학술논문

Portfolio Prediction of Online Advertisement Keywords' Biding via Role-Based Collaboration
Document Type
Conference
Source
Proceedings of the 12th Chinese Conference on Computer Supported Cooperative Work and Social Computing. :237-238
Subject
E-CARGO
Portfolio
advertising keywords
linear programming
role-based collaboration
Language
English
Abstract
With respect to the cost of advertising investment is limited1, the processing of rationalizing and maximizing marketing investment via online keyword bidding is hard. In order to solve this problem, this paper proposes an optimization method, which is based Role-Based Collaboration (RBC) and its E-CARGO model. According to history data, it is modeling the problem by mapping keywords and their combinations to roles and groups, and using linear programming to obtain the best investment prediction. The proposed methods are verified by simulation experiments. The experimental results present the practicability of the proposed solutions. Using the proposed methods, decision makers need only to provide investment budget. The maximal profitability, the rate of return and the investment rang are obtained.

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