There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Within 15 years the web has grown from a group work tool for scientists at CERN into a global information space with more than a billion users. Currently, it is both returning to its roots as a read/write tool and also entering a new, more social and participatory stage. These trends have led to a feeling that the web is entering a ‘second phase’ – a new, ‘improved’ Web version 2.0. But how justified is this perception?

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What is Web 2.0? Ideas, technologies and implications for education

Online photo services such as Flickr and Zooomr allow users to share their photos with family, friends, and the online community at large. An important facet of these services is that users manually annotate their photos using so called tags, which describe the contents of the photo or provide additional contextual and semantical information. In this paper we investigate how we can assist users in the tagging phase. The contribution of our research is twofold. We analyse a representative snapshot of Flickr and present the results by means of a tag characterisation focussing on how users tags photos and what information is contained in the tagging. Based on this analysis, we present and evaluate tag recommendation strategies to support the user in the photo annotation task by recommending a set of tags that can be added to the photo. The results of the empirical evaluation show that we can effectively recommend relevant tags for a variety of photos with different levels of exhaustiveness of original tagging.

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Flickr tag recommendation based on collective knowledge

This paper presents a traffic characterization study of the popular video sharing service, YouTube. Over a three month period we observed almost 25 million transactions between users on an edge network and YouTube, including more than 600,000 video downloads. We also monitored the globally popular videos over this period of time.In the paper we examine usage patterns, file properties, popularity and referencing characteristics, and transfer behaviors of YouTube, and compare them to traditional Web and media streaming workload characteristics. We conclude the paper with a discussion of the implications of the observed characteristics. For example, we find that as with the traditional Web, caching could improve the end user experience, reduce network bandwidth consumption, and reduce the load on YouTube's core server infrastructure. Unlike traditional Web caching, Web 2.0 provides additional meta-data that should be exploited to improve the effectiveness of strategies like caching.

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Youtube traffic characterization: a view from the edge

We describe an approach for extracting semantics of tags, unstructured text-labels assigned to resources on the Web, based on each tag's usage patterns. In particular, we focus on the problem of extracting place and event semantics for tags that are assigned to photos on Flickr, a popular photo sharing website that supports time and location (latitude/longitude) metadata. We analyze two methods inspired by well-known burst-analysis techniques and one novel method: Scale-structure Identification. We evaluate the methods on a subset of Flickr data, and show that our Scale-structure Identification method outperforms the existing techniques. The approach and methods described in this work can be used in other domains such as geo-annotated web pages, where text terms can be extracted and associated with usage patterns.

Towards automatic extraction of event and place semantics from flickr tags

paper, we describe some promising initial results in inducing ontology from the Flickr tag vocabulary, using a subsumption-based model. We describe the utility of faceted ontology as a supplement to a tagging system and present our model and results. We propose a revised, probabilistic model using seed ontologies to induce faceted ontology, and describe how the model can integrate into the logistics of tagging communities.

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Inducing Ontology from Flickr Tags

This disclosure describes systems, methods and user interfaces that allow a user to identify, annotate and share a portion of a media item with another user. Through the user interface, the user may render a media item and identify a segment of the media item. Based on the media item, previously defined and shared segments may be suggested to the user allowing the user to quickly select and identify popular segments for sharing. In addition, previously used annotations of previously defined and shared segments may be suggested to the user allowing users to quickly select annotations. The sharing user may then issue a command that causes a link or other means for accessing the segment to be transmitted to a recipient. Accessing this link or other means, causes the segment defined by the sharing user to be rendered on the recipient's device.

Method and system for personalized segmentation and indexing of media

An asynchronous adaptive media server mechanism permits a user to navigate around a modelled multimedia space as quickly as input events or instances are handled. The mechanism permits cancellation of outstanding queued requests that have become obsolete as the user navigates out of the area for which the request was needed. A client module generates display requests by defining a client object for every active multimedia instance, and at least one server module acts as a request queue manager and processes the requests. The server module includes a media server that preferably provides service of user-selected quality. Upon request cancellation, client resources can be released immediately; a server state module mechanism may release server resources until there is no risk of endangering system operations. The ability to cancel or de-serialize queued requests permits prioritizing the requests in a fashion that will permit media server performance to be adaptively optimized to match the users' actions. The disclosed mechanism has application to any media that does not have a time-linear nature that maps directly onto some dimension of the modelled space displayed to the user.

Asynchronous media server request processing system for servicing reprioritizing request from a client determines whether or not to delay executing said reprioritizing request

We present a platform for community-supported media annotation and remix, including a pilot deployment with a major film festival. The platform was well received by users as fun and easy to use. An analysis of the resulting data yielded insights into user behavior. Completed remixes exhibited a range of genres, with over a third showing thematic unity and a quarter showing some attempt at narrative. Remixes were often complex, using many short segments taken from various source media. Reuse of spoken and written language in source media, and the use of written language in user-defined overlay text segments proved to be essential for most users. We describe how community remix statistics can be leveraged for media summarization, browsing, and editing support. Further, the platform as a whole provides a solid base for a range of ongoing research into community annotation and remix including analysis of remix syntax, identification of reusable segments, media and segment tagging, structured annotation of media, collaborative media production, and hybrid content-based and community-in-the-loop approaches to understanding media semantics.

Community annotation and remix: a research platform and pilot deployment

Against this backdrop systems and methods have been developed for identifying popular segments of media objects A remix system is provided to users allowing the easy remixing of a library of media objects The remixes created by the users are recorded From this information, the relative popularity of the segments and media objects in the library are identified based on how often they appear in the user-generated remixes Actions may then be automatically taken related to the popularity of segments and media objects such as changing payment terms, alerting users of the popular content, and notifying interested parties of the popular or unpopular content

Patrick Schmitz

Papers

Inducing Ontology from Flickr Tags

Method and system for personalized segmentation and indexing of media

Asynchronous media server request processing system for servicing reprioritizing request from a client determines whether or not to delay executing said reprioritizing request

Community annotation and remix: a research platform and pilot deployment

Identifying popular segments of media objects