In [27]:
text = """
28. Dobrean, D., Dioşan, L., A Comparative Study of Software Architectures in Mobile Applications, Studia Universitas Babes-Bolyai, Seria Informatica, 2019, LXIV(2):49-64
27. Dioșan L., Andreica A., Enescu A, The Use of Simple Cellular Automata in Image Processing, Studia Universitas Babes-Bolyai, Seria Informatica, 2017, LXII(1):1-12
26. Mocan R., Dioșan L., Support Vector Machine and Boosting based Multiclass Classification for Traffic Scene Obstacles, Studia Universitas Babes-Bolyai, Seria Informatica, 2016, LXI(2):70-81
25. Mocan R., Dioșan L., Obstacle Recognition in Traffic by Adapting the HOG Descriptor and Learning in Layers, Studia Universitas Babes-Bolyai, Seria Informatica, 2015, LX(2):47-54
24. Fratean Ș., Dioșan L., Descriptors fusion and genetic programming for breast cancer detection, Studia Universitas Babes-Bolyai, Seria Informatica, 2015, LX(1):88-97
23. Dioşan L., Andreica A., Multi-objective breast cancer classification by using Multi-Expression Programming, Applied Intelligence, 2015, 43(3):499-511
22. A. Andreica, L. Diosan, R. D. Gaceanu, A. Sîrbu, Pedestrian Recognition by Using Kernel Descriptors, Studia Universitas Babes-Bolyai, Seria Informatica, 2013, LVIII, 2, 77-89- pdf, bibTex
21. Dioşan L., Rogozan A. and Pecuchet J.-P., Improving classification performance of Support Vector Machine by genetically optimisation of kernel shape and hyper-parameters, Applied Intelligence, 36(2),280-294, 2012 – pdf, bibTex
20. L. Diosan, A. Rogozan, How the Kernels Can Influence Image Classification Performance, Studia Universitas Babes-Bolyai, Seria Informatica, 2012, LVII, 4, 97-109 – pdf, bibTex
19. Diosan L., Oltean M., Friction-based sorting, Natural Computing, 10(1),527-539, 2011 – pdf, bibTex
18. Dioşan L., Rogozan A. and Pecuchet J.-P., Learning SVM with complex multiple kernels evolved by Genetic Programming, International Journal of Artificial Intelligence Tools, 19(5),647-677, 2010 – pdf, bibTex
17. A. Sirbu, L. Diosan, A. Rogozan, J.P. Pecuchet, Alignment of Custom Standards by Machine Learning Algorithms, Studia Universitas Babes-Bolyai, Seria Informatica, 2010,LV,3 – pdf, bibTex
16. A. Sirbu, L. Diosan, A. Rogozan, J.-P. Pecuchet, Model Alignment by Using the Concept Definition, Studia Universitas Babes-Bolyai, Seria Informatica, 2010,LV,1 – pdf, bibTex
15. Diosan Laura, Mihai Oltean, Evolutionary design of Evolutionary Algorithms, Genetic Programming and Evolvable Machines, Springer, Vol 10, Issue 3, pp. 263-306, 2009 – pdf, bibTex
14. Oltean M., Grosan C., Diosan L., Mihaila C., Genetic Programming with linear representation – a survey, International Journal on Artificial Intelligence Tools (IJAIT), Vol 18, pp. 197-238, 2009 – pdf, bibTex
13. Oltean M., Diosan L., An autonomous GP-based system for regression and classification problems, Applied Soft Computing, 9(1), 49-60, 2008 – pdf, bibTex
12. Diosan L., Oltean M., What else is the evolution of PSO telling us?, Journal of Artificial Evolution and Applications, 1(1), 1-12, 2008- pdf bibTex
11. Diosan L., Dumitrescu D., Evolutionary coalition formation in full connected and scale free networks, International Journal of Computers, Communications & Control (IJCCC) – special issue ICCCC, 3, 259-265, 2008 – bibTex
10. Dioşan L., Rogozan A., Pecuchet J.P., Evolutionary Optimisation of Kernel Functions for SVMs, Studia Universitas Babes-Bolyai, Seria Informatica, 2008, LIII, 1, 29-44 – pdf, bibTex
9. Diosan L., Oltean M., Evolving the update strategy of the Particle Swarm Optimisation algorithms, International Journal on Artificial Intelligence Tools (IJAIT), 1(16), 87-110, 2007 – pdf, bibTex
8. Dioşan L., Dumitrescu, D., Evolutionary Coalition Formation in Complex Networks, Studia Universitas Babes-Bolyai, Seria Informatica, 2007, LII, 2, 115-129 – pdf, bibTex
