Deep Links, continued


Recent & Definitive


  • Deep links as an SEO practice for “regular web sites” [not treated]
  • Deep links pointing into Appware/Adware on storebought applications (i.e. “mobile,” on a phone or tablet).

Roundup of the Genre

InContext 2014

InContext 2014 by EverythingMe.

On the notion of context and anticipation of needs in & around a device class that has no keyboard and lives with you.


video; 48:47; slides

Benedict Evans, Andreesen Horowitz
Q&A with Benedict Evans faciliated byTim Draper (he plays John Battelle in this vignette)

  • Recites the boring statistics,
    • up-and-to-the-right,
    • explosive growth,
    • gosh it’s really big,
    • <gee whizz!>
  • He compares
    • Yahoo 1996 to App Store 2014; replaced by Google (unstructured search)
    • Web vs Internet; the web is all “the internet does”
    • Mobile is pre-pagerank”
  • What happens in 5 years
    • He doesn’t know
    • Android (in 5 years)
    • Coding languages (in 5 years)
    • iBeacon
    • Access vs owning
  • Strategies
    • Apple: top down the stack (from control of the supply chain)
    • Google: up the stack (from hardware fragmentation)
  • Strategies
    • I know what I want => Google
    • I’m bored => Facebook, BuzzFeed, etc. etc.
    • Demand Generation => empty
  • Smart(phones)
    • Are inherently social
    • Take away “winner take all”
  • Cards as content packages
    • Can be shared
    • Can be syndicated
    • Contradiction:
      • Atomised Content
      • App Silos
  • What’s Already Known
    • Contacts
    • Calendar
    • Apps frequently used
    • Travel patterns
    • etc.
  • Context
    • Google Now
    • or other similar things
  • But
    • The Filter Bubble
    • The Uncanny Valley
  • Something about ‘Ecosystem Cohorts’
  • Neither Apple nor Google “will win”; ther is no “winner take all” dynamic.


  • Some generalized whining
    • that intent and preference prediction won’t work;
      story about Pandora from Tim Draper.
    • that Google Now is ‘closed’ to (his) startups.
  • Unclear that a human butler (ahem, “life coach”) could live achive these standards.
  • Something about the music industry
    • It’s a distribution business
    • A quote from Mic Jagger about musicians not being paid 1970s-1995, not before, not after.
  • Draper on tablet vs PC
    • Tablet is for reading (&deleting)
    • PC is for creating

Bytes of Context

video; 25:42

  • Andreas Gal, Mozilla,
  • Andy Grignon, Quake Labs/Eightly, moderator
  • Andy Hickl, A.R.O,
  • G D Ramkumar, Swell.
  • Dave Smiddy, Alohar.

Global Context

video; 28:27

  • Josh Constine, TechCrunch, moderator
  • Brendan Eich from Mozilla,
  • Seth Sternberg from Google,
  • Ami Ben David from EverythingMe.

Mozilla Product Announcement

video; 29:52

  • Ami Ben David, Co-founder and Head of Strategy and Marketing at EverythingMe,
  • Andreas Gal, VP Mobile at Mozilla.

Firefox Launcher for Android by Mozilla

Wearables in Context

video; 33:08

  • Peter Berger, People+,
  • Christina Farr, VentureBeat,
  • Monisha Perkash, LUMO,
  • Rackspace’s Robert Scoble, moderator
  • Redg Snodgrass, Wearable World.

Via: backfill

How Mobile Is Eating The World | Benedict Evans, Enders Analysis at Business Insider

Benedict Evans (Enders Analysis); How Mobile Is Eating The World; In Business Insider; 2013-11-17.


  • Lots of up-and-to-the-right.
  • Irrelevance of Microsoft
  • Scale at Samsung
  • Scale at Apple
  • Tablets
  • Post-PC Vision
  • Four Horsemen
    • Google
    • Apple
    • Facebook
    • Amazon
  • Chinese Android is not Android
  • WebKit Everywhere
  • Smartphones are inherently social
    • address book
    • photo library
    • push notifications
    • home screen, task switcher
    • switching apps is easy
  • Unbundling Functions vs Unbundling Friends
  • Cards as Content Packets
  • Social as Discovery
  • Tablet Trends
  • Open Questions
    • What is the identity platform
    • Watch: protocols-and-services


