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Knowledge-Based Weak Supervision for Information Extraction of Overlapping Relations
TLDR
A novel approach for multi-instance learning with overlapping relations that combines a sentence-level extraction model with a simple, corpus-level component for aggregating the individual facts is presented. Expand
Learning 5000 Relational Extractors
TLDR
LUCHS is presented, a self-supervised, relation-specific IE system which learns 5025 relations --- more than an order of magnitude greater than any previous approach --- with an average F1 score of 61%. Expand
Assieme: finding and leveraging implicit references in a web search interface for programmers
TLDR
In a study of programmers performing searches related to common programming tasks, it is shown that programmers obtain better solutions, using fewer queries, in the same amount of time spent using a general Web search interface. Expand
Filling Knowledge Base Gaps for Distant Supervision of Relation Extraction
TLDR
This work proposes a simple yet novel framework that combines a passage retrieval model using coarse features into a state-of-the-art relation extractor using multi-instance learning with fine features, and adapts the information retrieval technique of pseudorelevance feedback to expand knowledge bases. Expand
Information extraction from Wikipedia: moving down the long tail
TLDR
Three novel techniques for increasing recall from Wikipedia's long tail of sparse classes are presented: shrinkage over an automatically-learned subsumption taxonomy, a retraining technique for improving the training data, and supplementing results by extracting from the broader Web. Expand
Fast and Robust Interface Generation for Ubiquitous Applications
TLDR
An overview of Supple is provided and key extensions that barred the previous version from practical application are described, including a functional modeling language capable of representing complex applications and a new adaptation strategy, split interfaces, which speeds access to common interface features without disorienting the user. Expand
Amplifying community content creation with mixed initiative information extraction
TLDR
The potential synergy promised if two interlocking feedback cycles can be made to accelerate each other by exploiting the same edits to advance both community content creation and learning-based information extraction is explored. Expand
Evaluating visual cues for window switching on large screens
An increasing number of users are adopting large, multi-monitor displays. The resulting setups cover such a broad viewing angle that users can no longer simultaneously perceive all parts of theExpand
Personalized Online Education - A Crowdsourcing Challenge
TLDR
Some of the challenges and directions that HCOMP researchers will address are sketched, and some of the directions researchers hope to address are outlined. Expand
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