7. Diosan L., Fanea A., Dumitrescu D., Genetic Algorithms based on Ising Machine, The International Journal of Information Technology and Intelligent Computing, 2007 1(3)585-594 – bibTex
6. Fanea A., Diosan L., Component-Based Model Using P-Systems, The International Journal of Information Technology and Intelligent Computing, 2007 1(3)499-508 – bibTex
5. Dioşan, L., Oltean M., Evolving the structure of the Particle Swarm Optimization algorithms , EuroGP2006 & EvoCOP2006, Lecture Notes in Computer Science, Springer Verlag Berlin, Budapest, Hungary, 2006, pp. 25-36, 2006 – pdf, bibTex
4. Dioşan, L., Oltean, M., Evolving crossover operators for function optimization, , EuroGP2006 & EvoCOP2006, Lecture Notes in Computer Science, Springer Verlag Berlin, Budapest, Hungary, 2006 -, 2006, pp. 97-108, 2006 – pdf, bibTex
3. Fanea A., Motogna S., Dioşan L., Automata-based Component Composition Analysis, Studia Universitas Babes-Bolyai, Seria Informatica, 2006, LI, 1, 13-20 – pdf, bibTex
2. Dioşan, L., Dumitrescu, D., David D., Far From Equilibrium Computation and Particle Swarm Optimization, Acta Universitatis Apulensis, 2006, 11, 1, 339-352 – pdf, bibTex
1. Fanea, A., Dioşan, L., Components Execution Order using Genetic Algorithms, Studia Universitas Babes-Bolyai, Seria Informatica, 2005, L, 2, 23-32 – pdf, bibTex
72. Mursa B., Diosan, L., Andreica, A., Complex networks: How micro and macroscale layers communicate through meso components?, MECO45 45th Conference of the Middle European Cooperation in Statistical Physics, 2020, accepted
71. Marginean, R., Andreica, A., Diosan, L., Bálint, Z., Stochastic remote neighborhoods control GrowCut’s segmentation semantics, MECO45 45th Conference of the Middle European Cooperation in Statistical Physics, 2020, accepted
70. Limboi, S., Dioșan, L., Hybrid features for Twitter Sentiment Analysis, The 19th International Conference on Artificial Intelligence and Soft Computing , 2020, accepted
69. Mărginean, R., Manole, S., Popa, L., Coman, M., Pop, S., Budurea, C., Andreica, A., Dioşan, L., Bálint, Z., Initial validation of an automatic algorithm for whole heart segmentation from cardiac MRI images using atrial volume determination, European congress of radiology (ECR 2020) https://www.myesr.org/congress, 2020, accepted
69. Mărginean, R., Popa, L., Coman, M., Manole, S., Coman, V., Andreica, A., Dioşan, L., Bálint, Z., Extended region growing algorithm for whole heart segmentation from cardiac MRI images, European Society of Cardiovascular Radiology Congress (ESCR 2019) https://www.escr.org/congress/, 2019, accepted
67. Dioşan, L., Motogna, S., Artificial intelligence meets software engineering in the classroom, EASEAI@ESEC 2019, 2019, 35-38
66. Enescu, A., Andreica, A., Dioşan, L., Evolved cellular automata for edge detection, GECCO 2019 (Proceedings of the Genetic and Evolutionary Computation Conference Companion, ACM, Eds.: Manuel López-Ibáñez), 2019, 316-317
65. Enescu, A., Andreica, A., Dioşan, L., Evolved Cellular Automata for Edge Detection in Binary Images, ICCP 2019, 2019, accepted
64. Tolciu, T., Toma, S., Matei, C., Diosan, L., An initial study of feature extraction’s methods in facial expression recognitio, ICCP 2019, 2019, accepted
63. Enescu, A., Andreica, A., Dioşan, L., Evolved Cellular Automata for Grey Images, SYNASC 2019, 2019, accepted
62. Dumitru, D., Andreica, A., Diosan, L., Balint, Z., Particle Swarm Optimization of Cellular Automata Rules for Edge Detection, SYNASC 2019, 2019, accepted
61. Marginean, R., Andreica, A., Diosan, L., Balint, Z., Autonomous image segmentation by Competitive Unsupervised GrowCut , SYNASC 2019, 2019, accepted
