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Analysis of feature pattern mining approaches on social network: A case study on Facebook için kapak resmi
Analysis of feature pattern mining approaches on social network: A case study on Facebook
Başlık:
Analysis of feature pattern mining approaches on social network: A case study on Facebook
Yazar:
Öztürk, Elife, author.
Yazar Ek Girişi:
Fiziksel Tanımlama:
x, 61 leaves: illustrarions, charts;+ 1 computer laser optical disc.
Özet:
Pattern mining algorithms obtain patterns frequently seen in a database and complex graphs which are available from gene networks to social networks. Complex graphs contain lots of valuable information on their nodes or edges. For this reason, pattern mining algorithms can be used to extract data from complex networks. However, these algorithms usually work on the graphs whose nodes have a single label. If these algorithms are implemented on multi labeled (multi-attributed) complex graphs, their complexities belong to NP-Complete. For this reason, in this study, different approaches have been evaluated to find patterns. The goal is to understand related methods and algorithms with their pros and cons to obtain common feature patterns from multi-attributed complex graphs. We also selected Facebook social network complex graph data set (SNAP - Stanford University FaceBook anonymized data set) as an application domain and we analyzed the most frequent feature patterns on friendship relations.
Konu Başlığı Ek Girişi:
Konu Başlığı:
Yazar Ek Girişi:
Tek Biçim Eser Adı:
Thesis (Master)--İzmir Institute of Technology: Computer Engineering.

İzmir Institute of Technology:Computer Engineering--Thesis (Master).
Elektronik Erişim:
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