Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.
Survival of the Fittest – Utilization of Natural selection Mechanisms for Improving PLE <ul><li>Behnam Taraghi,  Christian...
http://ple.tugraz.at Mashup of widgets
Darwin’s theory <ul><li>- Survival of the fittest </li></ul><ul><li>- Selection, Variation </li></ul><ul><li>- Macro evolu...
Selections <ul><li>Evolution theory of natural selections: </li></ul><ul><ul><li>- Reproduction rate </li></ul></ul><ul><u...
Selection Mechanisms* Stabilizing Selection : - Favorites the average. - Decrease of variability within the population.  <...
r/K Selection Theory* Tradeoff btw.  quantity  &  quality  of offspring In long term K-strategy is superior. Quality succe...
Variations <ul><li>Shift in genotypes or generic sequence </li></ul><ul><li>Mutation : </li></ul><ul><ul><li>Random proces...
Tracking module in PLE <ul><li>Tracks users’ behavior on widgets </li></ul><ul><li>Deep retrieve of statistics data </li><...
Conclusion & Future Work <ul><li>Tracking module helps </li></ul><ul><ul><li>To get knowledge about user behavior </li></u...
SOCIAL LEARNING Computer and Information Services http://tugraz.at http:// elearning .tugraz.at Slides available at:  http...
Upcoming SlideShare
Loading in …5
×

Survival of the Fittest – Utilization of Natural selection Mechanisms for Improving PLE

1,950 views

Published on

Published in: Education, Technology
  • Login to see the comments

Survival of the Fittest – Utilization of Natural selection Mechanisms for Improving PLE

  1. 1. Survival of the Fittest – Utilization of Natural selection Mechanisms for Improving PLE <ul><li>Behnam Taraghi, Christian Stickel, Martin Ebner </li></ul>
  2. 2. http://ple.tugraz.at Mashup of widgets
  3. 3. Darwin’s theory <ul><li>- Survival of the fittest </li></ul><ul><li>- Selection, Variation </li></ul><ul><li>- Macro evolution </li></ul><ul><li>- Micro evolution </li></ul>
  4. 4. Selections <ul><li>Evolution theory of natural selections: </li></ul><ul><ul><li>- Reproduction rate </li></ul></ul><ul><ul><li>- Mortality </li></ul></ul><ul><ul><li>- Population size </li></ul></ul><ul><ul><li>- Environmental capacity </li></ul></ul><ul><ul><li>- Cycle of updates, replacements & new widgets </li></ul></ul><ul><ul><li>- # widgets </li></ul></ul><ul><ul><li>Max # widgets on UI & # users </li></ul></ul>Different probabilities for the survival are the base for the selection mechanism .
  5. 5. Selection Mechanisms* Stabilizing Selection : - Favorites the average. - Decrease of variability within the population. <ul><li>Disruptive Selection : </li></ul><ul><li>Directed against the average. </li></ul><ul><li>Splits the population into new species. </li></ul><ul><li>Directed Selection : </li></ul><ul><li>Works against individuals on one side of distribution. </li></ul>*Solbrig O.T. (1970). Principles and Methods of Plant Biosystematics. The Mac-Millan Company. Collier-Mac Millan Limited, London. *Solbrig O.T. & D.J Solbrig. (1979). Populationbiology and evolution. Addision-Wesley. Publ. Co. Reading Mass.
  6. 6. r/K Selection Theory* Tradeoff btw. quantity & quality of offspring In long term K-strategy is superior. Quality succeeds in long run over quantity. <ul><li>r-Strategy </li></ul><ul><li>Succeeds in unpredictable, unknown environments. </li></ul><ul><li>High reproduction rate – short lifespan </li></ul><ul><li>K-Strategy </li></ul><ul><li>Succeeds in predictable, known environments. </li></ul><ul><li>Constant growth, ruled by population density & env. capacity </li></ul><ul><li>Usually close to the max. capacity </li></ul><ul><li>Slower adaptation – longer lifespan </li></ul>In PLE a mixed approach was applied. *Pianka E.R. (1970). On r and K selection. American naturalist 104, 592-597. *MacArthur, R. and Wilson, E.O. (1967). The Theory of Island Biography, Princeton University Press (2001 reprint).
  7. 7. Variations <ul><li>Shift in genotypes or generic sequence </li></ul><ul><li>Mutation : </li></ul><ul><ul><li>Random process aiming at generation of new alternatives </li></ul></ul><ul><ul><li>Ex. change in DNA structure </li></ul></ul><ul><ul><li>Continuously happening </li></ul></ul><ul><li>Recombination : </li></ul><ul><ul><li>Not random process </li></ul></ul><ul><ul><li>Combining & distributing genetic materials (DNA, RNA) </li></ul></ul>The Evolution never stops. In PLE : slight update of existing functionality or UI In PLE : combining code of different widgets to build new ones
  8. 8. Tracking module in PLE <ul><li>Tracks users’ behavior on widgets </li></ul><ul><li>Deep retrieve of statistics data </li></ul><ul><ul><li>Frequency of widgets usage </li></ul></ul><ul><ul><li>Features used in each widget </li></ul></ul><ul><li>Realized via IWC </li></ul><ul><li>- App. 1000 users registered up to now. </li></ul><ul><li>- App. 30% active users </li></ul><ul><li>- Top 5 most used widgets out of 30: </li></ul><ul><li>- tugWidget, tccourses, tugllBlogs, mail, changeThemeColor </li></ul><ul><li>Top 5 most activated widgets: </li></ul><ul><ul><li>weatherForcast, RSSReader, twitter, TUGLibrary, leoDictionary </li></ul></ul><ul><li>weatherForcast & newsgroup are improved according to K-strategy </li></ul>Most activated widgets are not necessarily most used ones
  9. 9. Conclusion & Future Work <ul><li>Tracking module helps </li></ul><ul><ul><li>To get knowledge about user behavior </li></ul></ul><ul><ul><li>To get user preferences </li></ul></ul><ul><ul><li>To categorize different user groups </li></ul></ul><ul><ul><li>Improve the PLE with variations & selections </li></ul></ul><ul><li>Missing qualitative data </li></ul><ul><ul><li>Qualitative rating system is needed in PLE </li></ul></ul><ul><ul><li>Small feedback questionnaire for each widget </li></ul></ul>
  10. 10. SOCIAL LEARNING Computer and Information Services http://tugraz.at http:// elearning .tugraz.at Slides available at: http:// www.slideshare.net/behi_at b.taraghi(at)tugraz.at

×