60. Mursa, B., Andreica, A., Dioşan, L., An empirical analysis of the correlation between the motifs frequency and the topological properties of complex networks, KES 2019 (Proceedings of the 23rd International Conference on Knowledge-Based and Intelligent Information Engineering Systems, September, 2019, Procedia Computer Science, Volume 159, 2019, Pages 333-341, Elsevier, Eds.: Imre J. Rudas, Csirik Janos, Carlos Toro, Janos Botzheim, Robert J. Howlett, Lakhmi C. Jain), 2019, 333-341
59. Mursa, B., Andreica, A., Dioşan, L., Mining network motif discovery by learning techniques, HAIS 2019 (In: Pérez García H., Sánchez González L., Castejón Limas M., Quintián Pardo H., Corchado Rodríguez E. (eds) Hybrid Artificial Intelligent Systems. HAIS 2019. Lecture Notes in Computer Science, vol 11734. Springer, Cham), 2019, 73-84
58. Dobrean, D., Dioşan, L., An analysis system for mobile applications MVC software architectures, ICSOFT 2019 (The 14th International Conference on Software Technologies (ICSOFT 2019), publisher SciTePress, eds.: Marten van Sinderen and Leszek Maciaszek), 2019, 178-185
57. Dobrean, D., Dioşan, L., Model View Controller in iOS mobile applications development, SEKE 2019 (Proc. of the 31st International Conference on Software Engineering Knowledge Engineering, 2019), 2019, 547-552
56. Mursa, B., Andreica, A., Dioşan, L., Study of connection between articulation points and network motifs in complex networks, ECIS 2019 (In Proceedings of the 27th European Conference on Information Systems (ECIS), Stockholm & Uppsala, Sweden, June 8-14, 2019. ISBN 978-1-7336325-0-8 Research Papers.
https://aisel.aisnet.org/ecis2019_rp/127), 2019, 43479
55. Mursa, B., Andreica, A., Dioşan, L., Parallel acceleration of Network Motif detection, SYNASC 2018, 2018, 191-198
54. Nechita, S., Dioşan, L., A four-phase meta-heuristic algorithm for solving large scale instances of the Shift minimization personnel task scheduling problem, SYNASC 2018, 2018, 394-400
53. Marinescu, A., Balint, Z., Dioşan, L., Andreica, A., Unsupervised and Fully Autonomous 3D Medical Image Segmentation based on Grow Cut, SYNASC 2018, 2018, 401-408
52. Enescu, A., Andreica, A., Dioşan, L., Evolving Cellular Automata for Two stage Edge Detection, SYNASC 2018, 2018, 417-424
51. Marinescu, A., Balint, Z., Dioşan, L., Andreica, A., Dynamic Autonomous Image Segmentation based on GrowCut, ESANN 2018, 2018, 67-72
50. Serban C., Vescan A., Dioșan L., Chisalita-Cretu C., Requirement Dependencies–based Formal Approach for Test Case Prioritization in Regression Testing, ICCP 2017, 2017, 181-188
49. Sandor A., Dioșan L., Andreica A., Hybrid topology in GrowCut algorithm, ECAL 2017, Late-breaking abstracts,, 2017, 19-20
48. Dioșan L., Andreica A., Voiculescu I., Boros I., Avenues for the Use of Cellular Automata In Image Processing, Applications of Evolutionary Computation. EvoApplications 2017. Lecture Notes in Computer Science, vol 10199, 2017, 282-296
47. Voiculescu I., Boros I., Popovici N., Dioșan L., Andreica A., Interval{state cellular automata and their applications to image segmentation, SWIMM 2017, 2017, accepted
46. Dioșan L., Andreica A., Voiculescu I., Parameterized Cellular Automata in Image Segmentation, SYNASC 2016, 2016, 199-205
45. Mocan R., Dioșan L., Multiclass classification based on clustering approaches for obstacle recognition in traffic scenes, the 2016 IEEE 12th International Conference on Intelligent Computer Communication and Processing, 2016, 257-261
44. Andreica A., Dioșan L., Șandor A., Exploring Various Neighborhoods in Cellular Automata for Image Segmentation, the 2016 IEEE 12th International Conference on Intelligent Computer Communication and Processing, 2016, 249-255
