Xydo’s Innards

Xydo, the social news web site, opened its beta to the public last week.

I’ve been using this news feed aggregator for the last few months, and if you think it’s easy to keep track of which subscriber likes which particular news nugget, there’s 34 slides to prove you wrong.

Robert Blumen and Nanda Yadav of Xydo gave a presentation at NYC Tech Talks in April on how node.js and Hadoop clusters keep the whole show going:Continue reading

Another Look at Xydo

Mobile World Congress is happening now in Barcelona. As much as we’d like to buy our paella salads at the La Boqueria before a day on the trade show floor, the editorial team is instead stuck here in NJ.

To help with my remote coverage, which involves monitoring tweets, decrypting media releases, and studying the keynote videos, I decided to take another look at Xydo. It’s the crowd-based recommendation service I wrote about a few months ago. Plus I’ve been informed it’s been re-designed.

As with other sites in this genre, the crowd votes on content, which is pulled in from a number of different sources and categorized into various topic areas.

Topics encompass this whole wide world—pasta and grains, business news, mobile, movies, and on and on

So I entered “mobile world congress” into Xydo’s global search box.Continue reading

Do I Need a Web Recommendation Service?

Xydo is a recommendation startup I first discovered at Hoboken Tech Meetup. Since then I’ve partially trained GetGlue and Hunch to respond to my tastes (not successfully), perused Parse.ly’s recommendation app for filtering feeds, and gauged Google’s own Prediction APIs and Set suggestion tools (pretty good stuff).

So when I received the beta invite from Xydo, I was almost at the beginnings of an existential crisis: do I really need a web site to show me other URLs to look at? After all, I was heavily reliant on Google Reader to bring the feeds I like to my attention. I wasn’t sure whether I required additional content advice.

I would want Xydo and other such sites to be my web magazine 2.0, bringing both content that I absolutely need yet also uncannily anticipate what I may want.Continue reading

Parse.ly’s P3 Platform

I was finally able to spend quality time with the Parse.ly Reader, an app designed to show some of the capabilities of the underlying Parse.ly platform, called P3, which is currently in beta. To be clear, unlike many other players in the recommendation patch (GetGlue, Xydo, Hunch, etc.), this NYC-based startup is not in the business of providing a direct service to users.

Instead they give access to their cloud-based recommendation server through a set of RESTful APIs. The Reader app is just a demonstration of what can be done with their technology.

So what can be done?

After reading through the P3 reference documents and interacting with the Parse.ly Reader, you quickly see that P3’s aim is to reproduce formerly expensive, proprietary technology mastered by a few players (Netflix, Amazon) for businesses in general— most likely, those in the small-to-medium bins.

It’s another Nick Carr moment for me, in which technology has turned a previously mysterious application, recommendation algorithms in this case, into something closer to an appliance meant for wider usage. Continue reading

The View from Hoboken

I’m liking the Hoboken Tech Meetup experience. As I remarked in my last HTM post, there are advantages with smaller groups and a limited roster of speakers. The pace is less hurried, the demos more leisurely, the speakers can make extended points, and the Q&As have more educational value.

Obviously, I hope that HTM grows and prospers, but I would recommend NYCers take the Path or ferry and try this more intimate tech gathering. And the views of the NYC skyline from the Babbio Center are quite stunning.

Kudos to Aaron Price and his staff.

I’ll confess that I come to these meetups just for the demos, but at last night’s Hoboken Tech Meetup I arrived earlier and stayed later to listen to the speakers.  To my surprise, I was able to understand some of the inner legal and financial aspects of the startup world, which were the subject of two of the talks.

Bigger surprise: I enjoyed  it.Continue reading

Knowledge-based Recommendations

Over the last few months, recommendation startups have sprouted up—getglue, Hunch, Foodspotting, Parse.ly, Miso, Xydo (in beta), Bubbalon, etc.—to offer suggestions about restaurants, books, web sites, or just about anything in this world.

If you add in Facebook (with its like button, and lots of 3rd-party rating apps ), Amazon, and NetFlix, there’s enough of a universe to merit a service that rates and recommends recommendation services. There’s a startup, no doubt, working this out.

All share the idea that there’s wisdom in the crowd, and to various extents use stats about the mob to algorithmically classify tastes—clustering, nearest neighbor,decision trees—and then generate suggestions. There’s a nice summary of these collaborative filtering techniques in the reference section below.

What about a more conventional, common-sense approach that derives wisdom from actual knowledge of the subject?Continue reading