Ontology engineering and feature construction for predicting friendship links and users interests in the Live Journal social network

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dc.contributor.author Bahirwani, Vikas
dc.date.accessioned 2008-10-15T14:48:29Z
dc.date.available 2008-10-15T14:48:29Z
dc.date.issued 2008-10-15T14:48:29Z
dc.identifier.uri http://hdl.handle.net/2097/992
dc.description.abstract An ontology can be seen as an explicit description of the concepts and relationships that exist in a domain. In this thesis, we address the problem of building an interests' ontology and using the same to construct features for predicting both potential friendship relations between users in the social network Live Journal, and users' interests. Previous work has shown that the accuracy of predicting friendship links in this network is very low if simply interests common to two users are used as features and no network graph features are considered. Thus, our goal is to organize users' interests into an ontology (specifically, a concept hierarchy) and to use the semantics captured by this ontology to improve the performance of learning algorithms at the task of predicting if two users can be friends. To achieve this goal, we have designed and implemented a hybrid clustering algorithm, which combines hierarchical agglomerative and divisive clustering paradigms, and automatically builds the interests' ontology. We have explored the use of this ontology to construct interest-based features and shown that the resulting features improve the performance of various classifiers for predicting friendships in the Live Journal social network. We have also shown that using the interests' ontology, one can address the problem of predicting the interests of Live Journal users, a task that in absence of the ontology is not feasible otherwise as there is an overwhelming number of interests. en
dc.language.iso en_US en
dc.publisher Kansas State University en
dc.subject Social network analysis en
dc.subject Interest ontology en
dc.subject Clustering en
dc.subject Machine learning en
dc.subject Friendship link prediction en
dc.subject Interest prediction en
dc.title Ontology engineering and feature construction for predicting friendship links and users interests in the Live Journal social network en
dc.type Thesis en
dc.description.degree Master of Science en
dc.description.level Masters en
dc.description.department Department of Computing and Information Sciences en
dc.description.advisor Doina Caragea en
dc.description.advisor William H. Hsu en
dc.subject.umi Computer Science (0984) en
dc.date.published 2008 en
dc.date.graduationmonth December en

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