43. Andreica A., Dioșan L., Șandor A., Investigation of Cellular Automata Neighbourhoods in Image Segmentation, 6th International Workshop on Combinations of Intelligent Methods and Applications (CIMA 2016), 22nd European Conference on Artificial Intelligence (ECAI 2016), 2016, 1-8
42. Rus, A., Rogozan, A., Dioșan, L., Benshrair, A., Pedestrian recognition using a dynamic modality fusion approach, ICCP, 2015, 393-400
41. Rus, A., Rogozan, A., Dioșan, L., Benshrair, A., Pedestrian recognition by using a dynamic modality selection approach, ITSC, 2015, 1862 – 1867
40. Rus, A., Rogozan, A., Dioșan, L., Benshrair, A., Pedestrian recognition by using a kernel-based multi-modality approach, SYNASC 2014, 2014, 258-263
39. Sîrbu A., Dioșan L., Rogozan, A., Pécuchet, J.-P., An Automatic Approach In Ontology Alignment, ZAC 2012, pp. 159-163, 2012 – bibTex
38. Sîrbu A., Dioșan L., Rogozan, A., Pécuchet, J.-P., Automatic Alignment of Custom Standards, ZAC 2010, pp.11-14, 2010 – bibTex
37. Diosan L., A. Rogozan, J.-P. Pecuchet, Improving Definition Alignment by SVM with a Kernel of Kernels, KEPT 2009, 180-186, 2009 – bibTex
36. Dioşan, L., and Dumitrescu, D, Context-based Networks – Scale-free or not?Proceedings of the Symposium Colocviul Academic Clujean de INFORMATICA, 2008 – bibTex
35. Dioşan, L., Dumitrescu, D., Evolutionary coalition formation in full connected and scale free networks, The IEEE 2nd International Conference on Computers, Communications & Control (ICCCC 2008), 2008, pp. 259-264 – bibTex
34. Dioşan, L., Rogozan, A., Pécuchet, J.-P., Apport des traitements morpho-syntaxiques pour l’alignement des définitions par SVM, 8 ème édition de la conférence francophone Extraction et Gestion des Connaissances, EGC, 2008 , 2008, pp. 201-202 – bibTex
33. Dioşan, L., Rogozan, A., Pécuchet, J.-P., Une approche évolutive pour générer des noyaux multiples, 16e congres francophone AFRIF-RFIA, Recnaissance des Formes et Intelligence Artificielle, 2008, 2008, pp. 498-506 – bibTex
32. Oltean, M., Diosan, L., An adaptive GP strategy for evolving digital circuits, 12th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems, KES 2008, Zagreb, Croatia, 2008, 2008, pp. 376-383 – pdf, bibTex
31. Dioşan, L., Rogozan, A., Pécuchet, J.-P., Evolutionary Optimisation of Kernel and Hyper-Parameters for SVM, MCO 2008, 2008, pp. 107-116 – pdf, bibTex
30. Dioşan, L., Rogozan, A., Pécuchet, J.-P., Automatic Alignment of Medical vs. General Terminologies, 11th European Symposium on Artificial Neural Networks, ESANN 2008, 2008, pp. 487-492 – pdf, bibTex
29. Dioşan, L., Rogozan, A., Pécuchet, J.-P., Optimising multiple kernels for SVM by Genetic Programming, EuroGP2008 & EvoCOP2008, Lecture Notes in Computer Science, Springer Verlag Berlin, Napoly, Italy, 2008, pp. 230-241 – pdf, bibTex
28. Dioşan, L., Rogozan, A., Pécuchet, J.-P., Alignement des définitions par un apprentissage SVM avec une optimisation des hyper-paramètre, Grand Colloque STIC 2007, 2007, pp. 1-6 – bibTex
27. Lortal, G., Dioşan, L., Pécuchet, J.-P., Rogozan, A., Du terme au mot: Utilisation de techniques de classification pour l’alignement de terminologies, Terminologie et Intelligence Artificielle, TIA2007, Sophia Antipolis, France, 2007 – bibTex
26. Dioşan, L., Oltean, M., A. Rogozan, J. P. Pecuchet, Improving SVM Performance using a Linear Combination of Kernels, ICANNGA’07, International Conference on Adaptive and Natural Computing Algorithms, Warsaw, Poland, LNCS, 4432, 2007, pp. 218-227 – pdf, bibTex
25. Dioșan, L., and Oltean, M. Who’s better? PESA or NSGA II? In The International Conference on Intelligent Systems Design and Applications, Workshop on Evolutionary Multi-objective Optimization: Design and Applications, ISDA 2007, Rio de Janeiro, Brazil (2007), IEEE Computer Society, pp. 869–874 – pdf, bibTex
