Research On Word Cloud Layout Method Based On Movable Components Guided By Frame Field

In the information age,visualization technology enables people to obtain key information from massive data efficiently.In recent years,word cloud,as a vivid and interesting text information visualization method,has attracted many users on the Internet,especially word cloud with shape boundary constraints favoured by industries such as business,news,and creative arts.As a critical issue in word cloud generation,the layout algorithm needs to consider the effectiveness of the generated layout and the final presentation effect of the word cloud.Therefore,it has been a concern in the field of visualization technology.Although there have been some achievements in the field of automatic layout algorithms for word clouds,some things could still be improved.For example,the layouts generated by existing layout algorithms are monotonous.They only focus on filling the word cloud model’s space with words and do not consider the placement posture of the words.However,word clouds that conform to the shape features of the model are more attractive and popular from both visual perception and aesthetic perspectives.Regarding dynamic word clouds,existing layout algorithms mostly use rigid-body dynamics.However,due to the complexity of physical calculations,they are inefficient,and the motion effects are also difficult to control.In response to the problems existing in current word cloud layout algorithms,this paper proposes a static and dynamic word cloud layouts algorithm based on movable components guided by frame field.The main work of this paper are summarized as follows:1.A static word cloud algorithm based on movable component optimization and feature streamlines is proposed.This method can generate word cloud layouts aligned with the model’s feature and freely specified centers.According to the visual effect of the words in the word cloud,it divides the word set into the important word set and less important word set,and then solves the layout optimization problem and uses streamlines guide words to place.For the important word’s layout,this method establishes an optimization model with overlap constraints based on the movable component under the guidance of the frame and distance fields,then solves the optimization problem by fixing variables and relaxing constraints.For the less important word’s layout,this method uses streamlines extracted from the frame field to guide words to place efficiently.This method is extended from two-dimensional planes to three-dimensional surfaces to generate texture maps of surfaces such as word clouds and picture clouds.Finally,the experimental comparison,quantitative and user evaluation verify the effectiveness of the algorithm and demonstrate its advantages compared with the current word cloud algorithm.2.A dynamic word cloud algorithm based on the movable component group is proposed.This method extends the design concept of the static word cloud algorithm using the frame field aligning shape features to the dynamic word cloud.It regards the word collection as a movable component flock and transforms the word cloud’s design principles into the group’s behavior control criteria.This algorithm is efficient and easily manipulates word’s motion.In addition to the fundamental requirements,such as shape word cloud’s boundary constraints and overlap avoidance,this group system also provides functions for aggregation,feature matching,velocity matching,and category matching to achieve the following goals: attracting word convergence,aligning shape features,stabilizing the layout,and word classification.Finally,the comprehensive experiments and evaluation verify the design concept and the effectiveness of the algorithm.