Increasing the expression power of persons' profiles in semantic social networks

The amount of social information published in the Web has dramatically increased in the past years. FOAF, Dublin Core, and vCard are examples of popular vocabularies that are used to present computer understandable profiles of persons in social media. These profiles describe facts about a person such as his or her interests, and thereby we can easily find persons having the same interests. However, in reality we are rather interested in about the closeness of persons' interests than whether they have precisely the same interests. Such aspects are easily understandable for humans but they are not machine understandable without additional semantics. Therefore we have extended the vocabularies of social media by domain specific taxonomies. In addition, to increase the expression power of persons' profiles we have also attached weights to persons' interests. We have also consider a variety of ways for expressing and computing the closeness of weighted profiles.