future: apple-controlled mobile browsing

Imagine that iPhone 2.0 attains the kind of market penetration currently enjoyed by the iPod music player. ... We will have sleep-walked into a different world. How come? Because whereas the personal computer is an open, user-configurable device, the iPhone is a decidedly closed one. Nothing runs on it other than software approved by Apple. This is not because the iPhone is incapable of running complex software: on the contrary, it is, in fact, a powerful Unix computer. But users who treat it as such - for example, by installing 'unofficial' software on it - run the risk of having their device 'bricked' [disabled] the next time they synchronise it with the iTunes software on their PCs.

Of course anyone can write programs for the iPhone with the aid of Apple's (free) Systems Developers Kit. But the only way they can get them installed will be via Apple's 'App Store'. And nothing will get into the store unless it's been approved by Apple.

If Apple's strategy succeeds, an increasing proportion of internet users will access through a gateway entirely controlled by a single company.

From guardian.

Challenges & Drivers for Mobile web 2.0 applications

This whitepaper categorizes mobile web 2.0 applications by three verbs - share, collaborate, exploit. For example, in location-based services, users share their location with others, collaborate with those narby and exploit local knowledge.

Challenges
* Telcos control the distribution channel and content on it.
-> It's impossible for small start-ups and developers to innovate
* Flat-rate data pricing undermines revenues
* Don't exist performance analytics for advertisers

Drivers
* Offer new ways to deliver ads
* Anywhere/anytime accessibility of mobile phones
* Convergence of mobile & web worlds
* Flat-rate pricing (cheaper and more transparent for customers)
* If operators' portals will be open --> each operator can search beyond its portal

Mobile Cultures

It is tempting to look at Japan (and Tokyo in particular) as a vision of the future for other countries or cities. ... However, there are more fundamental aspects of a society that cannot be disentangled from their attitudes and integration of technology.

Firstly, Tokyo is all about public transport. Trains run at minute intervals and are packed. Public transport is prime info-snacking space.

Secondly, population density in Tokyo results, obviously, in small accommodations. One consequence of this is that people, and young people in particular, spend a lot of time outside". More.

Branding Yourself With A Blog

" Certainly personal branding isn't a new concept, but the future of personal branding could be in at your fingertips with a blog. One of the first steps in creating a brand for yourself is to make your blog visible. Post meaningful entries, comment on your industry's top blogs, or simply gain a regular readership. Visibility creates opportunities" says Schawbel, a social media specialist at EMC Corporation. He believes that when you brand yourself, the competition becomes irrelevant. "The goal of personal branding is to be recruited based on your brand, not applying for jobs," Schawbel says. "

Seeing Our Signals: Combining location traces and web-based models for personal discovery

Here is the paper.

By combining web applications and mobile phones, they are developing algorithms for implementing a Personal Environmental Impact Report (PEIR). PEIR is a mechanism for longitudinal documentation of both impact—what an individual does to the environment—and what the environment does to the individual, or exposure.

Eigen-Trend: Trend Analysis in the Blogosphere based on Singular Value Decompositions

Here is the paper.

Situation: The blogosphere provides free large-scale information sources from which businesses can quickly learn trends (e.g., opinions and complaints from their customers). How? For example, by keeping track of how often relevant keywords are mentioned across blogs (summing up the occurrence of keywords).

Complication: This simple way of extracting trends has tree problems:
1) Different blogs contribute to the trend differently.
2) For the same keyword, different groups of blogs may have different interests.
3) Can we directly study and extract meaningful trends from such a dynamically changing blog graph structure? The blogosphere can be considered as a blog graph where the nodes are blogs and the links reflect endorsements and interactions among blogs. In addition, such a blog graph is changing with time as a result of the development of internal relationships (e.g., interactions among blogs) and external events (e.g., breaking news).

Solution: The authors propose eigen-trends, temporal indicators derived through singular value decomposition, that take differences among individual blogs in consideration. The key idea is to represent the observed data as a combination of information that captures temporal changes of the underlying data (i.e., eigen-trends) and information that captures the characteristics of individual bloggers (e.g., authority).

Boosting Topic-Based Publish-Subscribe Systems with Dynamic Clustering

Great paper.

Problem: The maintenance overhead of a topic-based pub-sub system becomes particularly dominating when the system supports a large number of topics with moderate event frequency (e.g., news syndication scene).

Fact: One can typically detect correlations between users subscriptions, which can be used to group topics and reduce the overall maintenance cost. For instance, users that are subscribed to updates for a given piece of software (say the free bitmap image editor GIMP [25]) are likely to be also subscribed to updates of other software pieces on which the given software depends (e.g. GTK+, libart and Pango [9]).

Proposal: A dynamic distributed clustering algorithm that

+ utilizes correlations between user subscriptions to dynamically group topics together, into virtual topics (called topic-clusters).

+ continuously adapts the topic-clusters and, resp., the user subscriptions, to the changing system state by employing local cluster updates. Each local update is performed only when it is estimated to be (globally) cost effective. Furthermore, to minimize the overhead involved in gain estimations, a probabilistic component is employed to guarantee that (with high probability) gain estimation are computed only for updates that are likely to be beneficial.