- 2015 CCC Videos — collected talks from the 32nd Chaos Computer Congress conference.
- An Integrated Bayesian Approach for Effective Multi-Truth Discovery (PDF) — Integrating data from multiple sources has been increasingly becoming commonplace in both Web and the emerging Internet of Things (IoT) applications to support collective intelligence and collaborative decision-making. Unfortunately, it is not unusual that the information about a single item comes from different sources, which might be noisy, out-of-date, or even erroneous. It is therefore of paramount importance to resolve such conflicts among the data and to find out which piece of information is more reliable.
- Direct Links to Free Springer Books — Springer released a lot of math books.
- A Psychological Exploration of Engagement in Geek Culture — Seven studies (N = 2354) develop the Geek Culture Engagement Scale (GCES) to quantify geek engagement and assess its relationships to theoretically relevant personality and individual differences variables. These studies present evidence that individuals may engage in geek culture in order to maintain narcissistic self-views (the great fantasy migration hypothesis), to fulfill belongingness needs (the belongingness hypothesis), and to satisfy needs for creative expression (the need for engagement hypothesis). Geek engagement is found to be associated with elevated grandiose narcissism, extraversion, openness to experience, depression, and subjective well-being across multiple samples.
"machine learning" entries
The O'Reilly Radar Podcast: Narrative Science's foray into proprietary business data and bridging the data gap.
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In this week’s episode, O’Reilly’s Mac Slocum chats with Kristian Hammond, Narrative Science’s chief scientist. Hammond talks about Natural Language Generation, Narrative Science’s shift into the world of business data, and evolving beyond the dashboard.
Here are a few highlights:
We’re not telling people what the data are; we’re telling people what has happened in the world through a view of that data. I don’t care what the numbers are; I care about who are my best salespeople, where are my logistical bottlenecks. Quill can do that analysis and then tell you — not make you fight with it, but just tell you — and tell you in a way that is understandable and includes an explanation about why it believes this to be the case. Our focus is entirely, a little bit in media, but almost entirely in proprietary business data, and in particular we really focus on financial services right now.
You can’t make good on that promise [of what big data was supposed to do] unless you communicate it in the right way. People don’t understand charts; they don’t understand graphs; they don’t understand lines on a page. They just don’t. We can’t be angry at them for being human. Instead we should actually have the machine do what it needs to do in order to fill that gap between what it knows and what people need to know.