Class information for: |
Basic class information |
Class id | #P | Avg. number of references |
Database coverage of references |
---|---|---|---|
30788 | 163 | 30.5 | 31% |
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 |
235 | 2 | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE//FEATURE SELECTION//MACHINE LEARNING | 20237 |
30788 | 1 | META LEARNING//LIACC FEP//ALGORITHM RECOMMENDATION | 163 |
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 | META LEARNING | authKW | 583589 | 11% | 17% | 18 |
2 | LIACC FEP | address | 562003 | 2% | 100% | 3 |
3 | ALGORITHM RECOMMENDATION | authKW | 374669 | 1% | 100% | 2 |
4 | COMPONENT BASED ALGORITHMS | authKW | 374669 | 1% | 100% | 2 |
5 | DATA SET CHARACTERISTICS EXTRACTION | authKW | 374669 | 1% | 100% | 2 |
6 | REUSABLE COMPONENT | authKW | 374669 | 1% | 100% | 2 |
7 | EXPLANATION FACILITY | authKW | 249778 | 1% | 67% | 2 |
8 | 3C DISTRIBUTORS | authKW | 187334 | 1% | 100% | 1 |
9 | ABC KMDSS | authKW | 187334 | 1% | 100% | 1 |
10 | ALGORITHM AUTOMATIC RECOMMENDATION | authKW | 187334 | 1% | 100% | 1 |
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 | 10447 | 66% | 0% | 107 |
2 | Computer Science, Theory & Methods | 517 | 16% | 0% | 26 |
3 | Computer Science, Information Systems | 134 | 8% | 0% | 13 |
4 | Automation & Control Systems | 59 | 4% | 0% | 7 |
5 | Computer Science, Cybernetics | 58 | 2% | 0% | 3 |
6 | Operations Research & Management Science | 47 | 4% | 0% | 7 |
7 | Computer Science, Software Engineering | 31 | 4% | 0% | 6 |
8 | Robotics | 26 | 1% | 0% | 2 |
9 | Engineering, General | 18 | 3% | 0% | 5 |
10 | Engineering, Electrical & Electronic | 13 | 8% | 0% | 13 |
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 | LIACC FEP | 562003 | 2% | 100% | 3 |
2 | COMMON SERV DIRECTORATE | 187334 | 1% | 100% | 1 |
3 | INGN INFOMAC COMUNICAC | 187334 | 1% | 100% | 1 |
4 | INTELIGENCIA ARTIFICIAL GRUPO SISTEMAS INTELIGENT | 187334 | 1% | 100% | 1 |
5 | MERCEDES BENZ SINDELFINGEN PLANT | 187334 | 1% | 100% | 1 |
6 | MINE HAULAGE HOISTING | 187334 | 1% | 100% | 1 |
7 | QUAID E AZAM | 187334 | 1% | 100% | 1 |
8 | STRATEG OUTSOURCING | 187334 | 1% | 100% | 1 |
9 | TECHNOL ERCH | 187334 | 1% | 100% | 1 |
10 | TECHNOL FT3 KL | 187334 | 1% | 100% | 1 |
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 | INTELLIGENT DATA ANALYSIS | 19639 | 5% | 1% | 8 |
2 | MACHINE LEARNING | 15137 | 6% | 1% | 10 |
3 | ARTIFICIAL INTELLIGENCE REVIEW | 8932 | 4% | 1% | 6 |
4 | TECHNICS TECHNOLOGIES EDUCATION MANAGEMENT-TTEM | 4717 | 2% | 1% | 3 |
5 | LECTURE NOTES IN ARTIFICIAL INTELLIGENCE | 3670 | 11% | 0% | 18 |
