Functional-Oriented Relationship Strength Estimation: From Online Events to Offline Interactions
Link mining/analysis over network has received widespread attention from researchers. Recently, there has been growing interest in measuring relationship strength between entities based on attribute similarity. However, limited work has assessed the compe
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Shanghai Key Laboratory of Data Science, School of Computer Science, Fudan University, Shanghai, China {cliao15,yunx}@fudan.edu.cn 2 Shanghai Institute for Advanced Communication and Data Science, Fudan University, Shanghai, China 3 Worcester Polytechnic Institute, Worcester, MA, USA Technical Center of Shanghai Shengtong Metro Group Co. Ltd., Shanghai, China School of Computer, National University of Defense Technology, Changsha, China Abstract. Link mining/analysis over network has received widespread attention from researchers. Recently, there has been growing interest in measuring relationship strength between entities based on attribute similarity. However, limited work has assessed the competitive advantage of functional elements in relationship strength quantification. The functional elements embody the growth/development nature of the relationship. Motivated by the availability of large volumes of online event records that can potentially reveal underlying functional socio-economic characteristics, we study the problem of offline relationship strength estimation with functional elements awareness from online events. Two major challenges are identified as follows: (1) informal information, online events are of high dimensions, and not all the learnt functions of online events are predictive to offline interactions; (2) heterogeneous dependency, it’s hard to measure the relationship strength by modeling functional elements with network effects jointly. To handle these challenges, we propose generalized relationship strength estimation model (gStrength), a novel approach for relationship strength estimation. First, we define the combination of latent roles and observed groups as generalized roles, and present generalized role constrained latent topic model to make the extracted latent functions compatible with offline interactions. Second, we model the functional elements and further extend them to structural dependency settings to quantify relationship strength. We apply this approach to the political and economic application scenario of measuring international investment relations. The experimental results demonstrate the effectiveness of the proposed method.
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Introduction
Link mining/analysis, e.g., link existence prediction between entities, is an important task that has been well studied by the social network mining c Springer International Publishing AG, part of Springer Nature 2018 J. Pei et al. (Eds.): DASFAA 2018, LNCS 10827, pp. 442–459, 2018. https://doi.org/10.1007/978-3-319-91452-7_29
Functional-Oriented Relationship Strength Estimation
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community. However, most existing researches only address conventional link prediction tasks, where links only have one of two possible states: active and inactive. In this work, we take on the task of relationship strength estimation. Instead of characterizing relations with binary states, it designates a continuousvalued strength [23,27]. Having a good estimation of the relationship strength between entities can yield huge benefits. Investors and governments
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