Terms to Cluster Mapping

Example

>>> from techminer2.packages.networks.co_occurrence.descriptors import TermsToClustersMapping
>>> mapping = (
...     TermsToClustersMapping()
...     #
...     # 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("examples/fintech/")
...     .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) 
{'BANKS 08:1049': 0,
 'CHINA 06:0673': 1,
 'CONSUMERS 07:0925': 0,
 'DATA 07:1086': 0,
 'FINANCE 10:1188': 1,
 'FINANCIAL_SERVICES 06:1116': 1,
 'FINANCIAL_TECHNOLOGIES 12:1615': 1,
 'FINTECH 38:6131': 0,
 'FINTECH_COMPANIES 05:1072': 0,
 'INFORMATION_TECHNOLOGY 05:1101': 0,
 'INNOVATION 08:1816': 1,
 'PRACTITIONER 06:1194': 0,
 'REGULATORS 08:0974': 1,
 'SERVICES 06:1089': 1,
 'TECHNOLOGIES 15:1633': 1,
 'THE_DEVELOPMENT 09:1293': 1,
 'THE_FINANCIAL_INDUSTRY 09:2006': 0,
 'THE_FINANCIAL_SECTOR 05:1147': 0,
 'THE_FINANCIAL_SERVICES_INDUSTRY 06:1237': 1,
 'THE_IMPACT 06:0908': 0}

Example

>>> mapping = (
...     TermsToClustersMapping()
...     #
...     # 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(False)
...     #
...     # NETWORK:
...     .using_clustering_algorithm_or_dict("louvain")
...     .using_association_index("association")
...     #
...     # DATABASE:
...     .where_root_directory_is("examples/fintech/")
...     .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) 
{'BANKS': 0,
 'CHINA': 1,
 'CONSUMERS': 0,
 'DATA': 0,
 'FINANCE': 1,
 'FINANCIAL_SERVICES': 1,
 'FINANCIAL_TECHNOLOGIES': 1,
 'FINTECH': 0,
 'FINTECH_COMPANIES': 0,
 'INFORMATION_TECHNOLOGY': 0,
 'INNOVATION': 1,
 'PRACTITIONER': 0,
 'REGULATORS': 1,
 'SERVICES': 1,
 'TECHNOLOGIES': 1,
 'THE_DEVELOPMENT': 1,
 'THE_FINANCIAL_INDUSTRY': 0,
 'THE_FINANCIAL_SECTOR': 0,
 'THE_FINANCIAL_SERVICES_INDUSTRY': 1,
 'THE_IMPACT': 0}