Class information for: |
Basic class information |
Class id | #P | Avg. number of references |
Database coverage of references |
---|---|---|---|
1900 | 2436 | 27.6 | 33% |
Hierarchy of classes |
The table includes all classes above and classes immediately below the current class. |
Cluster id | Level | Cluster label | #P |
---|---|---|---|
9 | 4 | COMPUTER SCIENCE, THEORY & METHODS//COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE//COMPUTER SCIENCE, INFORMATION SYSTEMS | 1247339 |
211 | 3 | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE//IEEE TRANSACTIONS ON NEURAL NETWORKS//DATA MINING | 51632 |
2216 | 2 | ASSOCIATION RULES//DATA MINING//FREQUENT ITEMSETS | 4819 |
1900 | 1 | ASSOCIATION RULES//DATA MINING//FREQUENT ITEMSETS | 2436 |
Terms with highest relevance score |
rank | Term | termType | Chi square | Shr. of publ. in class containing term |
Class's shr. of term's tot. occurrences |
#P with term in class |
---|---|---|---|---|---|---|
1 | ASSOCIATION RULES | authKW | 1845148 | 14% | 43% | 346 |
2 | DATA MINING | authKW | 1170702 | 35% | 11% | 855 |
3 | FREQUENT ITEMSETS | authKW | 1075832 | 4% | 83% | 104 |
4 | SEQUENTIAL PATTERNS | authKW | 997840 | 5% | 69% | 116 |
5 | FREQUENT PATTERNS | authKW | 601658 | 3% | 66% | 73 |
6 | FREQUENT PATTERN MINING | authKW | 545903 | 3% | 66% | 66 |
7 | UTILITY MINING | authKW | 466347 | 2% | 93% | 40 |
8 | INCREMENTAL MINING | authKW | 449323 | 2% | 81% | 44 |
9 | ASSOCIATION RULE MINING | authKW | 390275 | 4% | 36% | 87 |
10 | SEQUENTIAL PATTERN MINING | authKW | 379226 | 2% | 64% | 47 |
Web of Science journal categories |
Rank | Term | Chi square | Shr. of publ. in class containing term |
Class's shr. of term's tot. occurrences |
#P with term in class |
---|---|---|---|---|---|
1 | Computer Science, Artificial Intelligence | 151028 | 65% | 1% | 1573 |
2 | Computer Science, Information Systems | 64576 | 42% | 1% | 1028 |
3 | Computer Science, Theory & Methods | 7789 | 16% | 0% | 390 |
4 | Operations Research & Management Science | 3549 | 9% | 0% | 220 |
5 | Computer Science, Software Engineering | 2953 | 8% | 0% | 206 |
6 | Engineering, Electrical & Electronic | 1631 | 17% | 0% | 420 |
7 | Computer Science, Interdisciplinary Applications | 775 | 5% | 0% | 132 |
8 | Computer Science, Hardware & Architecture | 515 | 3% | 0% | 70 |
9 | Computer Science, Cybernetics | 226 | 1% | 0% | 24 |
10 | Engineering, General | 97 | 2% | 0% | 50 |
Address terms |
Rank | Term | Chi square | Shr. of publ. in class containing term |
Class's shr. of term's tot. occurrences |
#P with term in class |
---|---|---|---|---|---|
1 | IIIRC | 122817 | 1% | 70% | 14 |
2 | SHENZHEN INTERNET INFORMAT ABORAT | 105200 | 1% | 44% | 19 |
3 | HIIT BASIC UNIT | 59897 | 1% | 34% | 14 |
4 | COMP SCI INFORMAT ENGN | 49320 | 8% | 2% | 207 |
5 | PISA KDD | 45115 | 0% | 60% | 6 |
6 | LIPAH | 40934 | 0% | 47% | 7 |
7 | ARTIFICIAL INTELLIGENCE INFRASTRUCT INFORM | 37600 | 0% | 100% | 3 |
8 | FUQLING BRANCH | 37600 | 0% | 100% | 3 |
9 | COMP SCI | 35847 | 27% | 0% | 662 |
10 | INGN SYST INFORMAT | 34110 | 0% | 39% | 7 |
Journals |
Rank | Term | Chi square | Shr. of publ. in class containing term |
Class's shr. of term's tot. occurrences |
#P with term in class |
---|---|---|---|---|---|
1 | DATA MINING AND KNOWLEDGE DISCOVERY | 198304 | 4% | 16% | 96 |
2 | KNOWLEDGE AND INFORMATION SYSTEMS | 143822 | 5% | 10% | 110 |
3 | INTELLIGENT DATA ANALYSIS | 138011 | 3% | 13% | 82 |
4 | IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING | 83942 | 6% | 5% | 142 |
5 | LECTURE NOTES IN ARTIFICIAL INTELLIGENCE | 80685 | 13% | 2% | 326 |
6 | EXPERT SYSTEMS WITH APPLICATIONS | 32151 | 7% | 2% | 165 |
7 | DATA & KNOWLEDGE ENGINEERING | 27498 | 2% | 4% | 52 |
8 | INTERNATIONAL JOURNAL OF DATA WAREHOUSING AND MINING | 25847 | 1% | 13% | 16 |
9 | WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY | 24423 | 1% | 10% | 19 |
