Multiple Outcome Supervised Latent Dirichlet Allocation for Expert Discovery in Online Forums

AAAI Conferences

This paper presents a supervised bayesian approach to model expertise in online forums with application to question routing. The proposed method extends the well-known sLDA model to the multi-task case, accounting for a supervised stage with multiple outputs per document corresponding to the users of the system. A study of the characteristics of real world data revealed a number of challenges in the practical application of this model, relevant to the research community.

Properties of ABA+ for Non-Monotonic Reasoning Artificial Intelligence

We investigate properties of ABA+, a formalism that extends the well studied structured argumentation formalism Assumption-Based Argumentation (ABA) with a preference handling mechanism. In particular, we establish desirable properties that ABA+ semantics exhibit. These pave way to the satisfaction by ABA+ of some (arguably) desirable principles of preference handling in argumentation and nonmonotonic reasoning, as well as non-monotonic inference properties of ABA+ under various semantics.

It's official: People are having sexual fantasies about their digital voice assistants


But for a growing number of people, it's a mystery based not in the vagaries of human emotion but rather in the ones and zeros of proprietary software. According to an April 5 industry trend report focusing on voice-activated systems like Google Home and Amazon Echo, users are getting more than unsolicited Beauty and the Beast ads out of their digital assistants. That's right, people these days are intimately connecting to the Alexas of the world -- or at least fantasizing about doing so, anyway. "Over a third (37%) of regular voice technology users say that they love their voice assistant so much that they wish it were a real person," reads the report. "Even more astonishing is that more than a quarter of regular voice technology users say they have had a sexual fantasy about their voice assistant."

Students explore the social impact of artificial intelligence


Shawn Rickenbacker teaches Humans Machines, a Social Innovation and Social Entrepreneurship course. An architect, he is a Taylor Senior Fellow and Favrot Visiting Chair. Artificial intelligence is at most people's fingertips everyday. But we may not understand its implications and complexities. "When you speak to Apple's Siri or Amazon's Alexa to retrieve info, or use Facebook, you're actually engaging with artificial intelligence," said Shawn Rickenbacker, a Taylor Senior Fellow at the Phyllis Taylor Center for Social Innovation and Design Thinking and Favrot Visiting Chair in the Tulane School of Architecture.