Lifelong Machine Learning, Second Edition is an introduction to an advanced machine
learning paradigm that continuously learns by accumulating past knowledge that it then …

We consider here the problem of building a never-ending language learner; that is, an
intelligent computer agent that runs forever and that each day must (1) extract, or read …

We consider the problem of semi-supervised learning to extract categories (eg, academic
fields, athletes) and relations (eg, PlaysSport (athlete, sport)) from web pages, starting with a …

The emergence of various disruptive technologies such as big data, Internet of Things, and
artificial intelligence have instigated our society to generate enormous volumes of data. The …

Originating from Facebook, LinkedIn, Twitter, Instagram, YouTube, and many other
networking sites, the social media shared by users and the associated metadata are …

There are major trends to advance the functionality of search engines to a more expressive
semantic level. This is enabled by the advent of knowledge-sharing communities such as …

We compare various forms of prompts to represent event types and develop a unified
framework to incorporate the event type specific prompts for supervised, few-shot, and zero …

We describe a open-domain information extraction method for extracting concept-instance
pairs from an HTML corpus. Most earlier approaches to this problem rely on combining …

In this paper, we study the problem of expanding a set of given seed entities into a more
complete set by discovering other entities that also belong to the same concept set. A typical …

A dictionary---a set of instances belonging to the same conceptual class---is central to
information extraction and is a useful primitive for many applications, including query log …