Class information for: |
Basic class information |
| Class id | #P | Avg. number of references |
Database coverage of references |
|---|---|---|---|
| 35708 | 93 | 25.5 | 29% |
Hierarchy of classes |
The table includes all classes above and classes immediately below the current class. |
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 | TREE KERNELS | authKW | 1313361 | 4% | 100% | 4 |
| 2 | RATIONAL KERNELS | authKW | 1050687 | 4% | 80% | 4 |
| 3 | STRING KERNELS | authKW | 1050679 | 9% | 40% | 8 |
| 4 | LEARNING WITH SEQUENTIAL DATA | authKW | 656680 | 2% | 100% | 2 |
| 5 | ADAPTIVE CONSTRAINT PROPAGATION | authKW | 437786 | 2% | 67% | 2 |
| 6 | SEQUENCE KERNELS | authKW | 437786 | 2% | 67% | 2 |
| 7 | SEQUENCE KERNEL | authKW | 422148 | 3% | 43% | 3 |
| 8 | AMBIGUOUS SUPERVISION | authKW | 328340 | 1% | 100% | 1 |
| 9 | APPROXIMATELY CONTIGUOUS SEQUENCES | authKW | 328340 | 1% | 100% | 1 |
| 10 | APPROXIMATING KERNELS | authKW | 328340 | 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 | 5563 | 63% | 0% | 59 |
| 2 | Computer Science, Information Systems | 444 | 18% | 0% | 17 |
| 3 | Computer Science, Theory & Methods | 442 | 19% | 0% | 18 |
| 4 | Automation & Control Systems | 347 | 13% | 0% | 12 |
| 5 | Computer Science, Software Engineering | 42 | 5% | 0% | 5 |
| 6 | Engineering, Electrical & Electronic | 30 | 13% | 0% | 12 |
| 7 | Computer Science, Interdisciplinary Applications | 17 | 4% | 0% | 4 |
| 8 | Information Science & Library Science | 14 | 2% | 0% | 2 |
| 9 | Computer Science, Cybernetics | 10 | 1% | 0% | 1 |
| 10 | Statistics & Probability | 4 | 2% | 0% | 2 |
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 | COMP SECUR GRP 1 | 328340 | 1% | 100% | 1 |
| 2 | INFORMAT ASSURANCE BRANCH | 328340 | 1% | 100% | 1 |
| 3 | INTELLIGENT DATA ANAL 1 | 328340 | 1% | 100% | 1 |
| 4 | IP VOICE SERV | 328340 | 1% | 100% | 1 |
| 5 | CIUTAT POLITECN INNOVACIO | 164169 | 1% | 50% | 1 |
| 6 | GRP M2SF | 82084 | 1% | 25% | 1 |
| 7 | ITC IRST | 52531 | 2% | 8% | 2 |
| 8 | MASDAR SCI TECHNOL | 36480 | 1% | 11% | 1 |
| 9 | SERV INFRASTRUCT | 36480 | 1% | 11% | 1 |
| 10 | EQUIPE CMAO | 32832 | 1% | 10% | 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 | JOURNAL OF MACHINE LEARNING RESEARCH | 20947 | 11% | 1% | 10 |
| 2 | DATA MINING AND KNOWLEDGE DISCOVERY | 5071 | 3% | 1% | 3 |
| 3 | KNOWLEDGE AND INFORMATION SYSTEMS | 2800 | 3% | 0% | 3 |
| 4 | STATISTICAL ANALYSIS AND DATA MINING | 2625 | 1% | 1% | 1 |
| 5 | WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY | 1773 | 1% | 1% | 1 |
| 6 | JOURNAL OF WEB ENGINEERING | 1682 | 1% | 1% | 1 |
| 7 | LECTURE NOTES IN ARTIFICIAL INTELLIGENCE | 1606 | 10% | 0% | 9 |
| 8 | INTERNATIONAL JOURNAL OF FOUNDATIONS OF COMPUTER SCIENCE | 1384 | 2% | 0% | 2 |
| 9 | INTERNATIONAL JOURNAL ON DOCUMENT ANALYSIS AND RECOGNITION | 1286 | 1% | 0% | 1 |
| 10 | MACHINE LEARNING | 1059 | 2% | 0% | 2 |
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 | TREE KERNELS | 1313361 | 4% | 100% | 4 | Search TREE+KERNELS | Search TREE+KERNELS |
