Related papers: A Systematic Method for On-The-Fly Denormalization…
It is a long term desire of the computer users to minimize the communication gap between the computer and a human. On the other hand, almost all ICT applications store information in to databases and retrieve from them. Retrieving…
Many data we collect today are in tabular form, with rows as records and columns as attributes associated with each record. Understanding the structural relationship in tabular data can greatly facilitate the data science process.…
In this research project, we investigate an alternative to the standard cloud-centralized data architecture. Specifically, we aim to leave part of the application data under the control of the individual data owners in decentralized…
The digital transformation of companies has led to the evolution of databases towards Big Data. Our work is part of this context and concerns more particularly the mechanisms to extract datasets stored in a Data Lake and to store the data…
The relational model is the most commonly used data model for storing large datasets, perhaps due to the simplicity of the tabular format which had revolutionized database management systems. However, many real world objects are recursive…
The technique of database refactoring is all about applying disciplined and controlled techniques to change an existing database schema. The problem is to successfully create a Database Refactoring Framework for databases. This paper…
The execution logs that are used for process mining in practice are often obtained by querying an operational database and storing the result in a flat file. Consequently, the data processing power of the database system cannot be used…
Enterprise level data is often distributed across multiple sources and identifying the correct set-of data-sources with relevant information for a knowledge request is a fundamental challenge. In this work, we define the novel task of…
As an on-ramp to databases, we offer several well-structured private database templates as open source resources for agriculturalists, particularly those with modest spreadsheet skills. These farmer-oriented Air table databases use simple…
A hidden database refers to a dataset that an organization makes accessible on the web by allowing users to issue queries through a search interface. In other words, data acquisition from such a source is not by following static…
An important problem in training deep networks with high capacity is to ensure that the trained network works well when presented with new inputs outside the training dataset. Dropout is an effective regularization technique to boost the…
Database normalization is crucial to preserving data integrity. However, it is time-consuming and error-prone, as it is typically performed manually by data engineers. To this end, we present Miffie, a database normalization framework that…
We discuss long-term preservation of and access to relational databases. The focus is on national archives and science data archives which have to ingest and integrate data from a broad spectrum of vendor-specific relational database…
This paper presents TableQuery, a novel tool for querying tabular data using deep learning models pre-trained to answer questions on free text. Existing deep learning methods for question answering on tabular data have various limitations,…
Maintaining a legacy database is a difficult task especially when system documentation is poor written or even missing. Database reverse engineering is an attempt to recover high-level conceptual design from the existing database instances.…
Tackling the information retrieval gap between non-technical database end-users and those with the knowledge of formal query languages has been an interesting area of data management and analytics research. The use of natural language…
This paper describes our experience with using Grid files as the main storage organization for a relational database management system. We primarily focus on the following two aspects. (i) Strategies for implementing grid files efficiently.…
Object-oriented database systems proved very valuable at handling and administrating complex objects. In the following guidelines for embedding neural networks into such systems are presented. It is our goal to treat networks as normal data…
This paper describes a unique approach to perform application behavioral analysis for identifying how tables might be related to each other. The analysis techniques are based on the properties of primary and foreign keys and also the data…
Storing XML documents in a relational database is a promising solution because relational databases are mature and scale very well and they have the advantages that in a relational database XML data and structured data can coexist making it…