6 | NEURAL COMPUTATION | 3643 | 4% | 0% | 7 |
7 | KNOWLEDGE-BASED SYSTEMS | 3311 | 4% | 0% | 7 |
8 | JOURNAL OF MACHINE LEARNING RESEARCH | 1906 | 2% | 0% | 4 |
9 | INTERNATIONAL JOURNAL ON ARTIFICIAL INTELLIGENCE TOOLS | 1191 | 1% | 0% | 2 |
10 | FLEXIBLE SERVICES AND MANUFACTURING JOURNAL | 1154 | 1% | 1% | 1 |
Author Key Words |
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 | ALI, R , LEE, S , CHUNG, TC , (2017) ACCURATE MULTI-CRITERIA DECISION MAKING METHODOLOGY FOR RECOMMENDING MACHINE LEARNING ALGORITHM.EXPERT SYSTEMS WITH APPLICATIONS. VOL. 71. ISSUE . P. 257 -278 | 9 | 38% | 1 |
2 | REIF, M , SHAFAIT, F , GOLDSTEIN, M , BREUEL, T , DENGEL, A , (2014) AUTOMATIC CLASSIFIER SELECTION FOR NON-EXPERTS.PATTERN ANALYSIS AND APPLICATIONS. VOL. 17. ISSUE 1. P. 83-96 | 8 | 67% | 10 |
3 | WANG, GT , SONG, QB , ZHU, XY , (2015) AN IMPROVED DATA CHARACTERIZATION METHOD AND ITS APPLICATION IN CLASSIFICATION ALGORITHM RECOMMENDATION.APPLIED INTELLIGENCE. VOL. 43. ISSUE 4. P. 892 -912 | 9 | 53% | 1 |
4 | LEE, JW , GIRAUD-CARRIER, C , (2013) AUTOMATIC SELECTION OF CLASSIFICATION LEARNING ALGORITHMS FOR DATA MINING PRACTITIONERS.INTELLIGENT DATA ANALYSIS. VOL. 17. ISSUE 4. P. 665 -678 | 8 | 62% | 4 |
5 | SERBAN, F , VANSCHOREN, J , KIETZ, JU , BERNSTEIN, A , (2013) A SURVEY OF INTELLIGENT ASSISTANTS FOR DATA ANALYSIS.ACM COMPUTING SURVEYS. VOL. 45. ISSUE 3. P. - | 9 | 43% | 14 |
6 | AYE, TT , LEE, GKK , SU, Y , ZHANG, TY , LEE, C , KASIM, H , HOE, I , LEE, FBS , HUNG, TGG , (2017) LAYMAN ANALYTICS SYSTEM: A CLOUD-ENABLED SYSTEM FOR DATA ANALYTICS WORKFLOW RECOMMENDATION.IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING. VOL. 14. ISSUE 1. P. 160 -170 | 5 | 71% | 0 |
7 | WANG, GT , SONG, QB , ZHANG, XY , ZHANG, KY , (2014) A GENERIC MULTILABEL LEARNING-BASED CLASSIFICATION ALGORITHM RECOMMENDATION METHOD.ACM TRANSACTIONS ON KNOWLEDGE DISCOVERY FROM DATA. VOL. 9. ISSUE 1. P. - | 11 | 33% | 2 |
8 | GOSWAMI, S , CHAKRABARTI, A , CHAKRABORTY, B , (2016) A PROPOSAL FOR RECOMMENDATION OF FEATURE SELECTION ALGORITHM BASED ON DATA SET CHARACTERISTICS.JOURNAL OF UNIVERSAL COMPUTER SCIENCE. VOL. 22. ISSUE 6. P. 760 -781 | 6 | 55% | 0 |
9 | SUN, HL , WANG, GT , SONG, QB , ZHANG, XY , XU, BW , ZHOU, YM , (2013) A FEATURE SUBSET SELECTION ALGORITHM AUTOMATIC RECOMMENDATION METHOD.JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH. VOL. 47. ISSUE . P. 1 -34 | 9 | 36% | 10 |
10 | BARNARD, E , (2011) DETERMINATION AND THE NO-FREE-LUNCH PARADOX.NEURAL COMPUTATION. VOL. 23. ISSUE 7. P. 1899 -1909 | 5 | 71% | 0 |
Classes with closest relation at Level 1 |