| 2 | RATIONAL KERNELS | 1050687 | 4% | 80% | 4 | Search RATIONAL+KERNELS | Search RATIONAL+KERNELS |
| 3 | STRING KERNELS | 1050679 | 9% | 40% | 8 | Search STRING+KERNELS | Search STRING+KERNELS |
| 4 | LEARNING WITH SEQUENTIAL DATA | 656680 | 2% | 100% | 2 | Search LEARNING+WITH+SEQUENTIAL+DATA | Search LEARNING+WITH+SEQUENTIAL+DATA |
| 5 | ADAPTIVE CONSTRAINT PROPAGATION | 437786 | 2% | 67% | 2 | Search ADAPTIVE+CONSTRAINT+PROPAGATION | Search ADAPTIVE+CONSTRAINT+PROPAGATION |
| 6 | SEQUENCE KERNELS | 437786 | 2% | 67% | 2 | Search SEQUENCE+KERNELS | Search SEQUENCE+KERNELS |
| 7 | SEQUENCE KERNEL | 422148 | 3% | 43% | 3 | Search SEQUENCE+KERNEL | Search SEQUENCE+KERNEL |
| 8 | AMBIGUOUS SUPERVISION | 328340 | 1% | 100% | 1 | Search AMBIGUOUS+SUPERVISION | Search AMBIGUOUS+SUPERVISION |
| 9 | APPROXIMATELY CONTIGUOUS SEQUENCES | 328340 | 1% | 100% | 1 | Search APPROXIMATELY+CONTIGUOUS+SEQUENCES | Search APPROXIMATELY+CONTIGUOUS+SEQUENCES |
| 10 | APPROXIMATING KERNELS | 328340 | 1% | 100% | 1 | Search APPROXIMATING+KERNELS | Search APPROXIMATING+KERNELS |
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 | YIN, CH , TIAN, SF , MU, SM , SHAO, C , (2008) EFFICIENT COMPUTATIONS OF GAPPED STRING KERNELS BASED ON SUFFIX KERNEL.NEUROCOMPUTING. VOL. 71. ISSUE 4-6. P. 944-962 | 6 | 67% | 2 |
| 2 | CANCEDDA, N , MAHE, P , (2009) FACTORED SEQUENCE KERNELS.NEUROCOMPUTING. VOL. 72. ISSUE 7-9. P. 1407-1413 | 3 | 100% | 6 |
| 3 | YIN, CH , TIAN, SF , MU, SM , (2006) A FAST BIT-PARALLEL ALGORITHM FOR GAPPED STRING KERNELS.NEURAL INFORMATION PROCESSING, PT 1, PROCEEDINGS. VOL. 4232. ISSUE . P. 634-641 | 4 | 80% | 0 |
| 4 | RIECK, K , WRESSNEGGER, C , BIKADOROV, A , (2012) SALLY: A TOOL FOR EMBEDDING STRINGS IN VECTOR SPACES.JOURNAL OF MACHINE LEARNING RESEARCH. VOL. 13. ISSUE . P. 3247-3251 | 4 | 67% | 1 |
| 5 | TSIVTSIVADZE, E , PAHIKKALA, T , BOBERG, J , SALAKOSKI, T , (2009) LOCALITY KERNELS FOR SEQUENTIAL DATA AND THEIR APPLICATIONS TO PARSE RANKING.APPLIED INTELLIGENCE. VOL. 31. ISSUE 1. P. 81 -88 | 4 | 67% | 1 |
| 6 | WANG, TH , ZHONG, J , CHEN, JT , HU, Q , (2015) COMPOSITE KERNELS FOR AUTOMATIC WORD SENSE DISAMBIGUATION.JOURNAL OF COMPUTATIONAL AND THEORETICAL NANOSCIENCE. VOL. 12. ISSUE 4. P. 619 -623 | 5 | 45% | 0 |
| 7 | GIULIANO, C , GLIOZZO, AM , STRAPPARAVA, C , (2009) KERNEL METHODS FOR MINIMALLY SUPERVISED WSD.COMPUTATIONAL LINGUISTICS. VOL. 35. ISSUE 4. P. 513-528 | 3 | 75% | 6 |
| 8 | TIAN, SF , MU, SM , YIN, CH , (2007) SEQUENCE-SIMILARITY KERNELS FOR SVMS TO DETECT ANOMALIES IN SYSTEM CALLS.NEUROCOMPUTING. VOL. 70. ISSUE 4-6. P. 859 -866 | 4 | 57% | 5 |
| 9 | RIECK, K , WRESSNEGGER, C , (2016) HARRY: A TOOL FOR MEASURING STRING SIMILARITY.JOURNAL OF MACHINE LEARNING RESEARCH. VOL. 17. ISSUE . P. - | 3 | 60% | 0 |
| 10 | HAN, XW , YU, M , ZHU, CH , ZHAO, TJ , (2010) A SEQUENCE KERNEL METHOD FOR CHINESE SUBCATEGORIZATION ANALYSIS.CHINESE JOURNAL OF ELECTRONICS. VOL. 19. ISSUE 3. P. 414-418 | 2 | 100% | 0 |
Classes with closest relation at Level 1 |