Cyberattacks include Structured Query Language Injection (SQLi), which represents threats at the level of web applications that interact with the database. These attacks are carried out by executing SQL commands, which compromise the integrity and co...
Geospatial big data analysis (GBDA) is extremely significant for time-constraint applications such as disaster response. However, the time-constraint analysis is not yet a trivial task in the cloud computing environment. Spatial query processing (SQP...
The processing and analysis of trajectories are the core of many location-based applications and services, while trajectory similarity is an essential concept regularly used. To address the time-consuming problem of similarity query, an efficient alg...
In this study, we propose a novel adaptive algorithm for approximate nearest neighbor (ANN) search, based on the inverted file (IVF) index (cluster-based index) and online query complexity classification. The concept of the classical IVF search imple...
Knowledge graphs (KGs) have gained prominence for representing real-world facts, with queries of KGs being crucial for their application. Aggregate queries, as one of the most important parts of KG queries (e.g., “ What is the average price of...
The rapid growth of GPS-enabled mobile devices has popularized many location-based applications. Spatial keyword search which finds objects of interest by considering both spatial locations and textual descriptions has become very useful in these app...
Faced with the rapid growth of vector data and the urgent requirement of low-latency query, it has become an important and timely challenge to effectively achieve the scalable storage and efficient access of vector big data. However, a systematic met...
This paper presents a novel neural network model for the detection of Structured Query Language (SQL) injection attacks for web applications. The model features high detection accuracy, fast inference speed, and low weight size. The model is based on...
The range query is one of the most important query types in spatial data processing. Geographic information systems use it to find spatial objects within a user-specified range, and it supports data mining tasks, such as density-based clustering. In...
Location recommendation is essential for various map-based mobile applications. However, it is not easy to generate location-based recommendations with the changing contexts and locations of mobile users. Skyline operation is one of the most well-est...
As a structural indicator of dense subgraphs, k-core has been widely used in community search due to its concise and efficient calculation. Many community search algorithms have been expanded on the basis of k-core. However, relevant algorithms often...
Modern route planners such as Google Maps and Apple Maps serve millions of users worldwide, optimizing routes in large-scale road networks where fast responses are required for diverse cost metrics including travel time, fuel consumption, and toll co...
A join order directly affects database query performance and computational overhead. Deep reinforcement learning (DRL) can explore efficient query plans while not exhausting the search space. However, the deep Q network (DQN) suffers from the overest...
SimRank is a widely used metric for evaluating vertex similarity based on graph topology, with diverse applications such as large-scale graph mining and natural language processing. The objective of the single-source and top-k SimRank query problem i...
With the development of cloud computing, interest in database outsourcing has recently increased. However, when the database is outsourced, there is a problem in that the information of the data owner is exposed to internal and external attackers. Th...
Cloud computing has a significant role in healthcare services, especially in medical applications. In cloud computing, the best choice of virtual machines (Virtual_Ms) has an essential role in the quality improvement of cloud computing by minimising...
Modern complex systems include products and services that comprise many interconnected pieces of integrated hardware and software, which are expected to serve humans interacting with them. As technology advances, expectations of a smooth, flawless sy...
Dense object detection is widely used in automatic driving, video surveillance, and other fields. This paper focuses on the challenging task of dense object detection. Currently, detection methods based on greedy algorithms, such as non-maximum suppr...
Large language models (LLMs) have driven transformative progress in artificial intelligence, yet critical challenges persist in data management and privacy protection during model deployment and training. The approximate nearest neighbor (ANN) search...
In the process of data services, compressing and indexing data can reduce storage costs, improve query efficiency, and thus enhance the quality of data services. However, different service requirements have diverse demands for data precision. Traditi...
With continuous improvement of earth observation technology, source, and volume of remote sensing data are gradually enriched. It is critical to realize unified organization and to form data sharing service capabilities for massive remote sensing dat...
Updating the most recent set of point cloud data is critical in autonomous driving environments. However, existing systems for point cloud data management often fail to ensure real-time updates or encounter situations in which data cannot be effectiv...
In recent years positioning sensors have become ubiquitous, and there has been tremendous growth in the amount of trajectory data. It is a huge challenge to efficiently store and query massive trajectory data. Among the typical operation over traject...
Edge computing can reduce the transmission pressure of wireless networks in earthquakes by pushing computing functionalities to network edges and avoiding the data transmission to cloud servers. However, this also leads to the scattered storage of da...
Bipartite networks are widely used to model interactions between two types of entities in many real-world applications, such as recommendation systems, social networks, and academic networks. Community search aims to identify cohesive groups containi...
