- Shiv Malik: 11.6K followers on Twitter.
- Owen Bowcott: 1,311 followers on Twitter.
- Laurence Topham: 2,119 followers on Twitter.
- Carlo Festa: 481 followers on Twitter.
- Daniele Bellasio: 13.9k followers on Twitter.
- Gabriele Caramellino: no twitter profile found.
To whom interested in coding I did the graph above with:
Write a function DashInsert(num) insert dashes ('-') between each two odd numbers and insert asterisks ('*') between each two even numbers in num. For example: if num is 4546793 the output should be 454*67-9-3. Don't count zero as a negative or positive number.
how to debug a #bash script: insert into it set -x trap read debug— Walter Traspadini (@uollter) February 10, 2014
This is a very simple example which illustrates how it works one of the most used technique to determine which document is most relevant in respect of a given topic defined as a query term.
Now suppose you have 3 documents and you want to find out which one is more relevant in discussing the topic "Open Source".
In production and development, open source as a development model promotes a) universal access via free license to a product's design or blueprint, and b) universal redistribution of that design or blueprint, including subsequent improvements to it by anyone.
Open source software is software that can be freely used, changed, and shared (in modified or unmodified form) by anyone. Open source software is made by many people, and distributed under licenses that comply with the Open Source Definition.
Leaders of the nation’s biggest technology firms warned President Obama during a lengthy meeting at the White House on Tuesday that National Security Agency spying programs are damaging their reputations and could harm the broader economy.
You can already see by yourself the third document is less relevant than the others.
Below The Full code:
from tfidf import tf, idf, tf_idf
The most relevant document
Overall TF-IDF scores for query 'Open Source'
As you can see the most relevant document is the second with the highest term frequency inverse document frequency. The third document is completely irrelevant with no tf-idf