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Thieme Hennis

The Web of Identities: Making Machine-Accessible People Data - 0 views

  • In the future, ID providers will loosen their connection to social applications and start taking over management of users' social attributes. Users will be able to log in to applications using credentials hosted by their ID providers of choice and grant permissions to these applications to read or even sync selected fragments of their profile data. The borders of these walled gardens will thus blur, and the social Web will become more of a weave than a patchwork quilt.
  • In the future, ID providers will loosen their connection to social applications and start taking over management of users' social attributes. Users will be able to log in to applications using credentials hosted by their ID providers of choice and grant permissions to these applications to read or even sync selected fragments of their profile data. The borders of these walled gardens will thus blur, and the social Web will become more of a weave than a patchwork quilt.
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    In the future, ID providers will loosen their connection to social applications and start taking over management of users' social attributes. Users will be able to log in to applications using credentials hosted by their ID providers of choice and grant permissions to these applications to read or even sync selected fragments of their profile data. The borders of these walled gardens will thus blur, and the social Web will become more of a weave than a patchwork quilt.
Thieme Hennis

Citizendium Blog » Syndicated Web ratings - an idea whose time has come? - 0 views

  • (c) Moreover, a feed could have meta-data about the person doing the rating, listing facts like education level, age, ethnicity, political views, or whatever a person might feel is relevant.
  • (4) Search engines then use the data aggregated by the registrar(s). Due to the quantity and variety of data published in the aggregated feeds, it becomes possible to weight and filter search results not just on Google-style pagerank algorithms, but also things like: (a) quality according to generally trusted sources; or quality according to your peer group; or quality according to academic and academic-endorsed sources; etc.
  • Moreover, with data included in the feed about the rater, we would be enabled to see, for any given search, what the top rated websites were for our peer group. How teenage girls rate a news article might differ greatly from how 40-year-old men rate them — and this would be useful data for both groups to have.
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    interesting blog post about the need for syndicated web ratings.
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    heel interessant idee, zeer veel raakvlak met Peers IMS.
Thieme Hennis

Folksonomies-Cooperative Classification and Communication Through Shared Metadata - 0 views

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    This paper examines user-generated metadata as implemented and applied in two web services designed to share and organize digital me- dia to better understand grassroots classification. Metadata - data about data - allows systems to collocate related information, and helps users find relevant information.
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    another article about folksonomies and tagging..
Thieme Hennis

Credit Scoring, Data Mining, Predictive Analytics, Statistics, StatSoft Electronic Text... - 0 views

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    This Textbook offers training in the understanding and application of statistics. The material was developed at the StatSoft R&D department based on many years of teaching undergraduate and graduate statistics courses and covers a wide variety of applications, including laboratory research (biomedical, agricultural, etc.), business statistics, credit scoring, forecasting, social science statistics and survey research, data mining, engineering and quality control applications, and many others. The Electronic Textbook begins with an overview of the relevant elementary (pivotal) concepts and continues with a more in depth exploration of specific areas of statistics, organized by "modules," accessible by buttons, representing classes of analytic techniques. A glossary of statistical terms and a list of references for further study are included.
Thieme Hennis

yiid - Your Internet ID - 0 views

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    Welcome to yiid.com - A new service developed to help you build a social identity you can take with you on the web. You don't like to fill in your data again and again and you are fed up with regathering your contacts every now and then. Shortly you will be able to hop through communities using our openID (Yiid) and take along your data. JOIN NOW !
Thieme Hennis

Web Technology Trends for 2008 and Beyond - 0 views

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    PRESENTATION: Richard MacManus looks at the top trends covered on ReadWriteWeb in early 2008; such as Websites becoming web services, Semantic Apps, Open Data, Mobile Web, Recommendation Engines.
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    PRESENTATION: Richard MacManus looks at the top trends covered on ReadWriteWeb in early 2008; such as Websites becoming web services, Semantic Apps, Open Data, Mobile Web, Recommendation Engines. >> overview
Thieme Hennis

Mediamatic - Interfacing to anyMeta - 0 views

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    Accessing semantic data using anyMeta
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    de aanpak van mediamatic om data te retrieven uit andere systemen.
Thieme Hennis

iCharts | create, share, and embed interactive charts online - 0 views

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    data visualization
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    misschien handig zolang we nog geen datavisualisator hebben... :)
Thieme Hennis

sioc-project.org | Semantically-Interlinked Online Communities - 0 views

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    mogelijk interessant framework.. interlinking communities...
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    What is SIOC? The SIOC initiative (Semantically-Interlinked Online Communities) aims to enable the integration of online community information. SIOC provides a Semantic Web ontology for representing rich data from the Social Web in RDF.
Thieme Hennis

Socialstream - 0 views

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    ontwikkelingen in social networking (aggregated)
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    a unified social network that, as a service, provides social data to many other applications
Thieme Hennis

