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Recent years have witnessed a growing number of researches on communitycharacterization. In contrast to the large body of researches on thecategorical measures (rise or decline) for evaluating the communitydevelopment, we propose to estimate the community development strength (towhich degree the rise or decline is). More specifically, given already knowncategorical information of community development, we are attempting to quantifythe community development strength, which is of great interest. Motivated bythe increasing availability of large-scale data on the network between entitiesamong communities, we investigate how to score the the community's developmentstrength. We formally define our task as prospecting community developmentstrength from categorization based on multi-relational network information andidentify two challenges as follows: (1) limited guidance for integrating entitymulti-relational network in quantifying the community development strength; (2)the existence of selection effect that the community development strength hason network formation. Aiming at these challenges, we start by a hybrid ofdiscriminative and generative approaches on multi-relational network-basedcommunity development strength quantification. Then a network generationprocess is exploited to debias the selection process. In the end, weempirically evaluate the proposed model by applying it to quantify enterprisebusiness development strength. Experimental results demonstrate theeffectiveness of the proposed method.

Prospecting Community Development Strength based on Economic Graph: From Categorization to Scoring