A framework for extracting and representing project knowledge contexts using topic models and dynamic knowledge maps

There is still a lack of effective paradigms and tools for analysing and discovering the contents and relationships of project knowledge contexts in the field of project management. In this paper, a new framework for extracting and representing project knowledge contexts using topic models and dynamic knowledge maps under big data environments is proposed and developed. The conceptual paradigm, theoretical underpinning, extended topic model, and illustration examples of the ontology model for project knowledge maps are presented, with further research work envisaged

Hybrid Intelligent Models and Systems for Problem Solving and Decision Making in the Digital Age (Keynote)

Due to fierce competition, growing overload of data and information, and high level of complexity and uncertainties, it is ever more challenging for people, and managers in particular, to solve problems and make timely and sound business, management and engineering decisions in this digital age. The needs for the applications of artificial intelligence and other methods, techniques and technologies in support of problem solving and decision making have never been greater. However, each of the support methods, techniques or technologies has its own weaknesses, and normally, can only be utilized to solve and process one aspect of the complex multi-facet properties of real-world problems. Therefore, hybrid intelligent models and systems that integrate the strengths and powers of diverse techniques and technologies should be created, developed and used as effective solutions. In this report, we will focus on hybrid frameworks, paradigms and systems that deal with different types of problems, and will cover the following research topics: •Context-aware intelligent project knowledge recommendation framework and system (Jin Xu & Shuliang Li) •A framework for extracting and representing project knowledge contexts using topic models and dynamic knowledge maps: a big data perspective (Zheng Li, Jin Xu, Yanyan Zhang & Shuliang Li) •Linking social media with open innovation: an intelligent model (Shuliang Li) •The innovation network as a complex adaptive system: flexible multi-agent based modeling, simulation and evolutionary decision making (Qingqi Long & Shuliang Li) •A multi-agent-based evolution model of innovation networks in dynamic environments (Qingqi Long & Shuliang Li) •Hybrid framework and model for modelling and simulation for unethical return behaviour and how companies respond (Shawkat Rahman & Shuliang Li) •AgentsInternational: integration of multiple agents, simulation, knowledge bases and fuzzy logic for international marketing decision making (Shuliang Li & Jim Zheng Li) •A Web-based hybrid intelligent system for blended conventional, digital, mobile and social media marketing strategy formulation (Shuliang Li & Jim Zheng Li) •A hybrid intelligent model for Web & social media dynamics, and evolutionary and adaptive branding (Shuliang Li) •A hybrid paradigm for modelling, simulation and analysis of brand virality in social media (Shuliang Li & Jim Zheng Li