Predicting Cooperation Relationships in Heterogeneous Movie Networks
碩士 === 國立成功大學 === 工程科學系 === 102 === In social network analysis, relationship prediction among people in the interpersonal network is a broadly discussed problem. Nevertheless, when modeling a real network as a heterogeneous information network instead of a homogeneous one, this problem becomes more...
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ndltd-TW-102NCKU50281062015-10-14T00:12:48Z http://ndltd.ncl.edu.tw/handle/42380065753676717654 Predicting Cooperation Relationships in Heterogeneous Movie Networks 異質電影網路中之合作關係預測 Wei-ChinHung 洪偉欽 碩士 國立成功大學 工程科學系 102 In social network analysis, relationship prediction among people in the interpersonal network is a broadly discussed problem. Nevertheless, when modeling a real network as a heterogeneous information network instead of a homogeneous one, this problem becomes more challenging. In this work, we focus on the movie network constituted by multiple types of entities (e.g., movies, participants, studios, and genres) and multiple types of links among these entities. To clearly represent the semantic meanings in such a movie network, we utilize the meta-path-based prediction model. Advantages of our approach are two-fold. First, the meta-path-based method systematically retrieves topological features in a movie network. Second, we use the supervised method to learn the best weights connected with different topological features in building cooperation relationships. Empirical studies based on the real IMDb dataset show that our approach precisely predicts cooperation relationships in a large-scale movie network. Wei-Guang Teng 鄧維光 2014 學位論文 ; thesis 43 en_US |
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碩士 === 國立成功大學 === 工程科學系 === 102 === In social network analysis, relationship prediction among people in the interpersonal network is a broadly discussed problem. Nevertheless, when modeling a real network as a heterogeneous information network instead of a homogeneous one, this problem becomes more challenging. In this work, we focus on the movie network constituted by multiple types of entities (e.g., movies, participants, studios, and genres) and multiple types of links among these entities. To clearly represent the semantic meanings in such a movie network, we utilize the meta-path-based prediction model. Advantages of our approach are two-fold. First, the meta-path-based method systematically retrieves topological features in a movie network. Second, we use the supervised method to learn the best weights connected with different topological features in building cooperation relationships. Empirical studies based on the real IMDb dataset show that our approach precisely predicts cooperation relationships in a large-scale movie network.
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Wei-Guang Teng |
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Wei-Guang Teng Wei-ChinHung 洪偉欽 |
author |
Wei-ChinHung 洪偉欽 |
spellingShingle |
Wei-ChinHung 洪偉欽 Predicting Cooperation Relationships in Heterogeneous Movie Networks |
author_sort |
Wei-ChinHung |
title |
Predicting Cooperation Relationships in Heterogeneous Movie Networks |
title_short |
Predicting Cooperation Relationships in Heterogeneous Movie Networks |
title_full |
Predicting Cooperation Relationships in Heterogeneous Movie Networks |
title_fullStr |
Predicting Cooperation Relationships in Heterogeneous Movie Networks |
title_full_unstemmed |
Predicting Cooperation Relationships in Heterogeneous Movie Networks |
title_sort |
predicting cooperation relationships in heterogeneous movie networks |
publishDate |
2014 |
url |
http://ndltd.ncl.edu.tw/handle/42380065753676717654 |
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1718087622665961472 |