Data & Knowledge Engineering

The popularity of chatbots, such as ChatGPT, has brought research attention to question answering systems, capable to generate natural language answers to user’s natural language queries. However, also in other kinds of systems, flexibility of ...

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• Top-down and Bottom-up analysis of research literature on Flexible Query Answering Systems (FQASs) following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines.
• Network and temporal Analysis of ...

Existing embedded multi-hop Question Answering over Knowledge Graph (KGQA) methods attempted to handle Knowledge Graph (KG) sparsity using Knowledge Graph Embedding (KGE) to improve KGQA. However, they almost ignore the intermediate path ...

Digitalization has greatly increased the importance of data in recent years, making data an indispensable resource for value creation in our time. There is currently still a lack of theories as well as practicable methods and techniques for the ...

The high growth of Online Social Networks (OSNs) over the last few years has allowed automated accounts, known as social bots, to gain ground. As highlighted by other researchers, many of these bots have malicious purposes and tend to mimic human ...

One of the problems that e-commerce users face is that the desired products are sometimes not available and Web shops fail to provide similar products due to their exclusive reliance on Boolean faceted search. User preferences are also often not ...

• We propose a framework for determining the most representative image on a Web page.
• We introduce and evaluate several novel image features and meta-data protocols.
• We design and evaluate a less-restrictive ranking methodology than ...

The efficient processing of mass stream data has attracted wide attention in the database field. The skyline query on the sensor data stream can monitor multiple targets in real time, to avoid abnormal events such as fire and explosion, which is ...

Process mining can help organizations by extracting knowledge from event logs. However, process mining techniques often assume business processes are stationary, while actual business processes are constantly subject to change because of the ...

Security risk management (SRM) is crucial for protecting valuable assets from malicious harm. While blockchain technology has been proposed to mitigate security threats in traditional applications, it is not a perfect solution, and its security ...

Relation extraction aims at identifying semantic relations between pairs of named entities from unstructured texts and is considered an essential prerequisite for many downstream tasks in natural language processing (NLP). Owing to the ability in ...

Deep reinforcement learning holds significant potential for application in industrial decision-making, offering a promising alternative to traditional physical models. However, its black-box learning approach presents challenges for real-world ...

• Segmentation of the state–space through probabilistic modeling.
• Initializing baseline policy for guided exploration using Behavioral Cloning (BC).
• Identifying segmented abnormal states with probabilistic modeling and DRL.
• ...

As influenza is easily converted to another type of virus and spreads very quickly from person to person, it is more likely to develop into a pandemic. Even though vaccines are the most effective way to prevent influenza, it takes a lot of time ...

In this paper, we propose a scraping method for collecting tweets, which we call DeepScraper. DeepScraper provides the complete scraping for the entire tweets written by a certain group of users or them containing search keywords with a fast ...

The usefulness of drawing-based psychological testing has been demonstrated in a variety of studies. By using the familiar medium of drawing, drawing-based psychological testing can be applied to a wide range of age groups and is particularly ...