Name
Abstract | ||
|---|---|---|
When a critical system exhibits an incident during its operation, a ticket is usually generated by the monitoring systems or users to describe its issue and should be fixed by system maintenance teams in an acceptable short period of time to avoid serious economic or reputation losses. Although there are a few works about ticket classification, they suffer from poor performance because of the obvious characteristics of unstructured, short free-text with large vocabulary size, large volume, and so on. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.future.2017.07.054 | Future Generation Computer Systems |
Keywords | Field | DocType |
Document clustering,Ticket classification,Domain knowledge,Local search,Signature,Semantic similarity | Data mining,Domain knowledge,Computer science,Critical system,Ticket,Group signature,Information technology management,Local search (optimization),Vocabulary,Reputation | Journal |
Volume | Issue | ISSN |
78 | P1 | 0167-739X |
Citations | PageRank | References |
1 | 0.35 | 22 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jian Xu | 1 | 9 | 2.63 |
| hang zhang | 2 | 31 | 16.05 |
| Wubai Zhou | 3 | 134 | 11.29 |
| Rouying He | 4 | 3 | 1.13 |
| Tao Li | 5 | 387 | 41.20 |