Clusters to Terms MappingΒΆ

>>> from techminer2.packages.networks.co_authorship.organizations import ClustersToTermsMapping
>>> mapping = (
...     ClustersToTermsMapping()
...     #
...     # FIELD:
...     .having_terms_in_top(20)
...     .having_terms_ordered_by("OCC")
...     .having_term_occurrences_between(None, None)
...     .having_term_citations_between(None, None)
...     .having_terms_in(None)
...     #
...     # COUNTERS:
...     .using_term_counters(True)
...     #
...     # NETWORK:
...     .using_clustering_algorithm_or_dict("louvain")
...     .using_association_index("association")
...     #
...     # DATABASE:
...     .where_root_directory_is("example/")
...     .where_database_is("main")
...     .where_record_years_range_is(None, None)
...     .where_record_citations_range_is(None, None)
...     .where_records_match(None)
...     #
...     .run()
... )
>>> from pprint import pprint
>>> pprint(mapping)
{0: ['Goethe Univ Frankfurt (DEU) 2:1065',
     'Pennsylvania State Univ (USA) 1:0576',
     'Singapore Manag Univ (SMU) (SGP) 1:0576',
     'Univ of Delaware (USA) 1:0576'],
 1: ['Columbia Grad Sch of Bus (USA) 1:0390',
     'Stanford GSB and the Hoover Institution, United States (USA) 1:0390',
     'Univ of Chicago (USA) 1:0390',
     'Univ of Texas at Austin (USA) 1:0390'],
 2: ['Baylor Univ (USA) 2:0395',
     'Univ of New South Wales (AUS) 2:0340',
     'Univ of Sydney (AUS) 2:0300'],
 3: ['Fed Reserv Bank of Philadelphia (USA) 3:0317',
     'Fed Reserv Bank of Chicago (USA) 2:0253'],
 4: ['Hankyong Nac Univ (KOR) 1:0557', 'Western Illinois Univ (USA) 1:0557'],
 5: ['Univ of Zurich (CHE) 3:0434'],
 6: ['Max Planck Inst for Innovation and Competition (DEU) 2:0358'],
 7: ['Pace Univ (USA) 2:0323'],
 8: ['Sungkyunkwan Univ (KOR) 2:0307'],
 9: ['Univ of Latvia (LVA) 2:0163']}