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專利授權區

專利授權區
專利名稱(中)	社群網路中單一目標節點之挑選方法及其系統
專利名稱(英)	METHOD AND SYSTEM FOR SELECTING SINGLE TARGET NODE WITHIN SOCIAL NETWORK
專利家族	中華民國：I753659 美國：US-2022-0156853-A1(公開號)
專利權人	國立清華大學 100.00%
發明人	葉維彰
技術領域	資訊工程

專利摘要(中)
本發明提供一種社群網路中單一目標節點之挑選方法。節點提供步驟設定社群網路之其中一節點為起始節點。機率計算步驟依據蒙地卡羅模組與層搜尋模組計算出起始節點之複數個傳播節點數。期望值產生步驟依據傳播節點數與傳播成功機率產生期望值。目標節點挑選步驟重新設定另一節點作為起始節點並重複執行機率計算步驟與期望值產生步驟而產生另一期望值，然後比對期望值與另一期望值而挑選出具有最大期望值之目標節點。藉此，對目標節點投放訊息，可在社群網路中達到最大的傳播節點數。

專利摘要(中)

本發明提供一種社群網路中單一目標節點之挑選方法。節點提供步驟設定社群網路之其中一節點為起始節點。機率計算步驟依據蒙地卡羅模組與層搜尋模組計算出起始節點之複數個傳播節點數。期望值產生步驟依據傳播節點數與傳播成功機率產生期望值。目標節點挑選步驟重新設定另一節點作為起始節點並重複執行機率計算步驟與期望值產生步驟而產生另一期望值，然後比對期望值與另一期望值而挑選出具有最大期望值之目標節點。藉此，對目標節點投放訊息，可在社群網路中達到最大的傳播節點數。

專利摘要(英)
The present disclosure provides a method for selecting single target node within a social network. A node providing step is performed to set one of a plurality of nodes within the social network as an original node. A probability calculating step is performed to calculate a plurality of propagation-node amounts of the original node according to a Monte Carlo module and a layered-search module. An expected value generating step is performed to generate an expected value according to the propagation-node amounts and a plurality of propagating success probabilities. A target node selecting step is performed to reset another one of the nodes as the original node and repeat the probability calculating step and the expected value generating step to generate another expected value, and compare the expected value with the another expected value to select the target node having a maximum expected value. Therefore, it is favorable for achieving the max propagation-node amount within the social network through putting the message to the target node.

專利摘要(英)

The present disclosure provides a method for selecting single target node within a social network. A node providing step is performed to set one of a plurality of nodes within the social network as an original node. A probability calculating step is performed to calculate a plurality of propagation-node amounts of the original node according to a Monte Carlo module and a layered-search module. An expected value generating step is performed to generate an expected value according to the propagation-node amounts and a plurality of propagating success probabilities. A target node selecting step is performed to reset another one of the nodes as the original node and repeat the probability calculating step and the expected value generating step to generate another expected value, and compare the expected value with the another expected value to select the target node having a maximum expected value. Therefore, it is favorable for achieving the max propagation-node amount within the social network through putting the message to the target node.

聯絡資訊
承辦人姓名	李佳玲
承辦人電話	03-5715131 #62300
承辦人Email	cl.lee@mx.nthu.edu.tw