24. Dioşan, L., Dumitrescu, D., A Hybrid Genetic Algorithm based on the Potts system, Workshop, NCA, 7th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC07, 2007, pp. 453-456 – pdf, bibTex
23. Dioşan, L., Rogozan, A., Pécuchet, J.-P., Evolving Kernel Functions for SVMs by Genetic Programming, The 2007 International Conference on Machine Learning and Applications ( ICMLA’07), Ohio, USA, 2007, pp. 19-24 – pdf, bibTex
22. Dioşan, L., Oltean, M., Observing the swarm behaviour during its evolutionary design, The Genetic and Evolutionary Computation Conference, GECCO 2007, 2007, pp. 2667-2674 – pdf, bibTex
21. Muntean O., Dioşan, L., Oltean, M., Best SubTree Genetic Programming, The Genetic and Evolutionary Computation Conference, GECCO 2007, 2007, pp. 1667-1673 – pdf, bibTex
20. Muntean O., Dioşan, L., Oltean, M., Solving the even-n-parity problems using Best Sub Tree Genetic Programming, The NASA/ESA Conference on Adaptive Hardware and Systems, AHS 2007, 2007, pp. 511-518 – pdf, bibTex
19. Dioşan, L., Oltean, M., A. Rogozan, J. P. Pecuchet, Genetically Designed Multiple-Kernels for Improving the SVM Performance, The Genetic and Evolutionary Computation Conference, GECCO 2007, 2007, pp. 1873-1874 – pdf, bibTex
18. Dioşan, L., Oltean, M., Evolving Evolutionary Algorithms using Evolutionary Algorithms, The Genetic and Evolutionary Computation Conference, GECCO 2007, 2007, pp. 2442 – 2449 – pdf, bibTex
17. Dioşan, L., Oltean, M., A. Rogozan, J. P. Pecuchet, Improving SVM Performance using a Linear Combination of Kernels, ICANNGA’07, International Conference on Adaptive and Natural Computing Algorithms, Warsaw, Poland, LNCS, 4432, 2007, pp. 218-227 – pdf, bibTex
16. Diosan, L., and Oltean, M. Evolving kernel function for Support Vector Machines. In The 17th European Conference on Arti cial Intelligence, Evolutionary Computation Workshop, ECAI’06, Riva del Garda, Italy (2006), S. Cagnoni, Ed., Trento University, pp. 11–1 – pdf, bibTex
15. Vescan, A., and Diosan, L. Computational intelligence-based model for component composition. In International Conference on Computers, Communications and Control, ICCCC 2006, Agora University, Oradea, Romania (2006), M.-J. M. Ioan Dzitac, Florin-Gheorghe Filip, Ed., Universiatea din Oradea, pp. 474–479 – pdf, bibTex
14. Vescan, A., and Diosan, L. Evolutionary approach for behaviour component composition. In International Conference on Computers, Communications and Control, ICCCC 2006, Agora University, Oradea, Romania (2006), F.-G. F. Ioan Dzitac and M.-J. Manolescu, Eds., Universiatea din Oradea, pp. 480–485 – pdf, bibTex
13. David, D., Dioşan, L., Dumitrescu, D., A Far From Equilibrium Computation System, the 6th IEEE Communications International Conference, Bucuresti, 2006, pp. 245-248 – bibTex
12. David, D., Dioşan, L., and Dumitrescu, D., A Far From Equilibrium Model for the Classification Problem, Proceedings of the Symposium Colocviul Academic Clujean de INFORMATICA, 2006, pp. 1- 6 – bibTex
11. Dioşan, L., Mihailescu, I.,Identifying and Forecasting the Efficient Frontier Using Evolutionary Computation, Proceedings of the Symposium Colocviul Academic Clujean de INFORMATICA, 2006, pp. 97-102 – bibTex
10. David, D., Dioşan, L., and Dumitrescu, D., A new Computational Model Based Ising Machine, Proceedings of the Symposium Colocviul Academic Clujean de INFORMATICA, 2005, 99-104 – bibTex
9. Dioşan, L., and Dumitrescu, D., Cellular Computing using Cellular Neural Networks – a survive, Proceedings of the Symposium Colocviul Academic Clujean de INFORMATICA, 2005, pp. 219-225 – bibTex
8. Dioşan, L., Fanea, A., Designing a Component-Based Machine using Multi Expression Programming, Proceedings of the Symposium Colocviul Academic Clujean de INFORMATICA, 2005, pp. 93-98 – bibTex
