Tribhuvan University

Faculty of Humanities and Social Sciences

Orchid International College

COLLEGE RECOMMENDATION SYSTEM

A PROJECT REPORT

Submitted to
Department of Computer Application
Orchid International College

In partial fulfillment of the requirements for the Bachelors in Computer Application.

Submitted by

Suman Rai (9391130)

June, 2022

Under the supervision of

Er. Dhiraj Kumar Jha
 Tribhuvan University
Faculty of Humanities and Social Sciences
Orchid International College
Bijaychowk, Kathmandu

SUPERVISOR’S RECOMMENDATION

I hereby recommend that this project prepared under my supervision by Suman Rai
entitled “COLLEGE RECOMMENDATION SYSTEM” in partial fulfillment of
the requirements for the degree of Bachelor of Computer Application is recommended for
the final evaluation.

………………

SIGNATURE

Er. Dhiraj Kumar Jha

SUPERVISOR

Project Co-ordinater
Department of IT
Orchid International College
Bijayachowk, Gaushala

i
 Tribhuvan University
Faculty of Humanities and Social Sciences
Orchid International College
Bijaychowk, Kathmandu

LETTER OF APPROVAL

This is to certify that this project prepared by Suman Rai entitled “COLLEGE
RECOMMENDATION SYSTEM” in partial fulfillment of the requirements for the
degree of Bachelor in Computer Application has been evaluated. In our opinion it is
satisfactory in the scope and quality as a project for the required degree. 

SIGNATURE of Supervisor  SIGNATURE of HOD/ Coordinator 

…………………………………
………………………….
Er. Dhiraj Kumar Jha Mr. Bidur Dahal

Project Co-ordinater Head of Department

Department of IT Orchid International College

Orchid International College Bijaychowk, Gausala
Bijaychowk, Gausala

SIGNATURE of Internal SIGNATURE of External

Examiner Examiner

………………………. ………………………………..
Ms. Shikha Sharma
Lecturer,
Orchid International College
Bijaychowk, Gausala

ii
 ABSTRACT
College Recommendation System Project is a web-based application in python, developed
mainly for recommendation of college for those students who don’t know the proper
knowledge of college in a particular area. Most of the students confused of choosing their
interested college and faculty. They have to make decision within a 2 month of time and they
don’t have proper guidance for searching quality college and high scope faculty. In order to
solve student’s problems, this project College Recommendation System will guide to collect
best college in the particular area.

In this project, we have developed a recommender system that take some information from
the user, survey and review from old students and generates recommendations in sorted
order. Which provides information to the students and advisors to improve the choice of
college and course. This project help to those students who want good college and faculty
according to the old student’s details. Students who passed out SEE, they don’t worry about
the choosing college. In our methodology we use collaborative filtering algorithm to
improves our recommendation. Recommending college based on old students’ data,
processing of these data, thus if the information is properly listed then the task of
recommending would get a lot easier. The difficult task for this project is to collect all the old
student’s data from their respective college who passed out SEE. Also, when results are
shown to the user, big challenge is how well data can be ranked so that user satisfaction is
guaranteed.

In this system, students can easily log in to the system and get sufficient knowledge about
college and faculty as per their interest. It is web-based system developed using Django
framework of python. This system make ease for every system who have passed SEE
examination.

Keywords: College Recommendation System, Unified Modeling Language, SEE, Web-

Based college Recommender

iii
 ACKNOWLEGDEMENT

We are very thankful to our project supervisor Er. Dhiraj Kumar Jha who had provided a
precious time for our project. In this time, we learned lot of things related to project and
made us proper guidance to complete our project. Also, I would like to thanks all of my
friend to be a part of my project by providing lot of support and guidance.
The aim of this project is to make familiar to the practical aspect and uses of theoretical
knowledge and clarifying the use of College Recommendation system and gives effective
way of recommending the college using the old school’s name. So, we have successfully
completed the project and compiled this report as the summary and the conclusion that we
have drawn from the project. During this project, we have gained a valuable experience and
knowledge.

iv
 TABLE OF CONTENTS
SUPERVISOR’S RECOMMENDATION…………………………………………………….i
LETTER OF
APPROVAL…………………………………………………………………….ii
ABSTRACT………………………………………………………….…………..…………..iii
ACKNOWLEDGEMENT……………………………………………………..…….……….iv
TABLE OF CONTENTS………………………………………………………….…………..v
LIST OF FIGURES……………………………………………………………..……………
vii
LIST OF TABLES………………………………………………………………….
……….viii
LIST OF ABBREVIATIONS………...………………………………………….…..……….ix
Chapter 1: Introduction……………………………………….
……………………………..1
1.1 Introduction………………………………………………………….…………….…..1
1.2 Problem statement……………………………………………………….………….....1
1.3 Objectives…………………………………………………………………….…….…2
1.4 Scope and limitation………………………………………………………….….….…
2
1.5 Report Organization………………………………………………..………..….……..3
Chapter 2: Background study and Literature
Review……………………………………..4
2.1 Background study…………………………………………..………….…………...
….4
2.2 Literature Review…………………………………………………………………..….4
Chapter 3: System Analysis and Design………………………………………………….…
5
3.1 System Analysis……………………………………………………………………….5
3.1.1 Requirement Analysis…………………………………………………………………5
3.1.2 Feasibility Analysis……………………………………………………………………9

