Archive for the ‘cmueller’ Category

Adaptive Treemap Based Navigation Through Web Portals

Tuesday, October 7th, 2008

Presentation by Sirko Schindler (University of Jena) at Lernen, Wissen, Adaptivität (LWA 2008), University of Würzburg, 6.-8. October 2008. Track: ABIS (collaboration with Andreas Nauerz). (see paper)

Treemaps were proposed by Johnson & Schneiderman in 1991. The author propose adaptive treemaps – displaying different treemaps to different users – to improve the navigation in web portals. To test several algorithms, the author developed a prototype, which is embedded into the IBM WebSphere Portal.

Making Legacy LMS adaptable using Policy and Policy templates

Tuesday, October 7th, 2008

Presentation by Arne Koesling at Lernen, Wissen, Adaptivität (LWA 2008), University of Würzburg, 6.-8. October 2008. Track: ABIS

Focus: Introduce Adaptability into regular Learning Management Systems (LMS) – introduce sophisticated rule systems (policies) that allow all stakeholders (learners , teachers, system admins) to adapt the system for their needs.

Policies are statements that define the behaviour of the system and are intended to guide decisions and actions. There are also known as business rules. For example: “New customers have to pay in advance, regular customers are allowed to pay after delivery” or “point all users to the basic material, if they enter the course the first time and notify all tutors”. Policies are dynamic, declarative, reusable, have a well-defined semantics, and allow for reasoning.

The author chose Protune as policy language, which additionally supports negotiations, explanations and integration with external sources (see concrete examples in Protune on the w3.org website).

Adaptive Portals: Adapting and Recommending Content and Expertise

Tuesday, October 7th, 2008

Presentation by Andreas Nauerz (IBM, University of Jena) at Lernen, Wissen, Adaptivität (LWA 2008), University of Würzburg, 6.-8. October 2008. Track: ABIS (see paper)

Focus: Improving accessibility of web portals. Company web portals (Enterprise Information Portals) often include immense corpora of contents, which are hardly ever used by the user as selection and navigation is often too tedious. Main concepts of the authors have been integrated in the IBM WebSphere Portal.

The author propose a complex user and context model (date, time, location). The user model reflect the user’s interest and preference: Information from static profiles (native language, home country, working location, age, …), the user’s interaction behaviour (pages and portlets they work with, tags users apply to resources); and the user’s social networks are used to derive knowledge on the user’s needs. For example, the user model includes information on the tagging, rating, and commenting behaviour of users: Tagging and rating behaviour are analysed to understand interest and preference of single users and entire communities. The static data is entered by the user, while more dynamic data is extracted from the user interaction using web usage mining.

Based on the user models two main services are provided:

  • Content adaptation: navigation and page layouts (improve accessibility of contents that users frequently use; make more content accessible but adapting its structure/ layout and make its relevance obvious to the user)
  • Content recommendation: based on background information, related content, or activities of experts and similar behaving users (make recommendation of new material, which relevance is not obvious to the user)

Three independent context profile are created: (1) travelling, (2) office, (3) at home: User activities during are only stored in the respective context. For example, activity during travelling do not influence the user modelling for office work or at home.

Tags can be associate to web pages, documents, fragments of pages (very granular). They can be typed by the users or their semantics can be automatically extracted by calling respective back-end services.

Adaptivity 2.0. – Challenges on the Road ahead to Next-Generation Adaptive Systems

Tuesday, October 7th, 2008

Keynote Alexandros Paramythis Lernen, Wissen, Adaptivität (LWA 2008), University of Würzburg, 6.-8. October 2008. Track: ABIS (see slides)

Current focus of Alexandros Paramythis:

  • Adaptation on the basis of collaborative user activities
  • Meta-Adaptivity
  • Evaluation of Adaptivity (see also Stephan Weibelzahl)

Focus of the talk: Is the research community on user modelling and adaptivity still relevant and (if so) in what ways?

Netflix Prize: The competition on improving Netflix’s accuracy of the prediction by 10% gives as insights in the maturity of the community. It was not possible to make the improvement of 10% immediately, indicating some level of maturity. But still the community is not yet mature enough as a 10% improvement is still consider realistic (in contrast to more mature communities such as the database researchers).

Web 2.0 paradigms: Bringing user participation and contribution to Web 2.0 content. The emphasis is on social behaviours/ online ways to connect with people with similar interest. Two aspects: (1) creating social graphs (networks) summarizing relation between people and (2) creating tag clouds to summarize relations between concepts (expressing people’s interest via their tags). Both structures can get unwieldy – so the challenge is to filter and adapt these structures. Researchers are starting on personalization of tag clouds and social networks now.

Are adaptive hypermedia different to adaptive systems? Is this really an important question to ask? Or should we no longer distinguish these two fields?

Some under-explored adaptivity topics are: (1) social dimension of users; (2) collaboration/ cooperation; and (3) user activities.

