Frequent Graph Mining for Data Streams

Summary

Frequent Graph Mining for Data Streams is a master's thesis^[1].

Key Facts

• Frequent Graph Mining for Data Streams authored Ranran Bian^[2].
• Frequent Graph Mining for Data Streams's instance of is recorded as master's thesis^[3].
• Frequent Graph Mining for Data Streams was published by ResearchSpace@Auckland^[4].
• Frequent Graph Mining for Data Streams's country of origin is recorded as New Zealand^[5].
• Frequent Graph Mining for Data Streams was published on 2015^[6].
• Frequent Graph Mining for Data Streams's main subject is computer science^[7].
• Frequent Graph Mining for Data Streams's title is recorded as Frequent Graph Mining for Data Streams^[8].
• Frequent Graph Mining for Data Streams's copyright holder is recorded as Ranran Bian^[9].
• Frequent Graph Mining for Data Streams's thesis submitted to is recorded as University of Auckland^[10].
• Frequent Graph Mining for Data Streams's on focus list of Wikimedia project is recorded as NZThesisProject^[11].
• Frequent Graph Mining for Data Streams's copyright status is recorded as copyrighted^[12].
• Frequent Graph Mining for Data Streams's online access status is recorded as closed user group^[13].
• Frequent Graph Mining for Data Streams's thesis committee member is recorded as Yun Sing Koh^[14].
• Frequent Graph Mining for Data Streams's thesis committee member is recorded as Gillian Dobbie^[15].
• Frequent Graph Mining for Data Streams's thesis submitted for degree is recorded as master's degree^[16].

Body

Authorship and Creation

Frequent Graph Mining for Data Streams authored Ranran Bian^[2]. It was published by ResearchSpace@Auckland^[4].

Publication

Frequent Graph Mining for Data Streams was published on 2015^[6].

Subject and Themes

Frequent Graph Mining for Data Streams's main subject is computer science^[7].