7. David, D., Dioşan, L., Dumitrescu, D., A New Nature-Inspired Computational Model – Ising Model with Rays, Proceeding of7th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC05, IEEE Computer Society, 2005, pp. 315-320 – pdf, bibTex
6. Dioşan, L., A multi-objective evolutionary approach to the portfolio optimization problem, International Conference on Computational Intelligence for Modelling Control and Automation, CIMCA 2005, Vienna, Austria, IEEE Press, 2005, pp. 183-188 – pdf, bibTex
5. Dumitrescu, D., Dioşan, L., Serban G., Campan, A., Daraban, A., Pop, H. F., Tambulea.L., Cooperative Learning for Distributed Data Mining, International Conference – the Impact of European Integration on the National Economy, Ed. Risoprint, Cluj-Napoca, 2005, 2005, pp. 432 – 440 – bibTex
4. David, D., Dioşan, L., Dumitrescu, D., A new Computational Model Based on Ising Machine – Ising model with rays, , Workshop, NCA, 7th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC05 September 25-29, Timisoara, 2005, 2005, pp. 45-51 – bibTex
3. Dioşan, L., Dumitrescu, D., David D., Far From Equilibrium Computation and Particle Swarm Optimization, International Conference on Theory and Applications in Mathematics and Informatics – ICTAMI 2005 September 15-18, 2005, pp. 42-43 – bibTex
2. Oltean, M., Sas, L., A Comparison of Genetic Programming and Statistical Methods for Solving Prediction Problems, International Conference on Computers and Communications, ICCC 2004 Mai 27-29, Băile Felix – Oradea, 2004, pp. 321-326 – bibTex
1. Sas (Dioșan), L., Statistical methods versus Genetic Algorithms – the case of market model, Proceedings of the Symposium Colocviul Academic Clujean de INFORMATICA, 2004, pp. 111-116 – bibTex
"""
In [44]:
papers = []
for line in text.split('\n'):
fields_csv = line.split(',')
title = None
affiliation = None
date = None
for k in fields_csv:
if len(k.split(' ')) > 3:
if title == None:
title = k
elif affiliation == None:
affiliation = k
date_field = True
if len(k) > 2 and (k[0] == '2' or k[1] == '2'):
for c in k.split('-')[0]:
if c not in "12345657890 ":
date_field = False
if date_field and date == None:
date = k
print("title: {0}".format(title))
print("affiliation: {0}".format(affiliation))
print("date: {0}".format(date))
papers.append((title, affiliation, date))
In [45]:
papers
Out[45]:
In [15]:
import mariadb
import json
In [17]:
with open('../credentials.json', 'r') as crd_json_fd:
json_text = crd_json_fd.read()
json_obj = json.loads(json_text)
In [18]:
credentials = json_obj["Credentials"]
username = credentials["username"]
password = credentials["password"]
In [47]:
table_name = "publications"
db_name = "ubbcluj"
In [49]:
mariadb_connection = mariadb.connect(user=username, password=password, database=db_name)
mariadb_cursor = mariadb_connection.cursor()
In [67]:
for paper in papers[1:-1]:
title = ""
pub_date = ""
affiliations = ""
try:
pub_date = paper[2].lstrip()
pub_date = str(pub_date) + "-01-01"
if len(pub_date) != 10:
pub_date = ""
except:
pass
try:
title = paper[0].lstrip()
except:
pass
try:
affiliations = paper[1].lstrip()
except AttributeError:
pass
insert_string = "INSERT INTO {0} SET ".format(table_name)
insert_string += "Title=\'{0}\', ".format(title)
insert_string += "ProfessorId=\'{0}\', ".format(4)
if pub_date != "":
insert_string += "PublicationDate=\'{0}\', ".format(str(pub_date))
insert_string += "Authors=\'{0}\', ".format("EMPTY")
insert_string += "Affiliations=\'{0}\' ".format(affiliations)
print(insert_string)
try:
mariadb_cursor.execute(insert_string)
except mariadb.ProgrammingError as pe:
print("Error")
raise pe
except mariadb.IntegrityError:
continue
In [68]:
mariadb_connection.close()