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Large language models (LLMs) have revolutionized natural language interfaces for databases, particularly in text-to-SQL conversion. However, current approaches often generate unreliable outputs when faced with ambiguity or insufficient context.

We ...

Two efficient iteration methods are proposed for solving the absolute value equation which are the accelerated generalized SOR-like (AGSOR-like) iteration method and the preconditioned generalized SOR-like (PGSOR-like) iteration method. We prove ...

We study the problem of processing continuous <inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="yu-ieq3-3344662.gif"/></alternatives></inline-formula> nearest neighbor ...

In real life, the relationship between social or economic environment and resource constraints may impose restrictions on the formation of coalitions. More and more scholars have recognized the limitations of (crisp) cooperative games and propose ...

This paper introduces DAMOCRO, a <u>da</u>ta <u>m</u>igration framework using <u>o</u>nline <u>c</u>lassification and tuple <u>r</u>e<u>o</u>rdering to improve throughput and decrease the costs of data migration. The DAMOCRO workflow consists of four ...

Breast cancer continues to be a major global health challenge, necessitating reliable diagnostic methods for early detection and improved patient outcomes. This study introduces a novel ensemble fuzzy model for predictive breast cancer diagnosis, ...

• A new approach integrates deep-learning classifiers with fuzzy logic for improved decision-making.
• The ensemble includes Inception-V4, Inception-ResNet, and Inception V3/V4 + BN, enhancing accuracy.
• Fuzzy logic allows adaptive ...

The problem of identifying the <italic>k</italic>-shortest paths (KSPs for short) in a dynamic road network is essential to many location-based services. Road networks are dynamic in the sense that the weights of the edges in the corresponding graph ...

Video Database Management Systems (VDBMS) leverage advancements in computer vision and deep learning for efficient video data analysis and retrieval. This paper introduces the concept of user-specified Clues, allowing users to incorporate domain-specific ...

This special issue of IEEE Internet Computing explores the transformative area of data marketplaces within the data economy, presenting three rigorously selected articles that address crucial topics, such as data valuation, privacy preservation, and trust ...

In recent years, there has been a growing recognition that high-quality training data is crucial for the performance of machine learning models. This awareness has catalyzed both research endeavors and industrial initiatives dedicated to data acquisition ...

A fuzzy game with a configuration structure (i.e., a fuzzy configuration structure game) is introduced, which not only allows the fuzzy participation of players but also admits the intersection of fuzzy priori coalitions. A kind of ...

In a cooperative game with a coalition structure (i.e., coalition structure game), a coalition structure value (CS-value) is obtained on the assumption that the coalition structure has been or can be formed. The necessity analysis of coalition ...

Machine Learning (ML) has gained prominence across various fields, including data management. Rule-based components are substituted by ML-driven counterparts that extract rules from experience. The prevalence of statistical methods is waning as ...

Data migration refers to the transfer of data from one location to another, for instance, from a local database to a cloud server or from one cloud to another. To minimize business disruption during this process, it is essential to ensure that data ...

Considering the group marginal contribution of coalitions (with size no larger than k), we study the cooperative game (transferable utility game (TU-game)) with a fuzzy payoff (i.e., fuzzy TU-game). In order to reflect the impact of the coalition'...

The markets for data and AI models are rapidly emerging and increasingly significant in the realm and the practices of data science and artificial intelligence. These markets are being studied from diverse perspectives, such as e-commerce, economics, ...

We present a novel multi-level representation of time series called OM3 that facilitates efficient interactive progressive visualization of large data stored in a database and supports various interactions such as resizing, panning, zooming, and visual ...

While selecting the execution plan for a given query based on a single estimated cost is a generally-adopted strategy, it is usually error-prone and fails to comprehensively profile the plan performance. In this work, we complement existing plan ...

The prevalence of location-based services has generated a deluge of check-ins, enabling the task of human mobility understanding. Among the various types of information associated with the check-in venues, categories (e.g., Bar and Museum) are vital to ...

Named Entity Recognition (NER) is fundamental to multiple downstream natural language processing (NLP) tasks, but most advanced NER methods heavily rely on massive labeled data with high cost. In this paper, we explore the effectiveness of self-training ...