Topic and Time Sensitive Entity Ranking Algorithm on Collaborative Networks
This paper proposes a novel topic and time sensitive algorithm called TTS-Rank,explaining entity ranking to random voting process.Firstly the collaborative network is projected according to given topics,then we propose a function to calculate transition probability based on time and topic factors on Markov chain,finally calculate the ranking score of each entity through power iteration method.The algorithm and traditional ones are evaluated empirically on a large real data set of open source software developer collaborative network,results show our algorithm is more accurate effective and applicable,and the ranking is a multi-dimension representation of authority of the entities in collaborative network.