How does user profile change in Web2.0? Are we (in academia) aware of approaches in industry? There is almost no cooperation between academia and industry although the latter came up with several de facto standards:

  • DataPortability initiative: “Data Portability is the option to use your personal data between trusted applications and vendors.”
  • OpenSocial (promoted by Google): “OpenSocial defines a common API for social applications across multiple websites. With standard JavaScript and HTML, developers can create apps that access a social network’s friends and update feeds.”
  • OpenID: “OpenID is a shared identity service, which allows Internet users to log on to many different web sites using a single digital identity, single sign-on, eliminating the need for a different user name and password for each site.”
  • APML – Attention Profiling Mark-up Language: “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.”

Adaptivity in Ubiquity: We have to address new adaptive scenarios. Also here industry has contributed already: see e.g. IBMS emotion mouse; see Geotagging

Ubiquity in adaptive eLearning: Computer have turned into tutors almost as good as human instructors. But mist learning takes place outside the classroom. We can not easily observe these learning processes; adaptive system do not support these informal and hidden learning processes.

Security Concerns: Some adaptation algorithms are to weak (see Amazon … case). We can strengthen the algorithms and/or increase the investment required for significant effects to the system’s adaptive behaviour.

Quality: Adaptation quality is an illusive goal as it is hard to define it (harder than e.g. interaction quality). Moreover, the success of adaptation often depends on the application domain and the overall experience of the user. Thus, evaluation adaptation is difficult (see Stephan Weibelzahl). We need to isolate adaptation from the other components to measure its impact without the influence of other aspects of the system (e.g. the user model or user interface).

The adaptation and user modelling community is a rather closed community. Access to publication is limited due to copy rights. Moreover, researchers tend to reinvent the wheel over and over again. Industry is completely ignored although they already widely use their de facto standards like OpenID … We should become aware of this and start to considering existing industrial approaches as well as start collaborations between industry and academia.

Development, Continuity, and Connectivity of Scientific Communities

Monday, September 29th, 2008

Research by Andrea Kienle and Martin Wessner

I have been following the work by Kienle and Wessner during my analysis of related work in the area of scientific communities of practice. I want to point to the design patterns listed by the authors as I find them particularly interesting in the discussion on the future of the open knowledge society and its venues.

  • Smooth transitions between different degrees of participation: New people with new ideas should be able to join the community as easily as possible; already existing members should be able to participate over a period of time on different levels.
  • Networking of local coordinators: Local coordinators influence by their publications, lectures, and advice how other work is perceived by their fellows.
  • Rotation of meeting locations: To provide low barriers for new people living near the meeting location to enter the community.
  • International program committees: committee members distribute information about the conference locally and encourage people from their local networks to submit to the conference. International program committees may thus lead to more international group of authors.

These principles have been based on an empirical study and biometric analysis of the CSCL community as well as conceptual work by Etienne Wenger et Al.. The design principles have been applied to propose a community platform for the CSCL community. A community platform might also be potentially useful to foster the the exchange and discussion in the knowledge society.

For more detailed information see:

Semantic Tagging: Some thoughts after the WSKS on tagging

Monday, September 29th, 2008
  • Tagging is used to structure content (e.g. to generate personalized sequences of lecture material)
  • Social tagging = collaborative structuring of content
  • Tags attach specific information to an object
  • Tags are usually keywords
  • Tagging creates a common vocabulary, in social tagging this is also referred to as folksonomy
  • My suggestions: Towards a more sophisticated (semantic) tagging: i.e. tags are semantic concepts, such as mathematical symbols (e.g. represented in OpenMath or (content) MathML) with commonly agreed on or private definitions, which are stored in Content Dictionaries
  • But: Maybe this conflicts with the definitions in the inclusive tagging paper (WSKS) as the authors distinguish between different levels of annotation (from tag to formal metadata). But considering the very general definition of “tagging is attaching specific information to an object”; we might want to include semantics concepts as potential tag-categories.
  • We provide a corpus of semantically marked up documents in the OMDoc format and respective workflows which allow the automatic extraction of mathematical symbols (which we want to use as semantic tags). For example, the panta rhei system provides an import for OMDoc during which it extracts all symbols; we simply need to memorizes the relation of symbols and the imported content snippets to provide the respective tags.
  • Moreover, I suggest to distinguish two types of semantic tags: acquired symbols and required symbols (prerequisites). Based on our OMDoc markup we can identify which symbols are required for the illustration in a mathematical theory and which symbols are acquired when studying the theory: Required symbols are specified via the OMDoc import-elements (which imports symbols from another mathematical theory) and acquired symbols, which are simply all remaining symbols that are not imported from other mathematical theories. Acquired symbols are defined/ introduced in the given theory.
  • Based on the extracted tag, we can visualize tag clouds for each content (e.g. in panta rhei)
  • We should also provide a user interface for creating tags:
    • Users can associate symbols to content snippets in the system (in particular to non-semantic content such as the forum, the library entries, manually entered problems — this allows us to use the semantic objects to bring order/structure in the collection of non-semantic content);
    • Users can create new tags (new symbols); this interface needs to be very intuitive, easy, and usable.
    • Maybe we can also allow users to use keywords for tagging: But these are non-semantic tags and should be disntiguished
  • Based on tagging-structure we can implement tag-based browsing: Given a tag cloud; the selection of a tag provides (i) all resources tag with this tag and (ii) all users that used this tag; clicking on a resources provides the collection of all tags of this resources and the collection of all users that tag this resource; selecting a user provides all his tags and tagged resources …
  • However: the tagging of non-semantic content restricts the granularity of the tags (as we cannot annotate fine granular content inside e.g. a post, we do not have IDs; maybe we have to consider a different annotation approach – e.g. based on xpointer as annotae is doing it); However, for now we neglect the granularity. If a posting annotates a content, we extract the symbols of the annotated area and use them to automatically tag the posting; if the posting links to other content we propagate the tags to this content

