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Shicheng Wan

6 papers hereh-index 111.2k citations33 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author4

Across the 6 of 6 papers where every author was matched, so the position is known.

fields
  • cs.DB4
  • cs.AI1
  • cs.CY1
same name
  • Shicheng Wan — 6 papers
  • Shicheng Wan — 3 papers

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20212023
most citedMetaverse in Education: Vision, Opportunities, and Challenges

33 citations · 54 across the 6 of their papers we have counts for

collaborators
Showing cs.DBShow all

4 papers · 1 filter

cs.DB2021

TargetUM: Targeted High-Utility Itemset Querying

Jinbao Miao, Shicheng Wan, Wensheng Gan +2

Traditional high-utility itemset mining (HUIM) aims to determine all high-utility itemsets (HUIs) that satisfy the minimum utility threshold (\textit{minUtil}) in transaction datab…

cs.DB2021★ 7 cited

FUIM: Fuzzy Utility Itemset Mining

Shicheng Wan, Wensheng Gan, Xu Guo +2

Because of usefulness and comprehensibility, fuzzy data mining has been extensively studied and is an emerging topic in recent years. Compared with utility-driven itemset mining te…

cs.DB2021★ 1 cited

THUE: Discovering Top-K High Utility Episodes

Shicheng Wan, Jiahui Chen, Wensheng Gan +2

Episode discovery from an event is a popular framework for data mining tasks and has many real-world applications. An episode is a partially ordered set of objects (e.g., item, nod…

cs.DB2021★ 3 cited

TOPIC: Top-k High-Utility Itemset Discovering

Jiahui Chen, Shicheng Wan, Wensheng Gan +2

Utility-driven itemset mining is widely applied in many real-world scenarios. However, most algorithms do not work for itemsets with negative utilities. Several efficient algorithm…

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