v
3.1.3 Object Modeling…….……………………………………………….…………….…
10
3.1.4 Dynamic Modeling….…….………………………………………….
………............11
3.1.4 Process Modeling….…….………………………………………….………..............12
3.2 System
Design………………………………………………………………………..12
3.2.1 Refinement of class…………………………………………………….………….....13
3.3 Algorithm Details…………………………………………………………………….14
Chapter 4: Implementing and Testing…………………………………………………….15
4.1 Implementation………………………………………………………………………15
4.1.1 Tools used……………………………………………………………………………15
4.2 Testing………………………………………………………………………………..16
4.2.1 Test Cases for Unit Testing……………………………………………………….….16
4.2.2 Test Cases for System Testing………….………………………………………….…
20
Chapter 5: Conclusion and Future Recommendations…………………………………..22
5.1 Conclusion……………………………………………………………….……….….22
5.1 Outcome……………………………………………………………….......................22
5.3 Future Recommendations ………………………………………………………..
…..22
REFERENCES………………...…………………………..…………………………….….23

vi
 LIST OF FIGURES

Figure 3.1: Use-Case Diagram of CR…………………………….……......………………….5

Figure 3.2: Gantt Chart……………………………….………………………..……….……..9
Figure 3.3 Conceptual class diagram of CR ………..…………………...…………..………10
Figure 3.4: State Diagram……….……………………………………………...……………11
Figure 3.5: Activity Diagram….………………………………....……..………….………...12
Figure 3.6: Refinement of class diagram. ..………………………………………….………13
Figure 3.7: Sentimental Analysis…...……...………………………………………...……14

vii
 LIST OF TABLES

Table 3.1: UC-Description for login ………………………………………………………….6

Table 3.2: UC-Description for choose recommendation…..………………………….………7

Table 3.3: UC-Description for select exam form………………..……….……………..…….7

Table 4.0: Details of modules…………..……………………………….……………..…….15

Table 4.1 Test-case for login………………………………………………………………...17

Table 4.2 Test-Case for bid product…………………………………………………………18

Table 4.3 Test-Case for payment…….………………………………………………………19

Table 4.4 System testing for AS.…….………………………………………………………20

viii
 LIST OF ABBREVIATIONS

CSS Cascading Style Sheet

DB Database

AS Auction System

HTML Hypertext Markup Language

JS JavaScript

UC Use Case

PYC Pycharm

VS Code Visual Studio Code

UML Unified Modeling Language

ix
 Chapter 1: Introduction

1.1 Introduction

Recommending on the basic of some information, past data, review, rating etc. with some
machine learning algorithm, that process of system we called as Recommendation System.
College Recommendation System guide the students to choose best college according to past
data and review of old students. Many students get confused to select which college is best near
his/her location. They do not have proper information of college. Also, they do not have time as
well to choose the best college with in a two month of time after SEE. This time might be the
toughest time ever to make decision. Some of them study bridge course to get help from mentor
to choose college and faculty.
The goal of this project is to study recommendation engines and identify the shortcomings of
tradition recommendation engine and to develop a web-based recommendation engine by
making the use of user based supervised learning and sentimental analysis. This system
recommends students by taking one of the input college name available in the system. Old
students record of that particular school are inside the database. And review of old students who
studied the college compare with that past data of particular school’s students who choose
college and carry out college name in the rank order.
Recommendation System are software or tools which provides recommendations of college to
the students in which they might be selected. This system represents important powerful method
enabling students to filter out large information and find out on the basic of their choice.
Various types of Recommendation techniques include:
• Supervised learning
• Sentimental Analysis
• Native Byes
• Decision tree
This project “College Recommendation System” the challenging task is to collect the database of
all colleges. Generating the list of colleges from all the colleges requires to eliminate those
colleges in which the candidate is not eligible

1
1.2 Problem Statement
We all have seen the social media like face book pages, Instagram pages, messages, huge
number of students asking what do after SEE, which faculty is best for career development,
which faculty cost reasonable, which college is best for higher education, which one is amongst
top 10 college in some certain area. Also, there is more instructions for career path way for
students after SEE. It was a hard decision for all those passed out SEE. Different course like
bridge course related to science, management and humanities are available for students for their
better decision after SEE. And we can find 75 % can join faculty according to bridge course and
remaining 25% will leave because of their interest and budget. Most of the students join bridge
course not because of their interest, because of their friend’s decision. This makes students
realize after 1 month of joining. To encounter this, we have College Recommendation system.
Using this system, students can choose college as well as faculty according to budget, their
capabilities, interest not according to friends’ opinion, parents’ opinion because this site make
students clear of which faculty make me what.

