KDD Retro: Google Knowledge Vault and Topic Modeling

The URX data science team recently attended the 2014 Knowledge Discover and Data mining (KDD) conference in New York. The conference was a whirlwind, four day tour of the latest research in data mining. The theme of these sessions was utilizing text information to improve knowledge inference. This encompasses a wide variety of text-based problems: topic modelling, structured knowledge extraction, bioinformatics, targeted advertising, and many, many more. In the wake of KDD14, we wanted to summarize a couple of our favorite programs and encourage feedback.

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The Science of Crawl (Part 1): Deduplication of Web Content

Here at URX we are building the world's first mobile app search API. Backing this API is a search engine containing a large corpus of web documents, meticulously maintained and carefully grown by crawling internet content. We've come to discover that building a functional crawler can be done relatively cheaply, but building a robust crawler requires overcoming a few technical challenges. In this series of blog posts, we will walk through a few of these technical challenges including content deduplication, link prioritization, feature extraction and re-crawl estimation. 

In this first installment, I will walk through the duplicate web content problem.

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The Deeplink Debrief - September 4

We rounded up the latest industry news, highlights and announcements in mobile engagement and deep linking to bring you the top articles to read.

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Deep Linking Webinar Recap

URX's John Milinovich joined Tune's Lucas Brown to cover the basics of deep linking and review the vast implications for mobile marketers. If you missed their webinar, you can watch the presentation here:

 You can also view the slides on SlideShare and read the companion white paper. To stay abreast of the rapid new developments in deep linking, sign up for the URX newsletter here.

If have any questions about deep linking and the content we covered during the webinar, please feel free to email stephanie@urx.com.

 

Introducing the URX App Search API

Today, we are excited to announce the world’s first App Search API, which enables developers to find and link users directly to relevant actions inside other apps.  Not only can developers weave apps into a seamless experience with the App Search API, they can also discover the best place to link users based on the apps on their devices.

Our team of engineers and data scientists have spent the last year building a knowledge graph on top of the content that exists within apps. We’re crawling and indexing linked data about apps to build an understanding of where entities exist, how they’re related to each other, and how they can be acted on. The App Search API lets developers access this graph with specific details about the user’s context (e.g. location, keywords, time, intended action).  The API then replies with the deep links and other meta data of relevant apps that the developer can present to the user.

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The Deeplink Debrief - August 7

This week, we take a look at deep linking solutions from Google, Facebook, and Apple, app unbundling, and how deep linking could change mobile revenue and advertising.

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Mobile Apps using Deeplinks have 2.5x Higher Engagement

Mobile Apps using Deeplinks have 2.5x Higher Engagement

It is well-known that we are spending more time online with our mobile devices. Furthermore, the majority of our time spent on mobile is in applications, rather than the mobile browser. Deeplinking standards have emerged to connect content across mobile apps and mobile browsers and provide the same fluid user experience as desktop.

However, for several leading companies such as Amazon, ESPN, and Ticketmaster, users are still accessing these sites more often from their mobile browsers than from the corresponding native apps. Why might some companies have higher in-app engagement than others? Does the use of deeplinks have any correlation to time spent via mobile apps?

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