  • The state of PCs
  • Smartphones are exploding
  • More mobile growth coming
  • The future is mobile
  • The world is 2017
  • Growth in emerging markets
  • Fundamental change
  • Fundamental change in scale
  • Fundamental change in use
  • What does mass mobile internet use really mean? From this…
  • … to this
  • Industry scale
  • Polarisation of manufacturers
  • The irrelevance of Microsoft
  • Scale at Samsung…
  • and scale at Apple
  • Very different products
  • Apple sticking to the high end?
  • Glass is eating the world
  • Tablets overtaking PCs
  • Tablet market splitting
  • iPad dominates use everywhere
  • Two distinct ‘tablet’ markets
  • Tablet [is] dynamic quite different to smartphones
  • Tablet [is] dynamic quite different to smartphones, continued
  • Blurring definitions
  • Tablets in 2013
  • Still lots of unknowns
  • ‘Four horsemen’ driving the agenda
  • Ecosystem sizes
  • Reach != value
  • (Chinese Android isn’t Google)
  • Geographic variation
  • Ecosystem is the key leverage point
  • People like apps
  • Mobile platform wars over?
  • Speed of innovation?
  • Different focus for innovation
  • App engagement
  • Self-selection
  • Ecosystem cohorts
  • Ecosystem cohorts?
  • Future of Android
  • Mobile social scale
  • Mobile social scale, continued
  • Children’s use of messaging
  • Smartphones are inherently social, unlike the desktop web
  • People happily abandon history, 3x slides
  • Facebook is one of many
  • Facebook is doing well on mobile
  • Half of DAUs are mobile-only
  • Is the mobile opportunity so big that it doesn’ matter to Facebook if it isn’t dominant?
  • Unbundling
  • The Aggregation Cycle
  • Unbundling Facebook
  • Unbundling functions or unbundling friends?
  • Mobile social is still in flux
  • There’s money in stickers
  • The next opportunity is creating the next platform
  • Cards as content packets – social as discovery
  • Two trends for mobile content
  • Again, all this is in flux
  • Broader uncertainty and opportunity
  • Blurring boundaries

Via: backfill

CAMEO: A Middleware for Mobile Advertisement Delivery | Khan, Jayarajah, Han, Misra, Balan, Seshan

Azeem J. Khan, Kasthuri Jayarajah, Dongsu Han, Archan Misra, Rajesh Balan, Srinivasan Seshan; CAMEO: A Middleware for Mobile Advertisement Delivery; In Proceedings of the 11th International Conference On Mobile Systems, Applications, And Services (MobiSys ’13); 2013-06-25; 13 pages.


Advertisements are the de-facto currency of the Internet with many popular applications (e.g. Angry Birds) and online services (e.g., YouTube) relying on advertisement generated revenue. However, the current economic models and mechanisms for mobile advertising are fundamentally not sustainable and far from ideal. In particular, as we show, applications which use mobile advertising are capable of using significant amounts of a mobile users’ critical resources without being controlled or held accountable. This paper seeks to redress this situation by enabling advertisement supported applications to become significantly more “user-friendly”. To this end, we present the design and implementation of CAMEO, a new framework for mobile advertising that

  1. employs intelligent and proactive retrieval of advertisements, using context prediction, to significantly reduce the bandwidth and energy overheads of advertising, and
  2. provides a negotiation protocol and framework that empowers applications to subsidize their data traffic costs by “bartering” their advertisement rights for access bandwidth from mobile ISPs.

Our evaluation, that uses real mobile advertising data collected from around the globe, demonstrates that CAMEO effectively reduces the resource consumption caused by mobile advertising.



  • CAMEO => Context-Aware Advertising Mediator and Optimizer
  • ANAS => AN Advertisement Selection
  • LAS => Local Advertisement Selection
  • BEAS => Best Effort Advertisement Selection


  • Context Predictor
  • Advertisement Manager
  • ISP Negotiator
  • Accounting and Verification module


See the paper.

Deep Links



  • URL =>
  • URI => profile://user123.



Organized along the great cultures






Cellogic (

  •, an ad retargeting network
  • Nextap (
  • Concept: “ for deep linking”
  • Specifications
    • 300×50 template
    • app badge icon
    • custom message
    • link
  • Who
    • Itamar Weisbrod, CEO
    • Noah Klausman, VP of Business Development
  • Previously



  • By Zwapp
  • open source
  • a database (unpublished) custom URL schemes for iOS applications
  • a downloadable tool
  • scans your iOS device looking for URLs


  • By Pocket Pixels, a photo app, iOS only
  • Older
  • Something about integrating photo sharing & editing web apps
  • iOS (iPhone) only
  • Source Code
  • Supported Apps
    • Original
    • Follow on
      • AutoStitch,
      • Click!,
      • Color Splash,
      • Juxtaposer,
      • PicTools,
      • Photogene,
      • Simply B&W,
      • Snap!,
      • TrueHDR.
  • Promotions



  • Mobile ad retargeting
  • Outreach
  • Promotion
    • Surely …



  • Mobile App Deeplink Retargeting
  • URX Mobile App Retargeting
  • Outreach
  • Founding
  • Funding
    • Y Combinator Summer 2012
    • $3.1 million seed round
    • Include First Round Capital, Maverick Capital, Google Ventures, SV Angel, Betaworks, Crunchfund (Michael Arrington), Greylock, CyberAgent, Fuel Capital, Garry Tan, Alexis Ohanian, Charlie Cheever, Sam Altman, Paul Bucheit, Geoff Ralston, Gus Fuldner, Plug & Play Ventures, Paul Sethi, Bill Peckovich, Joe Montana, Mehul Nariyawal, Dalton Caldwell, Virginia Turner, Andre Ranadive, Linda MacKenzie, Jamie Lee Curtis, Christopher Guest, Sumon Sadhu, Bruno Bowden, Chris Look, Nicholas Smith, and the Erickson Family.
  • Reference Customer
    • LivingSocial
  • Promotions


of the genre

Via: backfill, backfill, backfill

Sensor-ID, some trials


Does. Not. Work.

