We present the first learned index that supports predecessor, range queries and updates within provably efficient time and space bounds in the worst case. In the (static)...

This python library implements the discrimination discovery and prevention method proposed in the paper: “A methodology for direct and indirect discrimination prevention in...

GSP receives a text document as input and returns an enriched document, where all mentions of places/locations are associated to the corresponding geographic coordinates. To...

The SMAPH system links queries to the entities it mentions, disambiguating mentions if needed. Entities are Wikipedia pages. This problem is known as "entity recognition and...

The Quantum Distance-Based Classifier is a technique inspired by the classical k-Nearest Neighbors that leverages quantum properties to perform prediction.

CLiQS is a Python language software package for social media texts summarization with a diversified approach.

Efficient interpolation-based ranking on CPUs

This tool creates a dictionary with inverse document frequency (idf) values from the Google NGrams dataset.

Embeddings were created through applying word2vec skipgram to a corpus of wikipedia non-stub articles from a December 2015 English dump with the following parameters: -cbow 0...

CAsT 2019 data is split into two files one for training and the other one for testing. - Training set: CAsT 2019 conversations from training set and from test set without...

If you use this dataset, please cite the following paper: Fedor Vitiugin, Carlos Castillo: Cross-Lingual Query-Based Summarization of Crisis-Related Social Media: An Abstractive...

The dataset created for evaluation of summaries generated from social media posted during five natural disasters. The dataset contains: ground truth reports created by human...

Python library implementing sorted containers with state-of-the-art query performance and compressed memory usage.

Efficiency/Effectiveness Trade-offs in Learning to Rank” tutorial by Claudio Lucchese and Franco Maria Nardini at the European Conference on Machine Learning and Principles...

King’s College London developed a variety of data science materials based on R and Python. R is a de facto standard in statistical computing and visualisation, while our...

The 'Database Module' aims to introduce database analysis, focusing on DBMS architecture, Relational Models, SQL language and SQL nested queries. It is part of the Master in...

King’s College London has developed complete stories around Jupyter Notebooks that form easy recipes for reproducible methods in social data science. Jupyter...

Study, design and analysis of IR systems which are efficient and effective to process, mine, search, cluster and classify bigdata document collections, coming from textual as...