Title page for ETD etd-09242010-002320


Type of Document Master's Thesis
Author El-Goarany, Khaled
Author's Email Address goarany@vt.edu
URN etd-09242010-002320
Title Mining Social Tags to Predict Mashup Patterns
Degree Master of Science
Department Computer Science
Advisory Committee
Advisor Name Title
Kulczycki, Gregory W. Committee Chair
Blake, M. Brian Committee Member
Frakes, William B. Committee Member
Keywords
  • Social Tags
  • Mashups
  • Web Mining
  • Recommender Systems
Date of Defense 2010-09-10
Availability restricted
Abstract
In this thesis, a tag-based approach is proposed for predicting mashup patterns, thus deriving inspiration for potential new mashups from the community’s consensus. The proposed approach applies association rule mining techniques to discover relationships between APIs and mashups based on their annotated tags. The importance of the mined relationships is advocated as a valuable source for recommending mashup candidates while mitigating common problems in recommender systems. The proposed methodology is evaluated through experimentation using a real-life dataset. Results show that the proposed mining approach achieves prediction accuracy with 60% precision and 79% recall improvement over a direct string matching approach that lacks the mining information.
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