Publications associées à Structured Query Language

Aggregation and Exploration of High-Dimensional Data Using the Sudokube Data Cube Engine

Christoph Koch, Peter Lindner, Zhekai Jiang, Sachin Basil John

We present Sudokube, a novel system that supports interactive speed querying on high-dimensional data using partially materialized data cubes. Given a storage budget, it judiciously chooses what projections to precompute and materialize during cube constru ...

Association for Computing Machinery2023

LAQy: Efficient and Reusable Query Approximations via Lazy Sampling

Anastasia Ailamaki, Periklis Chrysogelos, Viktor Sanca

Modern analytical engines rely on Approximate Query Processing (AQP) to provide faster response times than the hardware allows for exact query answering. However, existing AQP methods impose steep performance penalties as workload unpredictability increase ...

2023

Efficient and Effective Multi-Modal Queries Through Heterogeneous Network Embedding

Karl Aberer, Thanh Trung Huynh, Quoc Viet Hung Nguyen, Thành Tâm Nguyên, Chi Thang Duong

The heterogeneity of today's Web sources requires information retrieval (IR) systems to handle multi-modal queries. Such queries define a user's information needs by different data modalities, such as keywords, hashtags, user profiles, and other media. Rec ...

IEEE COMPUTER SOC2022

Efficient Massively Parallel Join Optimization for Large Queries

Anastasia Ailamaki, Bikash Chandra, Srinivas Karthik Venkatesh, Riccardo Mancini, Vasileios Mageirakos

Modern data analytical workloads often need to run queries over a large number of tables. An optimal query plan for such queries is crucial for being able to run these queries within acceptable time bounds. However, with queries involving many tables, find ...

2022

Edit Based Grading of SQL Queries

Bikash Chandra

Grading student SQL queries manually is a tedious and error-prone process. Earlier work on testing correctness of student SQL queries, such as the XData system, can be used to test the correctness of a student query. However, in case a student query is fou ...

ASSOC COMPUTING MACHINERY2021

Taster: Self-Tuning, Elastic and Online Approximate Query Processing

Anastasia Ailamaki, Raja Appuswamy, Matthaios Alexandros Olma, Odysseas Papapetrou

Current Approximate Query Processing (AQP) engines are far from silver-bullet solutions, as they adopt several static design decisions that target specific workloads and deployment scenarios. Offline AQP engines target deployments with large storage budget ...

IEEE2019

Efficient Bundled Spatial Range Queries

Anastasia Ailamaki, Darius Sidlauskas, Thomas Heinis, Farhan Tauheed, Eleni Tzirita Zacharatou

Efficiently querying multiple spatial data sets is a growing challenge for scientists. Astronomers query data sets that contain different types of stars (e.g., dwarfs, giants, stragglers) while neuroscientists query different data sets that model different ...

ASSOC COMPUTING MACHINERY2019

Polisis: Automated Analysis and Presentation of Privacy Policies Using Deep Learning

Karl Aberer, Rémi Philippe Lebret, Hamza Harkous, Kassem Fawaz

Privacy policies are the primary channel through which companies inform users about their data collection and sharing practices. These policies are often long and difficult to comprehend. Short notices based on information extracted from privacy policies h ...

USENIX ASSOC2018

Interferometric synthetic aperture microscopy for extended focus optical coherence microscopy

Theo Lasser, Paul James Marchand, Arno Pino Bouwens, Jérôme Extermann, Séverine Coquoz

Optical coherence microscopy (OCM) is an interferometric technique providing 3D images of biological samples with micrometric resolution and penetration depth of several hundreds of micrometers. OCM differs from optical coherence tomography (OCT) in that i ...

2017

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Structured Query Language

Aggregation and Exploration of High-Dimensional Data Using the Sudokube Data Cube Engine

LAQy: Efficient and Reusable Query Approximations via Lazy Sampling

Efficient and Effective Multi-Modal Queries Through Heterogeneous Network Embedding

Efficient Massively Parallel Join Optimization for Large Queries

Edit Based Grading of SQL Queries

Taster: Self-Tuning, Elastic and Online Approximate Query Processing

Efficient Bundled Spatial Range Queries

Polisis: Automated Analysis and Presentation of Privacy Policies Using Deep Learning

Interferometric synthetic aperture microscopy for extended focus optical coherence microscopy

Program Analysis and Compilation Techniques for Speeding up Transactional Database Workloads

Graph Chatbot

Chattez avec Graph Search

Efficient and Effective Multi-Modal Queries Through Heterogeneous Network Embedding

Efficient Bundled Spatial Range Queries

Taster: Self-Tuning, Elastic and Online Approximate Query Processing

Polisis: Automated Analysis and Presentation of Privacy Policies Using Deep Learning

Interferometric synthetic aperture microscopy for extended focus optical coherence microscopy

Aggregation and Exploration of High-Dimensional Data Using the Sudokube Data Cube Engine

Edit Based Grading of SQL Queries

LAQy: Efficient and Reusable Query Approximations via Lazy Sampling

Efficient Massively Parallel Join Optimization for Large Queries

Program Analysis and Compilation Techniques for Speeding up Transactional Database Workloads