Themes#
>>> from techminer2.tech_mining.document.kmeans import themes
>>> x = themes(
... field='words',
... #
... # ITEM FILTERS:
... top_n=50,
... occ_range=(None, None),
... gc_range=(None, None),
... custom_items=None,
... #
... # KMEANS PARAMS:
... n_themes=6,
... init="k-means++",
... n_init=10,
... max_iter=300,
... kmeans_tol=0.0001,
... algorithm="auto",
... #
... # DATABASE PARAMS:
... root_dir="example/",
... database="main",
... year_filter=(None, None),
... cited_by_filter=(None, None),
... )
>>> print(x.to_markdown())
| | TH_0 | TH_1 | TH_2 | TH_4 | TH_5 |
|---:|:-------------------|:--------------------|:--------------------|:--------------------|:-----------------|
| 0 | © 42:6879 | technology 39:6527 | fintech 50:8135 | innovation 19:3070 | increase 11:1716 |
| 1 | study 23:3158 | new 26:4793 | financial 44:7123 | development 19:2499 | company 09:1671 |
| 2 | model 19:3820 | service 26:4327 | research 17:2383 | paper 14:2240 | |
| 3 | author 18:2443 | industry 23:4517 | finance 14:2199 | well 13:1908 | |
| 4 | data 17:2392 | market 17:3446 | make 13:1355 | offer 13:1850 | |
| 5 | result 14:2183 | sector 13:2748 | consumer 12:1472 | bank 13:1843 | |
| 6 | impact 13:2198 | institution 13:2648 | traditional 11:2254 | apply 11:2052 | |
| 7 | propose 13:1711 | business 13:2615 | discuss 10:2133 | aim 10:1111 | |
| 8 | system 12:1826 | information 12:2653 | area 09:1646 | banking 10:1032 | |
| 9 | customer 11:2437 | risk 11:1636 | | | |
| 10 | identify 11:1435 | process 10:2113 | | | |
| 11 | digital 10:1855 | change 10:2050 | | | |
| 12 | finding 10:1362 | “ 09:1743 | | | |
| 13 | investment 09:2077 | ” 09:1743 | | | |
| 14 | | focus 09:1631 | | | |
| 15 | | potential 09:1570 | | | |