A wide variety of predictive analytics techniques have been developed in statistics, machine learning and data mining; however, many of these algorithms take a black-box approach in which data is input and future pred...A wide variety of predictive analytics techniques have been developed in statistics, machine learning and data mining; however, many of these algorithms take a black-box approach in which data is input and future predictions are output with no insight into what goes on during the process. Unfortunately, such a closed system approach often leaves little room for injecting domain expertise and can result in frustration from analysts when results seem snurious or confusing. In order to allow for more human-centric approaches, the visualization community has begun developing methods to enable users to incorporate expert knowledge into the pre- diction process at all stages, including data cleaning, feature selection, model building and model validation. This paper surveys current progress and trends in predictive visual ana- lytics, identifies the common framework in which predictive visual analytics systems operate, and develops a summariza- tion of the predictive analytics workfiow.展开更多
With the rapid development of massively multiplayer online role-playing games(MMORPGs),a huge amount of fine-grained data on the in-game activities of players have been recorded by MMORPGs operators.These data provide...With the rapid development of massively multiplayer online role-playing games(MMORPGs),a huge amount of fine-grained data on the in-game activities of players have been recorded by MMORPGs operators.These data provide considerable opportunities with which to study the dynamic interplay between player behaviors and investigate the roles of various social structures that underlie such interplay.However,it is challenging to model and visualize these behavioral data.This study proposes a novel influence-susceptible model to measure the dynamic interplay between behaviors.Based on this model,we introduce a new visual analytics system called BeXplorer.This system enables analysts to interactively explore the dynamic interplay between player purchase and communication behaviors and to examine the manner in which this interplay is bound by social structures where players are embedded.Three case studies and a task-based evaluation are conducted to demonstrate the effectiveness and applicability of our method.展开更多
基金This work was supported by National Basic Re- search Program of China （973 Program） （2015CB352503）, Major Pro- gram of the National Natural Science Foundation of China （61232012）, the National Natural Science Foundation of China （Grant Nos. 61303141, 61422211, u1536118, u1536119）, Zhejiang Provincial Natural Science Foundation of China （LR13F020001）, the Fundamental Research Funds for the Central Universities, the Innovation Joint Research Center for Cyber- Physical-Society System, and the United State＇s National Science Founda- tion （1350573）.
文摘A wide variety of predictive analytics techniques have been developed in statistics, machine learning and data mining; however, many of these algorithms take a black-box approach in which data is input and future predictions are output with no insight into what goes on during the process. Unfortunately, such a closed system approach often leaves little room for injecting domain expertise and can result in frustration from analysts when results seem snurious or confusing. In order to allow for more human-centric approaches, the visualization community has begun developing methods to enable users to incorporate expert knowledge into the pre- diction process at all stages, including data cleaning, feature selection, model building and model validation. This paper surveys current progress and trends in predictive visual ana- lytics, identifies the common framework in which predictive visual analytics systems operate, and develops a summariza- tion of the predictive analytics workfiow.
基金Yingcai Wu and Wei Chen are supported by National Natural ScienceFoundation of China (61772456, 61761136020, 61502416)NSFC-Zhejiang JointFund for the Integration of Industrialization and Informatization (U1609217)+1 种基金Zhejiang Provincial Natural Science Foundation (LR18F020001)the 100Talents Program of Zhejiang University.
文摘With the rapid development of massively multiplayer online role-playing games(MMORPGs),a huge amount of fine-grained data on the in-game activities of players have been recorded by MMORPGs operators.These data provide considerable opportunities with which to study the dynamic interplay between player behaviors and investigate the roles of various social structures that underlie such interplay.However,it is challenging to model and visualize these behavioral data.This study proposes a novel influence-susceptible model to measure the dynamic interplay between behaviors.Based on this model,we introduce a new visual analytics system called BeXplorer.This system enables analysts to interactively explore the dynamic interplay between player purchase and communication behaviors and to examine the manner in which this interplay is bound by social structures where players are embedded.Three case studies and a task-based evaluation are conducted to demonstrate the effectiveness and applicability of our method.
