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Erschienen in:
2015 | OriginalPaper | Buchkapitel
Social Network Recommendation Based on Hybrid Suffix Tree Clustering
verfasst von : Jianhao Zhang, Xun Ma, Weimin Li, Qun Jin
Erschienen in: Computer Science and its Applications
Verlag: Springer Berlin Heidelberg
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Comparing to the ordinary text analysis and recommendation, the contents on Social Network Services (SNS) are observably more distinct and less redundant. Content-based recommendation has become the main method on SNSs. Because the limited contents are occurred in SNSs, a considerable effect can’t be reached by using ordinary cluster algorithms. In this paper, we propose a two-phase hybrid clustering algorithm based on Suffix Tree Clustering (STC), which not only uses the words themselves, but relations between them as well. Evaluation experiment and analysis confirm that our techniques have better recommendation results and effects on cold-start scenarios.