M.Sc. (Information Technology) / Recommender systems assist a system user to identify relevant content within a specific context. This is typically performed through an analysis of a system user’s rating habits and personal preferences and leveraging these to return one or a number of relevant recommendations. There are numerable contexts in which recommender systems can be applied, such as movies, tourism, books, and music. The need for recommender systems has become increasingly relevant, particularly on the Internet. This is mainly due to the exponential amount of content that is published online on a daily basis. It has thus become more time consuming and difficult to find pertinent information online, leading to information overload. The relevance of a recommender system, therefore, is to assist a system user to overcome the information overload problem by identifying pertinent information on their behalf. There has been much research done within the recommender system field and how such systems can best recommend items to an individual user. However, a growing and more recent research area is how recommender systems can be extended to recommend items to groups, known as group recommendation. The relevance of group recommendation is that many contexts of recommendation apply to both individuals and groups. For example, people often watch movies or visit tourist attractions as part of a group. Group recommendation is an inherently more complex form of recommendation than individual recommendation for a number of reasons. The first reason is that the rating habits and personal preferences of each system user within the group need to be considered. Additionally, these rating habits and personal preferences can be quite heterogeneous in nature. Therefore, group recommendation becomes complex because a satisfactory recommendation needs to be one which meets the preferences of each group member and not just a single group member. The second reason why group recommendation is considered to be more complex than individual recommendation is because a group not only includes multiple personal preferences, but also multiple personality types. This means that a group is more complex from a social perspective. Therefore, a satisfactory group recommendation needs to be one which considers the varying personality types and behaviours of the group. The purpose of this research is to present PerTrust, a generic framework for group recommendation with the purpose of providing a possible solution to the aforementioned issues noted above. The primary focus of PerTrust is how to leverage both personality and trust in overcoming these issues.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uj/uj:11648 |
| Date | 01 July 2014 |
| Creators | Leonard, Justin Sean |
| Source Sets | South African National ETD Portal |
| Detected Language | English |
| Type | Thesis |
| Rights | University of Johannesburg |
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