Knowledge base question answering (KBQA) aims to provide answers to natural language questions from information in the knowledge base. Although many methods perform well when dealing with simple questions, there are still two challenges for complex q...
Black-box attacks against deep neural network (DNN) classifiers are receiving increasing attention because they represent a more practical approach in the real world than white box attacks. In black-box environments, adversaries have limited knowledg...
Progressive visualization offers a great deal of promise for big data visualization; however, current progressive visualization systems do not allow for continuous interaction. What if users want to see more confident results on a subset of the visua...
In the domain of computer vision, object recognition aims at detecting and classifying objects in data sets. Model-driven approaches are typically constrained through their focus on either a specific type of data, a context (indoor, outdoor) or a set...
This paper studies the journey planning problem in the context of transit networks. Given the timetable of a schedule-based transportation system (consisting, e.g., of trains, buses, etc.), the problem seeks journeys optimizing some criteria. Specifi...
This paper presents an efficient algorithm for matching subgraph queries in a multi-graph based on features-based indexing techniques. The KD-tree data structure represents these nodes’ features, while the set-trie index data structure represen...
There has recently been an increasing need for the collection and sharing of microdata containing information regarding an individual entity. Because microdata typically contain sensitive information on an individual, releasing it directly for public...
As data volumes grow and business requirements become increasingly complex, Hybrid Transactional/Analytical Processing (HTAP) technologies, capable of handling both Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP) workload...
The current practice of users searching for different types of geo-resources in a geographic area and wishing to identify the most convenient routes for visiting the most relevant ones, requires the iterative formulation of several queries: first to...
Continuous k-similarity trajectories search over a data stream is an important problem in the domain of spatio-temporal databases. Given a set of trajectories
Black-box attacks generate adversarial examples by querying the target model and updating the noise according to the feedback. However, the current black-box attack methods require excessive queries to generate adversarial examples, increasing the ri...
It is extremely important to extract valuable information and achieve efficient integration of remote sensing data. The multi-source and heterogeneous nature of remote sensing data leads to the increasing complexity of these relationships, and means...
In several applications of text classification, training document labels are provided by human evaluators, and therefore, gathering sufficient data for model creation is time consuming and costly. The labeling time and effort may be reduced by active...
In traditional textile manufacturing, downstream manufacturers use raw materials, such as Nylon and cotton yarns, to produce textile products. The manufacturing process involves warping, sizing, beaming, weaving, and inspection. Staff members typical...
Handwritten keyword spotting (KWS) is of great interest to the document image research community. In this work, we propose a learning-free keyword spotting method following query by example (QBE) setting for handwritten documents. It consists of four...
Graph analytics has grown increasingly popular as a model for data analytics across a variety of domains. This has prompted an emergence of solutions for large-scale graph analytics, many of which integrate user-facing domain-specific languages (DSLs...
In the future, with the advent of the smart factory era, manufacturing and logistics processes will become more complex, and the complexity and criticality of traceability will further increase. This research aims at developing a performance assessme...
Despite the availability of a large amount of free unlabeled data, collecting sufficient training data for supervised learning models is challenging due to the time and cost involved in the labeling process. The active learning technique we present h...
Many modern applications are modeled using graphs of some kind. Given a graph, reachability, that is, discovering whether there is a path between two given nodes, is a fundamental problem as well as one of the most important steps of many other algor...
Current social-network-based and location-based-service applications need to handle continuous spatial approximate keyword queries over geo-textual streaming data of high density. The continuous query is a well-known expensive operation. The optimiza...
We propose a method to address the challenge of course discovery on search platforms by employing large language models (LLMs) to parse extended search parameters from natural language queries. We developed a set of algorithms that augment a course s...
In the Chinese character writing task performed by robotic arms, the stroke category and position information should be extracted through object detection. Detection algorithms based on predefined anchor frames have difficulty resolving the differenc...
The purpose of this research was to determine how we can optimize both customer and seller experiences in a super shop using hyperautomation technology. Here, a smart bot was employed to speed up responses of simple consumer queries by utilizing natu...
The Wireless Sensor Network similarity search problem has received considerable research attention due to sensor hardware imprecision and environmental parameter variations. Most of the state-of-the-art distributed data centric storage (DCS) schemes...
Image sensors produce high-dimensional visual data for classification algorithms. Deep Neural Networks (DNNs) achieve high accuracy but require large labeled datasets and computational and energy resources, limiting their use in embedded systems. Act...
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