10 | JOURNAL OF INTELLIGENT INFORMATION SYSTEMS | 24164 | 1% | 6% | 34 |
Author Key Words |
Rank | Term | Chi square | Shr. of publ. in class containing term |
Class's shr. of term's tot. occurrences |
#P with term in class |
LCSH search | Wikipedia search |
---|---|---|---|---|---|---|---|
1 | ASSOCIATION RULES | 1845148 | 14% | 43% | 346 | Search ASSOCIATION+RULES | Search ASSOCIATION+RULES |
2 | DATA MINING | 1170702 | 35% | 11% | 855 | Search DATA+MINING | Search DATA+MINING |
3 | FREQUENT ITEMSETS | 1075832 | 4% | 83% | 104 | Search FREQUENT+ITEMSETS | Search FREQUENT+ITEMSETS |
4 | SEQUENTIAL PATTERNS | 997840 | 5% | 69% | 116 | Search SEQUENTIAL+PATTERNS | Search SEQUENTIAL+PATTERNS |
5 | FREQUENT PATTERNS | 601658 | 3% | 66% | 73 | Search FREQUENT+PATTERNS | Search FREQUENT+PATTERNS |
6 | FREQUENT PATTERN MINING | 545903 | 3% | 66% | 66 | Search FREQUENT+PATTERN+MINING | Search FREQUENT+PATTERN+MINING |
7 | UTILITY MINING | 466347 | 2% | 93% | 40 | Search UTILITY+MINING | Search UTILITY+MINING |
8 | INCREMENTAL MINING | 449323 | 2% | 81% | 44 | Search INCREMENTAL+MINING | Search INCREMENTAL+MINING |
9 | ASSOCIATION RULE MINING | 390275 | 4% | 36% | 87 | Search ASSOCIATION+RULE+MINING | Search ASSOCIATION+RULE+MINING |
10 | SEQUENTIAL PATTERN MINING | 379226 | 2% | 64% | 47 | Search SEQUENTIAL+PATTERN+MINING | Search SEQUENTIAL+PATTERN+MINING |
Core articles |
The table includes core articles in the class. The following variables is taken into account for the relevance score of an article in a cluster c: (1) Number of references referring to publications in the class. (2) Share of total number of active references referring to publications in the class. (3) Age of the article. New articles get higher score than old articles. (4) Citation rate, normalized to year. |
Rank | Reference | # ref. in cl. |
Shr. of ref. in cl. |
Citations |
---|---|---|---|---|
1 | LEE, GG , YUN, U , (2017) A NEW EFFICIENT APPROACH FOR MINING UNCERTAIN FREQUENT PATTERNS USING MINIMUM DATA STRUCTURE WITHOUT FALSE POSITIVES.FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE. VOL. 68. ISSUE . P. 89 -110 | 19 | 58% | 15 |
2 | LE, T , VO, B , (2016) THE LATTICE-BASED APPROACHES FOR MINING ASSOCIATION RULES: A REVIEW.WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY. VOL. 6. ISSUE 4. P. 140 -151 | 55 | 89% | 0 |
3 | RYANG, H , YUN, U , (2016) HIGH UTILITY PATTERN MINING OVER DATA STREAMS WITH SLIDING WINDOW TECHNIQUE.EXPERT SYSTEMS WITH APPLICATIONS. VOL. 57. ISSUE . P. 214 -231 | 42 | 95% | 0 |
4 | HAMROUNI, T , (2012) KEY ROLES OF CLOSED SETS AND MINIMAL GENERATORS IN CONCISE REPRESENTATIONS OF FREQUENT PATTERNS.INTELLIGENT DATA ANALYSIS. VOL. 16. ISSUE 4. P. 581 -631 | 51 | 77% | 4 |
5 | YUN, U , LEE, G , (2016) INCREMENTAL MINING OF WEIGHTED MAXIMAL FREQUENT ITEMSETS FROM DYNAMIC DATABASES.EXPERT SYSTEMS WITH APPLICATIONS. VOL. 54. ISSUE . P. 304 -327 | 31 | 89% | 4 |
6 | LEE, G , YUN, U , RYANG, H , KIM, D , (2016) APPROXIMATE MAXIMAL FREQUENT PATTERN MINING WITH WEIGHT CONDITIONS AND ERROR TOLERANCE.INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE. VOL. 30. ISSUE 6. P. - | 34 | 100% | 0 |
7 | DENG, ZH , (2016) DIFFNODESETS: AN EFFICIENT STRUCTURE FOR FAST MINING FREQUENT ITEMSETS.APPLIED SOFT COMPUTING. VOL. 41. ISSUE . P. 214 -223 | 29 | 100% | 2 |
8 | YUN, U , LEE, G , (2016) SLIDING WINDOW BASED WEIGHTED ERASABLE STREAM PATTERN MINING FOR STREAM DATA APPLICATIONS.FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE. VOL. 59. ISSUE . P. 1 -20 | 25 | 100% | 3 |
9 | YUN, U , RYANG, H , (2015) INCREMENTAL HIGH UTILITY PATTERN MINING WITH STATIC AND DYNAMIC DATABASES.APPLIED INTELLIGENCE. VOL. 42. ISSUE 2. P. 323 -352 | 30 | 88% | 8 |
10 | SAHOO, J , DAS, AK , GOSWAMI, A , (2015) AN EFFICIENT APPROACH FOR MINING ASSOCIATION RULES FROM HIGH UTILITY ITEMSETS.EXPERT SYSTEMS WITH APPLICATIONS. VOL. 42. ISSUE 13. P. 5754 -5778 | 29 | 94% | 6 |
Classes with closest relation at Level 1 |