相关论文: Prioritizing Technical Debt in Database Normalizat…

Modern cloud databases present scaling as a binary decision: scale-out by adding nodes or scale-up by increasing per-node resources. This one-dimensional view is limiting because database performance, cost, and coordination overhead emerge…

User-driven privacy allows individuals to control whether and at what granularity their data is shared, leading to datasets that mix original, generalized, and missing values within the same records and attributes. While such…

Modern portfolio theory(MPT) addresses the problem of determining the optimum allocation of investment resources among a set of candidate assets. In the original mean-variance approach of Markowitz, volatility is taken as a proxy for risk,…

Data quality is a key element for building and optimizing good learning models. Despite many attempts to characterize data quality, there is still a need for rigorous formalization and an efficient measure of the quality from available…

The need for high availability and performance in data management systems has been fueling a long running interest in database replication from both academia and industry. However, academic groups often attack replication problems in…

The performance of database systems is usually characterised by their average-case (i.e., throughput) behaviour in standardised or de-facto standard benchmarks like TPC-X or YCSB. While tails of the latency (i.e., response time)…

Good database design is crucial to obtain a sound, consistent database, and - in turn - good database design methodologies are the best way to achieve the right design. These methodologies are taught to most Computer Science undergraduates,…

Technical debt (TD) is a metaphor for code-related problems that arise as a result of prioritizing speedy delivery over perfect code. Given that the reduction of TDs can have long-term positive impact in the software engineering life-cycle…

Most theoretical frameworks that focus on data errors and inconsistencies follow logic-based reasoning. Yet, practical data cleaning tools need to incorporate statistical reasoning to be effective in real-world data cleaning tasks.…

Balancing the management of technical debt within recommender systems requires effectively juggling the introduction of new features with the ongoing maintenance and enhancement of the current system. Within the realm of recommender…

Databases play an essential role in our society today. Databases are embedded in sectors like corporations, institutions, and government organizations, among others. These databases are used for our video and audio streaming platforms,…

Tabular neural network (NN) has attracted remarkable attentions and its recent advances have gradually narrowed the performance gap with respect to tree-based models on many public datasets. While the mainstreams focus on calibrating NN to…

The basic financial purpose of an enterprise is maximization of its value. Trade credit management should also contribute to realization of this fundamental aim. Many of the current asset management models that are found in financial…

Notarization is a procedure that enhance data management by ensuring the authentication of data during audits, thereby increasing trust in the audited data. Blockchain is frequently used as a secure, immutable, and transparent storage,…

The long lifetime and the evolving nature of industrial products make them subject to technical debt at different levels. Despite multiple years of research on technical debt management, our industrial experience shows that introducing…

Developers sometimes choose design and implementation shortcuts due to the pressure from tight release schedules. However, shortcuts introduce technical debt that increases as the software evolves. The debt needs to be repaid as fast as…

We posit that striving for distributed systems that provide "single system image" semantics is fundamentally flawed and at odds with how systems operate in the physical world. We realize the database as an optimization of this system: a…

Inspired by the visualization of dental plaque at the dentist's office, this article proposes a novel visualization of redundancies in relational data. Our approach is based on a well-principled information-theoretic framework that has so…

As we know that the normalization is a pre-processing stage of any type problem statement. Especially normalization takes important role in the field of soft computing, cloud computing etc. for manipulation of data like scale down or scale…

A key component of most neural network architectures is the use of normalization layers, such as Batch Normalization. Despite its common use and large utility in optimizing deep architectures, it has been challenging both to generically…