the future research directions of distributed SPARQL query optimization which oriented vertical application domain were pointed out aiming at problems of the existing distributed SPARQL query， such as poor query scalability， high query join complexity and long query compilation time.

In order to protect user's identity privacy and data security for access control in wireless sensor networks, a privacy-preserving access control protocol in multi-user wireless sensor networks was proposed. The protocol employed attribute-based encryption algorithms and distributed access control mode, using the attribute certificates, digital signatures and threshold mechanism to achieve the pay access, fine-grained access control and anonymous access. And it also ensured the confidentiality of data transmission and data integrity of query command. Analysis and protocol comparison shows that the proposed protocol has several advantages over the current access control methods: lower cost in computation, communication and storage, better scalability and better adaptation to access control requirement of payment wireless sensor network.

In order to realize the readable proofs in geometry and improve the efficiency of reason, the design and implementation of an automatic reasoning system for structive geometry statements was introduced in the paper. Users can input the prerequisites of geometry statements by graphic-drawing method that the system provided. Most structive geometry statements in elementary geometry can be proved and resolved automatically with readable proofs, which can meet the needs of education and research on elementary or high geometry.

Question Answering (QA) aims to find actual answers to users' questions in natural language. It has attracted more and more attention from the researchers in information retrieval and natural language research field. A typical QA system adopts a pipeline structure that contains "question analysis", "passage retrieval" and "answer selection" modules. In this paper, the research literature and the famous international conferences in QA research area were surveyed. The functions and methods of hot topics were mainly presented such as question analysis, query expansion, passage retrieval and answer selection. Furthermore, some existing problems were proposed in these studies.