Tasks

1. Fix minor issues in the document.
2. Start doing some simple experiments with the item selection to see if
• discussed methods are able to suggest items that the user knows
• acquisition of this information produces changes in the recommendation list.
3. Add kendale t to the list of methods for comparing lists.
4. Revise the strategy for improving the reliability of neighbors' similarity.
5. Add the strategy for eliciting opinion on items correlated to the best current recommendations.
6. Compute the p value using a different approach for ? (unknown) And ø (a user doesn't have and opinion).
7. Read the Carenini paper one more time and understand the simulation part completely.
8. Look at the abstract that my supervisor has sent for useful papers.
9. Look at the literature for predicting if a user has/doesn't have an opinion about an item.

Current Tasks

1. Fix minor issues in the document.
2. Correct the utility computation formula.
3. List other possible ways to compute the effect of a new rating in the output.
4. Include some methods for item selection not based on the effect of the rating on the prediction:
   • entropy
   • increase overlap with users
   • most controversial
   • items more correlated with best predictions
   • items with worst predictions
   • items with best and with worst predictions
5. Compute the p value using a different approach for ? (unknown) And ø (a user doesn't have and opinion).
6. Read the Carenini paper more carefully.
7. Look at the abstract that my supervisor has sent for useful papers.
8. Look at the literature for predicting if a user has/doesn't have an opinion about an item.
9. Start doing some simple experiments with the item selection to see if
   • discussed methods are able to suggest items that the user knows
   • acquisition of this information produces changes in the recommendation list.