Skip to main content

Home/ PEERS ONLINE INTERACTION FRAMEWORK/ Group items tagged algorithm

Rss Feed Group items tagged

Thieme Hennis

Towards the semantic web: Collaborative tag suggestions - 0 views

  •  
    Yahoo! employee describes and defines criteria and algorithms for a collaborative tag system: Since tags are created by individual users in a free form, one important problem facing tagging is to identify most appropriate tags, while eliminating noise and spam. For this purpose, we define a set of general criteria for a good tagging system. These criteria include high coverage of multiple facets to ensure good recall, least effort to reduce the cost involved in browsing, and high popularity to ensure tag quality. We propose a collaborative tag suggestion algorithm using these criteria to spot high-quality tags.
  •  
    another one about tagging: describes criteria for a good tagging system.
Thieme Hennis

Eigentaste - 0 views

  •  
    Eigentaste is a collaborative filtering algorithm that uses universal queries to elicit real-valued user ratings on a common set of items and applies principal component analysis (PCA) to the resulting dense subset of the ratings matrix. PCA facilitates dimensionality reduction for offline clustering of users and rapid computation of recommendations. Eigentaste was patented by UC Berkeley in 2003. It has many possible applications, such as the recommendation of books, movies, toys, stocks, and music. It was originally used in an online joke recommendation system called Jester, which recommends new jokes to users based on their ratings of an initial set.
Thieme Hennis

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

  •  
    This paper describes a technique for making personalized ecommendations from any type of database to a user based on similarities between the interest profile of that user and those of other users.
  •  
    algorithme beschreven..
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.
  •  
    article about social information filtering: items are recommended based upon values assigned by other people with similar taste.
Thieme Hennis

Improving Tag-Clouds as Visual Information Retrieval Interfaces - 0 views

  •  
    This paper presents a novel approach to Tag-Cloud's tags selection, and proposes the use of clustering algorithms for visual layout, with the aim of improve browsing experience. The results suggest that presented approach reduces the semantic density of tag set, and improves the visual consistency of Tag-Cloud layout.
  •  
    handig.. een alternative manier om tag-clouds te maken. makes sense.
Thieme Hennis

Intelligent Agents: Theory and Practice - 0 views

  •  
    overview of agent theory and practice
  •  
    The concept of an agent has become important in both Artificial Intelligence (AI) and mainstream computer science. Our aim in this paper is to point the reader at what we perceive to be the most important theoretical and practical issues associated with the design and construction of intelligent agents.
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.
  •  
    interesting blog post about the need for syndicated web ratings.
  •  
    heel interessant idee, zeer veel raakvlak met Peers IMS.
Thieme Hennis

Scoutle - Homepage - 0 views

  •  
    interessant initiatief.
  •  
    interesting Dutch startup trying to let blogs evolve into social networks..
Thieme Hennis

Building A Smarter Corporation - Forbes.com - 0 views

  • Tacit's software, when installed in an enterprise, interacts with the e-mail system on every employee's desk and "learns" their expertise. No, it is not LinkedIn, where all individuals need to feed in their resumes and thereby "announce" their expertise. Tacit's artificial intelligence algorithms work in the background, reading all your e-mail exchanges, noting who you correspond with, how often and on what topics, and in this way, it creates a personalized profile of your areas of knowledge. Tacit's software includes privacy controls, so no one can access your profile without your permission.
    • Thieme Hennis
       
      kijk, dit bedoel ik nu. het is dus niet actief bijhouden wie en wat je bent, maar meer passief (en automatisch) dit laten uitrekenen door de software.
  •  
    interesting article about smart social enterprises. Tacit Software as an example.
1 - 9 of 9
Showing 20 items per page