KICIMAN.ORG: Keyword Density Checker

Total words: 886 | 2-word phrases: 237 | 3-word phrases: 242 | 4-word phrases: 243

PAGE INFO

Title	Try to keep the title under 60 characters (40 characters) Emre Kıcıman – Personal Homepage
Description	Try to keep the meta description between 50 - 160 characters (0 characters)
Keywords	Meta keywords are not recommended anymore (0 characters)
H1	H1 tag on the page (7 characters) Welcome

#	Keyword	Frequency	Density
1	ai’s implications for	2	0.83%
2	talks news and	2	0.83%
3	news and other	2	0.83%
4	skip to content	1	0.41%
5	common sense and	1	0.41%
6	open new frontiers	1	0.41%
7	new frontiers for	1	0.41%
8	advancing the research	1	0.41%
9	the research practice	1	0.41%
10	research practice and	1	0.41%
11	practice and adoption	1	0.41%
12	and adoption of	1	0.41%
13	adoption of causality	1	0.41%
14	by capturing common sense	1	0.41%
15	and domain knowledge	1	0.41%
16	sense and domain	1	0.41%
17	llms can open	1	0.41%
18	domain knowledge about	1	0.41%
19	knowledge about causal	1	0.41%
20	mechanisms and supporting	1	0.41%
21	and supporting translation	1	0.41%
22	supporting translation between	1	0.41%
23	translation between natural	1	0.41%
24	between natural language	1	0.41%
25	natural language and	1	0.41%
26	formal methods the	1	0.41%
27	methods the dowhy	1	0.41%
28	can open new	1	0.41%
29	details how llms	1	0.41%
30	how llms can	1	0.41%

#	Keyword	Frequency	Density
1	talks news and other	2	0.82%
2	skip to content emre	1	0.41%
3	practice and adoption of	1	0.41%
4	causality details how llms	1	0.41%
5	details how llms can	1	0.41%
6	how llms can open	1	0.41%
7	llms can open new	1	0.41%
8	can open new frontiers	1	0.41%
9	open new frontiers for	1	0.41%
10	advancing the research practice	1	0.41%
11	the research practice and	1	0.41%
12	research practice and adoption	1	0.41%
13	by capturing common sense and	1	0.41%
14	and adoption of causality	1	0.41%
15	frontier for causality details	1	0.41%
16	common sense and domain	1	0.41%
17	sense and domain knowledge	1	0.41%
18	and domain knowledge about	1	0.41%
19	domain knowledge about causal	1	0.41%
20	mechanisms and supporting translation	1	0.41%
21	and supporting translation between	1	0.41%
22	supporting translation between natural	1	0.41%
23	translation between natural language	1	0.41%
24	between natural language and	1	0.41%
25	for causality details how	1	0.41%
26	models opening a new	1	0.41%
27	methods the dowhy library	1	0.41%
28	and enable new kinds	1	0.41%
29	bias and understanding how	1	0.41%
30	and understanding how new	1	0.41%
31	technologies affect our awareness	1	0.41%
32	affect our awareness of	1	0.41%
33	our awareness of the	1	0.41%
34	awareness of the world	1	0.41%
35	of the world and	1	0.41%
36	the world and enable	1	0.41%
37	world and enable new	1	0.41%
38	enable new kinds of	1	0.41%
39	language models opening a	1	0.41%
40	to content emre kıcıman	1	0.41%

#	URL	Whois	Check
1	https://www.microsoft.com/en-us/research/lab/microsoft-research-ai/	Whois	microsoft.com
2	https://arxiv.org/abs/2305.00050	Whois	arxiv.org
3	http://pywhy.org/	Whois	pywhy.org
4	https://scholar.google.com/citations?view_op=view_citation&hl=en&user=QZCU3NkAAAAJ&sortby=pubdate&citation_for_view=QZCU3NkAAAAJ:pcWPcJyQGiUC	Whois	google.com
5	https://www.superdatascience.com/podcast/causal-machine-learning	Whois	superdatascience.com