1.3 Objectives
Goal is a broad statement that defines what you plan to do in project. The main goal of this
Project is to guide students to choose best college using machine learning algorithm and Django
python framework.

Objectives detailed statements describing the ways through which you intend to achieve the goal.
The objectives are mentioned below:

• To create the straight vision of students after SEE according to their school past information
and rating.

• To get the better way of finding top 10 college.

• To reduce the effort of finding best rated college.

• To make the student confident to choose faculty and college based on system recommendation,
budget etc.

• To provide rank of college using some recommendation tools

2
1.4 Scope and Limitation
The main scope and deliverables of the project would be:
• Understand and prepare detailed requirement and specifications.
• Recommendation of college by clicking their old college name.
• Prepare high level and detailed design specification of the system.
• Prepare Test plan and Test case.
• Develop the system and coding.
• Perform unit testing, integration testing and system testing.
• Demonstrate a bug free application after suitable modification if needed.

There is various limitation of using College Recommendation System

• These types of system are very rare in the context of Nepal and difficult to use for the
first time.
• Without internet nothing is accessible.

1.5 Development Methodology

The development methodology selected for this system is the agile development model because
with agile software development, we can quickly adapt to requirements changes without
negatively impacting release dates. Not only that, Agile helps reduce technical debt, improve
students’ satisfaction and provide good decision for developer.
Here are some of the reasons why we choose agile development model:
 Easily and Quickly Adapt to Change
 Higher Quality Product
 Greater Customer Satisfaction
 Better Project Control
 Reduced risk

3
1.6 Report Organization

Chapter 1: Introduction

This section demonstrates the introduction, objective, scope and limitation of our system.

Chapter 2: Background Study & Literature Review

This section provides the knowledge of background study and literature review of the entire
system and limitations of previous others system.

Chapter 3: System analysis and design

This section provides system analysis and design with functional and non-functional requirement
of the system. Also, it provides the Domain object model, class diagram of the system.

Chapter 3: Implementing and Testing

This section provides the implementing tool and technique with proper testing like test cases.

Chapter 4: Conclusion and Future Recommendations.

This section provides the expected result and conclusion of the existing system.

4
 Chapter 2: Background Study and Literature Review

2.1. Background Study

We in this project aim to reduce all this manual working by making a system which will generate
a list of colleges in which candidate is eligible and also provide him functionality of inter-college
comparison. All the students after SEE get confused for their further studies. Most of the
students select their college, faculty by choosing their parents, decisions of friends, trending
topic available in social media etc. They don’t know what will be the outcomes after finishing
this faculty. Also, they don’t have idea what to do after graduation. Some of them left it out
because that was not their interest. They even don’t know, what to do after graduation. Like man
without goal. They don’t know where to reach. That was the main problem of students
nowadays. And some of them study for degree not for knowledge. And if they have no interest
on, they don’t get knowledge from there. To get what they need and what they interest is all
because of proper guidance in proper time. And this type of guidance is provided by college
recommendation System.

2.2. Literature Review

"College Recommendation System" by "Leena Deshpande, Nilesh Dakala, Himanshu
Shrivastava ", in this paper they had proposed different data analysis and data mining techniques
that can be used for college recommendation system. This system is made for students, parents
and educationalist who aims to search engineering colleges. Recommendation systems solve the
problem of information overload by searching through large volumes of data. There are different
prediction techniques that help recommendation systems to obtain data. It includes data mining
and machine learning techniques for presenting the required information and filtering data.

In "WEKA Approach for Comparative Study of Classification Algorithm by Trilok Chand

Sharma, Manoj Jain this paper compares Naive Bayes and J48 algorithm. Naive Bayes uses
probability and J48 algorithm uses decision tree. Accuracy is checked using WEKA tool. The
experiment results described in this paper are about classification accuracy and cost analysis. In
this paper the results on dataset also show that the efficiency and accuracy of J48 and Naive
Bayesian is good.

5
Chapter 3: System Analysis and Design

3.1 System Analysis

It is a method of gathering and evaluating data, finding problems, and breaking down a system
into its constituent parts. It's a problem-solving method that enhances the system and ensures
that all of its components work together to achieve their goals.

