Knowledge Engineering: Rapid Miner

University
Semester
– KNOWLEDGE ENGINEERING –
RAPID MINOR
Student ID
Student Name
Submission Date
1

Table of Contents
Introduction................................................................................................................................4
Part A - Business Case...............................................................................................................4
1. Tweet Data Description...................................................................................................4
2. Knowledge Creation Techniques....................................................................................5
2.1 Classification – Decision Tree.................................................................................5
2.2 Clustering – SOM (Self Organizing Map)...............................................................7
2.3 Association Rule Mining – FP Growth Algorithm................................................11
3. External Source Knowledge Creations.........................................................................16
Part – B Knowledge Creations.................................................................................................18
Conclusion................................................................................................................................19
References................................................................................................................................20
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Introduction
In today’s world of Internet and social media awareness, people feel a sense of
connected to the world and their loved ones by being on social platforms like Facebook,
Twitter, Instagram, WhatsApp etc. By using the Rapid Miner tool, we shall evaluate the
activity of users online on the basis of their tweet data. That will be the intention of this whole
project. As Twitter, Flicker, and Facebook and other social media platforms cover more and
more applications, tools and websites, people have started using these platforms to share their
feelings, experiences, gather information, news and convey their opinions with their family,
friends and peers. We shall focus on of the most popular social media platforms and
information acquiring media used in today’s world, Twitter. It is an online news, information,
and social networking platform. The account holders and the users post “tweets” which is
interactive and can also attach photos, links, services etc. It saves all the activities of the user
as and what he/she posts (tweets) on the platform and it is a real-time social media service. A
“Dynamic Data Streaming” system is what Twitter has become with the daily updates from
all its users and the posts that they keep on “tweeting”.
To understand and procure the in-depth knowledge of the activity of online users who
tweet and regularly use Twitter, a Knowledge Engineer will make use of the creation
technique and the knowledge representation to analyse all these data and information. On the
online pages, Twitter API etc, all these different data sets and the information packets are
available. So our focus for this project will be to acquire an in-depth knowledge and
information of the user’s online activities by using the user’s tweets, Twitter data and
evaluating the same (Challenges with Big Data Analytics, 2015).
Part A - Business Case
1. Tweet Data Description
The Twitter websites and servers collect all the tweet data, information from a user by
his /her tweets. This same data will be used in this project. To understand and acquire in-
depth knowledge of the user’s online activity, we shall evaluate this data that is generated by
the user’s tweets. The below given attributes are part of this data,
 ID
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