Move along, nothing to see here.

Previously noted.


Time X Coordinate Y Coordinate Unique
2013-10-13T12:21:29 -0.33926094532 1.0011098617 996
2013-10-13T12:23:19 -0.305329995155 1.00342984584 996
2013-10-13T12:24:45 -0.275689446926 1.00383234309 996
2013-10-13T17:11:54 -0.307242288589 1.00406484151 1000


Atrix 2, stock Android, with AT&T crapware; i.e. not CyanogenMod


User Experience

Unsupervised Indoor Localization: No Need to War-Drive | Wang, Sen, Eloghary, Farid, Youssef, Choudhury

He Wang, Souvik Sen, Ahmed Eloghary, Moustafa Farid, Moustafa Youssef, Romit Roy Choudhury; Unsupervised Indoor Localization: No Need to War-Drive; In Proceedings of MobiSys; 2012; 14 pages.


We propose UnLoc, an unsupervised indoor localization scheme that bypasses the need for war-driving. Our key observation is that certain locations in an indoor environment present an identifiable signature on one or more sensing dimensions. An elevator, for instance, imposes a distinct pattern on a smartphone’s accelerometer; a corridor-corner may overhear a unique set of WiFi access points; a specific spot may experience an unusual magnetic fluctuation. We hypothesize that these kind of signatures naturally exist in the environment, and can be envisioned as internal land- marks of a building. Mobile devices that “sense” these landmarks can recalibrate their locations, while dead-reckoning schemes can track them between landmarks. Results from 3 different indoor settings, including a shopping mall, demon strate median location errors of 1.69m. War-driving is not necessary, neither are floorplans – the system simultaneously computes the locations of users and landmarks, in a manner that they converge reasonably quickly. We believe this is an unconventional approach to indoor localization, holding promise for real-world deployment.

Via: backfill


PlaceRaider: Virtual Theft in Physical Spaces with Smartphones | Templeman, Rahman, Crandall, Kapadia

Robert Templeman, Zahid Rahman, David Crandall, Apu Kapadia; PlaceRaider: Virtual Theft in Physical Spaces with Smartphones; In arXiv pdf; 2012-09-26; landing


As smartphones become more pervasive, they are increasingly targeted by malware. At the same time, each new generation of smartphone features increasingly powerful onboard sensor suites. A new strain of sensor malware has been developing that leverages these sensors to steal information from the physical environment (e.g., researchers have recently demonstrated how malware can listen for spoken credit card numbers through the microphone, or feel keystroke vibrations using the accelerometer). Yet the possibilities of what malware can see through a camera have been understudied. This paper introduces a novel visual malware called PlaceRaider, which allows remote attackers to engage in remote reconnaissance and what we call virtual theft. Through completely opportunistic use of the camera on the phone and other sensors, PlaceRaider constructs rich, three dimensional models of indoor environments. Remote burglars can thus download the physical space, study the environment carefully, and steal virtual objects from the environment (such as financial documents, information on computer monitors, and personally identifiable information). Through two human subject studies we demonstrate the effectiveness of using mobile devices as powerful surveillance and virtual theft platforms, and we suggest several possible defenses against visual malware.

Via: backfill

Unsafe Exposure Analysis of Mobile In-App Advertisements | Grace, Zhou, Jiang, Sadeghi

Michael Grace, Wu Zhou, Xuxian Jiang, Ahmad-Reza Sadeghi; Unsafe Exposure Analysis of Mobile In-App Advertisements; In Proceedings of the 5th ACM Conference on Security and Privacy in Wireless and Mobile Networks (WiSec 2012); 2012; 12 pages.


In recent years, there has been explosive growth in smartphone sales, which is accompanied with the availability of a huge number of smartphone applications (or simply apps). End users or consumers are attracted by the many interesting features offered by these devices and the associated apps. The developers of these apps benefit financially, either by selling their apps directly or by embedding one of the many ad libraries available on smartphone platforms. In this paper, we focus on potential privacy and security risks posed by these embedded or in-app advertisement libraries (henceforth “ad libraries,” for brevity). To this end, we study the popular Android platform and collect 100,000 apps from the official Android Market in March-May, 2011. Among these apps, we identify 100 representative in-app ad libraries (embedded in 52.1% of the apps) and further develop a system called AdRisk to systematically identify potential risks. In particular, we first decouple the embedded ad libraries from their host apps and then apply our system to statically examine the ad libraries for risks, ranging from uploading sensitive information to remote (ad) servers to executing untrusted code from Internet sources. Our results show that most existing ad libraries collect private information: some of this data may be used for legitimate targeting purposes (i.e., the user’s location) while other data is harder to justify, such as the user’s call logs, phone number, browser bookmarks, or even the list of apps installed on the phone. Moreover, some libraries make use of an unsafe mechanism to directly fetch and run code from the Internet, which immediately leads to serious security risks. Our investigation indicates the symbiotic relationship between embedded ad libraries and host apps is one main reason behind these exposed risks. These results clearly show the need for better regulating the way ad libraries are integrated in Android apps.