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FOKUSday 2009

Friday, 06/19/2009, 22:41:33

Yesterday, it was time for the FOKUSday 2009 in our institute. All competence centers presented their research activities and projects. It was really amazing to see on what kind of projects our institute is working currently. For more information, take a look at the FOKUSday 2009 Flyer of our competence center.

In the evening, we all went to a beach bar, where we ate, drank and showed our skills in a kicker game.

Abdulbaki's Workplace

Author: Abdulbaki[no comments]

Scenario and Product Categorization

Saturday, 05/30/2009, 21:58:54

The scenario of my Master thesis is based on the recommendation of groceries by considering the special eating habits and contextual information of the users:

Bob is vegan and he emphasizes eating healthy food and buying organic products. He enters the desired groceries into the shopping list of the mobile application. Since the special eating habits "vegan, organic" are stored in his profile, the software recommends products for each entry in the shopping list, which fit to his profile. Furthermore it shows, which grocery stores nearby offer these products. In addition, the mobile application considers ratings given before by other users, so that Bob only gets products recommended, which were rated well by them. After buying these groceries, he as well can rate them.

To be able to realize this scenario, it is very important to find a suitable way of storing and categorizing groceries together with their ingredients. After doing research on the web and asking several grocery stores, I have found the following interesting sites:

It is not very easy to find ingredients for groceries on the web, so the best way of getting information on ingredients is to go the grocery store.

Special eating habits are characterized in that way that certain product categories or certain ingredients are not suitable for some consumers. That's why, products and their ingredients have to be connected with user preferences. Semantic ontologies provide a good way of doing that, because they allow to define restrictions on certain classes. Examples for food ontologies are:

Author: Abdulbaki[no comments]

The topic of my Master thesis

Sunday, 04/26/2009, 11:19:38

Sorry for not posting lately, I was busy finding and preparing my master thesis topic. Here, I would like to introduce it to you:

Incorporating contextual information in recommender systems

Today, people are confronted with a large amount of information in the World Wide Web. Receiving a small subset of desired and filtered content through standard search engines turns out to be very difficult. And it becomes quite impossible, if user specific needs and interests should be taken into consideration.
Recommender systems handle this issue by providing personalized content recommendations to the user based on his personal background, preferences and interests.
Numerous recommendation methods were designed over the years to enhance the preciseness of recommendations, such as content-based and collaborative filtering or hybrid approaches.
Even though hybrid methods often deliver acceptable results, incorporating contextual information into the recommendation process may be very important to get more precise results for the situation the user is currently in.
Current recommender systems as described above primarily focus on recommending items to users and vice versa. Existing ratings for items are the basis for effective recommendations. In many modern, mobile applications however, it may not be sufficient to consider only users and items. Contextual information may provide a significant preciseness to the recommendation.
If for example, a user is vegan, eats only organic and healthy food, goes shopping nearby and tries to live economical, it would not make sense to recommend him stores far away or only discounters without taking his preference for vegan food into consideration.

The objective of this thesis is to create a recommendation algorithm using the SMART Recommendations Engine of Fraunhofer FOKUS that incorporates contextual information to deliver more precise results taking users' current situation and preferences into account.
Furthermore a mobile application is to be implemented to demonstrate the recommendation algorithm in a predefined scenario.

Useful papers:

Author: Abdulbaki[no comments]
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