LIFE2VEC.DK KEYWORD DENSITY CHECKER

Total words: 5232 | 2-word phrases: 1403 | 3-word phrases: 1580 | 4-word phrases: 1616

PAGE INFO

Title Try to keep the title under 60 characters (48 characters)
life2vec - Official Model and Publication Source
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 (8 characters)
LIFE2VEC

ONE WORD PHRASES 633 Words

# Keyword H1 Title Des Volume Position Suggest Frequency Density
1the7612.01%
2to507.90%
3we436.79%
4of345.37%
5and325.06%
6is294.58%
7that284.42%
8in284.42%
9a264.11%
10are253.95%

TWO WORD PHRASES 1403 Words

# Keyword H1 Title Des Volume Position Suggest Frequency Density
1in the100.71%
2the model90.64%
3it is80.57%
4we are60.43%
5of the60.43%
6there are60.43%
7human lives60.43%
8on a60.43%
9on the50.36%
10training data50.36%
11the paper50.36%
12the data50.36%
13sequences we40.29%
14to be40.29%
15test data40.29%
16to predict40.29%
17patterns in40.29%
18with the40.29%
19for example40.29%
20is the40.29%

THREE WORD PHRASES 1580 Words

# Keyword H1 Title Des Volume Position Suggest Frequency Density
1sequences of life30.19%
2the training data30.19%
3there are many30.19%
4human lives in20.13%
5for example the20.13%
6nature computational science20.13%
7that if we20.13%
8the model is20.13%
9and how we20.13%
10the test data20.13%
11don’t know who20.13%
12vast majority of20.13%
13the vast majority20.13%
14test data we20.13%
15that claim to20.13%
16of individuals a20.13%
17predictions are happening20.13%
18the embedding spaces20.13%
19explain what the20.13%
20idea of insurance20.13%
21it’s a good20.13%
22sequences of lifeevents20.13%
23of lifeevents to20.13%
24lifeevents to predict20.13%
25using sequences of20.13%
26based on the20.13%
27patterns in the20.13%
28and sune lehmann20.13%
29we are not20.13%
30very good at20.13%

FOUR WORD PHRASES 1616 Words

# Keyword H1 Title Des Volume Position Suggest Frequency Density
1sequences of lifeevents to20.12%
2of lifeevents to predict20.12%
3using sequences of lifeevents20.12%
4the vast majority of20.12%
5human lives in a20.12%
6life2vec using sequences of10.06%
7that means that we10.06%
8expect … and that10.06%
9to expect … and10.06%
10what to expect …10.06%
11about what to expect10.06%
12more about what to10.06%
13know more about what10.06%
14and so on that10.06%
15on that means that10.06%
16so on that means10.06%
17and that if we10.06%
18companies and so on10.06%
19insurance companies and so10.06%
20to insurance companies and10.06%
21due to insurance companies10.06%
22example due to insurance10.06%
23for example due to10.06%
24… and that if10.06%
25we are very good10.06%
26that if we are10.06%
27many other algorithms the10.06%
28the following order first10.06%
29in the following order10.06%
30come in the following10.06%
31paper come in the10.06%
32the arguments in the10.06%
33algorithms the arguments in10.06%
34other algorithms the arguments10.06%
35with many other algorithms10.06%
36if we are very10.06%
37competition with many other10.06%
38in competition with many10.06%
39is in competition with10.06%
40it is in competition10.06%

EXTERNAL LINKS

# URL Whois Check
1https://www.dst.dk/en Whoisdst.dk