Titlebook: Databases Theory and Applications; 34th Australasian Da Zhifeng Bao,Renata Borovica-Gajic,Zhengyi Yang Conference proceedings 2024 The Edit

小丑

性冷淡

Glycogen

食品室

Why Query Plans Are Different: An Automatic Detection and Inference System-action framework and takes the detected differences as the input to explore the possible reasons behind them. We test .? with analytic workloads on a production database. Compared to developers, .? can find the right reason in most cases with much less time. .?has been deployed in TiDB to help opti

天空

kNN Join for?Dynamic High-Dimensional Data: A Parallel Approachet . to identify their . nearest neighbor points from the Item dataset .. This operation plays a crucial role in various domains, including knowledge discovery, data mining, similarity search applications, and scientific research. However, exact kNN search in high-dimensional spaces is computational

Amplify

Palatial

Probabilistic Reverse Top-k Query on Probabilistic Data-most interest based on their objects’ references. Moreover, answering the queries on probabilistic data has been studied in many applications. The most common problem with uncertain queries is how to calculate their probabilities. Currently, there are some proposed solutions for selecting answers t

PTCA635

只有

Learning Implicit Sentiment for?Explainable Review-Based Recommendationsting in the same review may cause confusion in recommendations and generate inappropriate explanations. However, most current explainable recommendation methods fail to capture users’ implicit sentiment behind the reviews. In this paper, we propose a novel .mplicit .entiment learning model for .xpl

Spinal-Fusion