Smart speakers such as Alexa and Google Home introduced Artificial Intelligence (AI) in
millions soon billions of households, making AI an everyday experience. We can now look …

This chapter provides an overview of the data matching process, and describes the five
major steps involved in this process: data pre-processing (cleaning and standardisation) …

This tutorial brings together perspectives on ER from a variety of fields, including databases,
machine learning, natural language processing and information retrieval, to provide, in one …

A crowdsourcing system, such as the Amazon Mechanical Turk (AMT), provides a platform
for a large number of questions to be answered by Internet workers. Such systems have …

The rapid growth of the Web in the past two decades has made it the largest publicly
accessible data source in the world. Web mining aims to discover useful information or …

This article defines a set of type inference rules for resolving overloading introduced by type
classes, as used in the functional programming language Haskell. Programs including type …

Entity resolution (ER) is the problem of identifying which records in a database refer to the
same entity. In practice, many applications need to resolve large data sets efficiently, but do …

Entity Resolution and Information Quality presents topics and definitions, and clarifies
confusing terminologies regarding entity resolution and information quality. It takes a very …

Conventional correlated topic models are able to capture correlation structure among latent
topics by replacing the Dirichlet prior with the logistic normal distribution. Word embeddings …

Author name ambiguity in a digital library may affect the findings of research that mines
authorship data of the library. This study evaluates author name disambiguation in DBLP, a …