APML - Attention Profiling Mark-up Language: The open standard for Attention Metadata - 0 views

    • Thieme Hennis
       
      ik begrijp de volgorde niet.. xml moet toch in het midden?
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    APML allows users to share their own personal Attention Profile in much the same way that OPML allows the exchange of reading lists between News Readers. The idea is to compress all forms of Attention Data into a portable file format containing a description of ranked user interests.
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    heel erg relevant. mooie ontwikkelingen. goed in de gaten houden.
Thieme Hennis

gRSShopper - 0 views

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    ntrstng
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    gRSShopper is a personal web environment that combines resource aggregation, a personal dataspace, and personal publishing. It allows you to organize your online content any way you want to, to import content - your own or others' - from remote sites, to remix and repurpose it, and to distribute it as RSS, web pages, JSON data, or RSS feeds.
Thieme Hennis

[true knowledge]™ - home - 0 views

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    PRESENTATION: Richard MacManus looks at the top trends covered on ReadWriteWeb in early 2008; such as Websites becoming web services, Semantic Apps, Open Data, Mobile Web, Recommendation Engines. Our initial products are: * The True Knowledge Answer Engine - a search engine-like consumer site which can answer questions, be used to add knowledge and also be used just like a conventional search engine. * an API product for computer-generated queries.
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    search engine technology +++
Thieme Hennis

Engagd.com - 0 views

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    even induiken wat het allemaal betekent..
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    Bundle of identity, trust, profiling, and attention services.. INTERESTING!!!!!! OpenID Use this service to quickly and easily create your own OpenID Account. Profiler Feed the AttentionProfiler your Attention Data and it will update your APML file. Developers Consume Engagd Web Services through your App or Mashup to instantly add Attention Awareness. ItemRank Give ItemRank a piece of content and it will return a Personal Relevancy Rank based on your APML file (+ other things) More coming... This is just the beginning. We will be adding more services soon.
Thieme Hennis

Finding Communities of Practice from User Profiles Based On Folksonomies - 0 views

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    User profiles can be used to identify persons inside a community with similar interests. Folksonomy systems allow users to individually tag the objects of a common set (e.g., web pages). In this paper, we propose to create user profiles from the data available in such folksonomy systems by letting users specify the most relevant objects in the system. Instead of using the objects directly to represent the user profile, we propose to use the tags associated with the specified objects to build the user profile. We have designed a prototype for the research domain to use such tag-based profiles in finding persons with similar interests. The combination of tag-based profiles with standard recommender system technology has resulted in a new kind of recommender system to recommend related publications, keywords, and persons.
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    user profiles based on tagging
Thieme Hennis

Social Information Filtering: Algorithms for Automating "Word of Mouth'' - 0 views

  • Social Information filtering essentially automates the process of ``word-of-mouth'' recommendations: items are recommended to a user based upon values assigned by other people with similar taste. The system determines which users have similar taste via standard formulas for computing statistical correlations.
    • Thieme Hennis
       
      dit gebeurt bij Last.fm, Amazon, etc...
  • need not be amenable to parsing by a computer
  • may recommend items to the user which are very different (content-wise) from what the user has indicated liking before
  • ...5 more annotations...
  • ecommendations are based on the quality of items, rather than more objective properties of the items themselves
  • The basic idea is: The system maintains a user profile, a record of the user's interests (positive as well as negative) in specific items. It compares this profile to the profiles of other users, and weighs each profile for its degree of similarity with the user's profile. The metric used to determine similarity can vary. Finally, it considers a set of the most similar profiles, and uses information contained in them to recommend (or advise against) items to the user.
  • One observation is that a social information filtering system becomes more competent as the number of users in the system increases.
  • The system may need to reach a certain {\em critical mass} of collected data before it becomes useful.
  • Finally, we haven't even begun to explore the very interesting and controversial social and economical implications of social information filtering systems like Ringo.
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    article about social information filtering: items are recommended based upon values assigned by other people with similar taste.
Thieme Hennis

Dave Snowden interviewed by Jon Husband - Knowledge Jolt with Jack - 0 views

  • Context is usually removed when you remove the human element, whether that is by archiving best practices to a "database," or by asking experts to "tell me what you know" about a given topic, or assuming knowledge is a fixed thing as opposed to an interconnected flow of many things.
  • The Web 2.0 aspect gives you the ability to pull together knowledge from many different sources, independent of how it was generated.  The implication of this for businesses is that they should focus on their business processes and making sure they have access to that knowledge (i.e. the people).
  • Open up the business to any applications that provide these knowledge flows; ban email attachments (forcing people to use blogs / wikis / etc); and lock down truly proprietary data. 
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    KM and Web 2.0
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    Dave Snowden interviewed by Jon Husband
Thieme Hennis

QuarkBase : Everything about a Website - 0 views

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    Interessante tool
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    Cool tool that analyzes websites, how they are used and talked about online.
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