Further Readings

  • How do others define/ interpret semantic tags? e.g. see [1]; [2]; [3] (German)

Educational Games Design Issues: Motivation and Multimodal Interaction

Monday, September 29th, 2008

Presentation by Mladjan Jovanovic at the 1st World Summit of the Open Knowledge Society, Athens, 24-26 September 2008. Track: Knowledge, Learning, Education, Learning Technologies, and eLearning for the Knowledge Society.

Unfortunately I missed this talk as it was in parrallel to my session. The authors present a framework that based on user profiles generates user-adaptive educational games. They base their user profile on psychological studies of motivation and social behaviour (see below) and apply the Self-Determination Theory, which provides the following classification of motivation:

  • Intrinsic: motivtion is not based on any external benefits, inherint satisfaction
  • Extrinsic: performance for outcome (money, rewards)
  • Amotivation: absence of motivation

I would be glad to read further papers on their work and to see an example of various games for the different user profiles they identify and construct.

Further Reading:

Social Recommendations within the Multimedia Sharing System

Friday, September 26th, 2008

Presentation by Przemyslaw Kazienko at the 1st World Summit of the Open Knowledge Society, Athens, 24-26 September 2008. Track: Social & Humanistic Computing for the Knowledge Society: Emerging Technologies and Systems for the Society and Humanity.

Two users participate in common activity related to the certain object with the same/ different role a: e.g. two users comment on the same image. The weights of relations depend on intensity, frequency and quantity. Distinction of different layers of the social network: contact lists, tags, groups, favourites, opinions, multi relational social network. Some layers have rather social (contacts, opinion-author, author-opinion); others have more semantic relations (tags, opinion-opinion relation).

The goal of the system is to recommend people to people. First relations are extracted – building the different layers of the social network (distinction between direct relations (contacts) and object-based relations (tags, opinions, favourites, groups). Based on the layers we create weights for the importance of each layer (consisting personal weight = the user’s individual weight of the user for each layer; and a system weight = aggregation over all users). Afterwards, a social filtering is applied: that is rejection based on the user’s contact lists; rejection of users blocked by the user, damp already viewed users. Rotation mechanism for more random results. Finally, the recommendation is presented to the user. Users are then asked to rate the recommendations.

The Bottleneck of the Knowledge Society

Friday, September 26th, 2008

Presentation by Michal Zemlicka (Charles University Prague; Faculty of Mathematics and Physics; Department of Software Engineering) at the 1st World Summit of the Open Knowledge Society, Athens, 24-26 September 2008. Track: Social & Humanistic Computing for the Knowledge Society: Emerging Technologies and Systems for the Society and Humanity.

Problem: STEM disciplines are very unpopular. Scientists and engineers are usually presented as crazy. Learning STEM is quite hard and requires hard work (and some minimal talent). STEM are taught less than before. Educated and well prepared teachers are required and they are expensive. Labs are expensive. People able to teach STEM can succeed also in other profession (we are lacking STEM specialists).

Approach to change the public opinion: The authors propose to create a system showing how successful alumnies of different school have become. They want to show that the knowledge of mathematicians is an advantage for being employed and having big income (tax statements).

Limits: All technical issues seem to have solved (architecture, certification, encryption, privacy). The main problem is that the use of the existing data is prohibited by law. There will be a powerful lobby of poor schools against such a system.

The authors want to prove the quality of an educational system by using the average success of alumnies. In the discussion it was criticized that “employment” is a rather poor parameter for a complex system such as education and that a more sophisticated approach needs to be taken.

Online Social Networks: Why do “we” use facebook?

Friday, September 26th, 2008

Presentation by Pui-Yee Chiu at the 1st World Summit of the Open Knowledge Society, Athens, 24-26 September 2008. Track: Social & Humanistic Computing for the Knowledge Society: Emerging Technologies and Systems for the Society and Humanity.

see also Do we know how to use facebook?