Context-aware Mobile Recommender System Based on SNA

This thesis aims to develop context-aware mobile social service as support for research collaboration. For example, in the context of a conference, context-aware mobile services could be very useful for conference participants. They can provide social recommendations to researchers to help them meet each other and allows them to interact on-side.

A Scenario describing the thesis requirements:
"Bob is an academic researcher. As a researcher he has written many papers sent to many conferences, and has collaborated with some other researchers, publishing papers together. Bob participates in academic events not only to present his research work and results, but moreover to meet with other community members and contact with potential collaboration partners.
However, finding the right people and talks in large academic events can be tedious. Therefore, Bob is using his mobile smartphone to access the cloud support services for social interaction on academic events. These services give Bob recommendations about talks and presentations interesting for him, or researchers that have similar research interests. His mobile device senses the current context, such as the event program, location, or other researchers presence. Based on the sensed context, the smartphone  Bob gives  information about the current speaker, including his/her publications, co-authors, research projects, or even common acquaintances. For example, Bob uses the cloud services to find mutual connection between him and a particular participant on the conference; thus potentially easing the first contact between them. The mutual social tie can be a common collaborator, an acquaintance, or a research project."

The applicant will be required to design and implement an recommender services delivered from cloud infrastructure. These services need to integrate the user's context with our existing SNA services ( AERCS ) and deliver them to a mobile smartphone (preferably Android-based).

The diploma/master thesis candidate should have knowledge on databases, Web, and XML technologies. Programming skills in Java are preferred.