3.1.1 Requirement Analysis

Requirements analysis is the method of evaluating the auction system requirements and
standards. It necessitates constant communication in order to clarify expectations, manage issues,
and document all critical criteria.

i. Functional requirement

Figure 3.1: Use-Case Diagram of College Recommendation System

6
A use case is a list of actions or event steps typically defining the interactions between actors and
the system. In our system there are mainly three actors and they are admin, buyer and seller who
interact with the system. Admin create/update a new post or category into the system and system
gives response if the action is implemented or not. Likewise, buyer can a new account by filling
up the registration form in our system and bid for the product. Also, a seller can sell his product
by adding the product and its description into the system.

Use-case Identifier UC5: Login into the system

Primary Actor Students, Admin

Secondary Actor None

The admin, students can login into the system

Description through a login form for security and
authentication.

The actor have to know the required username

Pre-condition
and password.

The actors can perform required action in the

Post-condition
system.

Success Scenario Login success message should be displayed.

Failure Scenario Login failed message should be displayed.

Table 3.1: UC-Description for login

7
 Table 3.2: UC-Description for choose Recommendation

Use-case Identifier UC1: choose recommendation

Primary Actor Students
Secondary Actor None
The students can select the two options for the
students who recently passed out SEE and +2.
Description For this SEE students can get the college with
positive and negative review for
recommendation.
The students can get the review if and only they
Pre-condition provide their correct past school with correct
location after logged in.
The database must be updated old students
Post-condition
provide review or any actions is performed.
College name and the sentiments of old students
Success Scenario
review is displayed.
Failure Scenario The database is not connected or misconfigured.

Use-case Identifier UC2: select exam form

Primary Actor Students
Secondary Actor None
If the students who passed out +2, that students
give us some review that make recommendation
Description for new students. For getting more data we use
exam form for bachelor that create some discount
with in limited time.
Pre-condition The
The students need to give review first after get
Post-condition
logged in to find out the admission form.

8
 Success Scenario The students successfully submit the form.
Failure Scenario Review error.
Table 3.3: UC-Description for select exam form

These are some functional requirement of our system “College Recommendation System”.

 Login/signup

System shall provide login and signup form for all users.

 View College

The system shall provide college details with review, rating and others necessary information.

 Choose Recommendation
The system shall provide old school name and location to get the review sentiments of old
students.
 Select admission form
The system shall admission form that helps to collect review data from old students.
 Logout
The system shall provide logout button for the students.

ii. Non-functional requirement:

These are some non-functional requirement of our system “College Recommendation System”:
 Performance Requirement:

i. Performance of the system shall be fast and accurate

ii. The system shall be able to handle large amount of data.

 Security:

i. The system shall be able to check validation and authentication of the users.

ii. The system shall be secure and proper accountability includes not allowing user to see other
users accounts.

9
iii. The system shall be able to save password as hash code in database.

 Usability requirement:

i. The system shall allow a user to access the system from the Internet.

ii. The system shall be able to run any web browser as an interface.

 Availability Requirement:
i. The system shall be available 100% for the users and is used 24hrs a day and 365 days a
year.
ii. The system shall be operational 24hrs a day and 7 days a week.

3.1.2 Feasibility Analysis

The feasibility study is concerned with how your project is feasible with respect to time and cost.
This system is not huge like Amazon, so implementation and maintenance are easy also all the
software used to develop is open source.

i. Technical Feasibility

This system can be implemented in various platform and various platform have different version,
that will help to operate in future.

1.Hardware Requirement
Processor: 700MHz Intel Pentium III or equivalent or new.
Disk space: 80mb or more
RAM: 4GB or more
2.Software Requirement
Operating system: Windows (7 or more)
Web Browser: IE 10 or above, Mozilla FF or google chrome
Jupyter notebook with install numpy and pandas
Django framework with python install.

ii. Operational Feasibility

10
Operational feasibility means how the system works effectively and efficiently in order to create
greater performance.

1. The project is easier to operate.

2. The system works better of collecting review data and old history of students
choose college with in single click.
3. It is easy to operate.
4. This system recommends students accurately with high number of data available
database.
iii. Schedule Feasibility

Figure 3.2: Gantt Chart

3.1.3 Object Modeling

An object model is a visual representation of a system’s objects, actions, and associated
attributes. An object model can be used, in conjunction with a design system, to create a
consistent experience across a system’s higher-level constructs.

11
 Figure 3.3: Conceptual Class Diagram of College Recommendation System
3.1.4 Dynamic Modelling
Dynamic Modelling describes those aspect of the system that are concerned with time and
sequencing of the operations. It is used to specify and implement the control aspect of the
system. Dynamic model is represented graphically with the help of state diagrams. It is also
known as state modelling.

i. State Diagram

A state diagram is used to represent the condition of the system or part of the system at finite
instances of time. It’s a behavioral diagram and it represents the behavior using finite state
transitions.

12
 Figure 3.4: State Diagram

3.1.5 Process Modeling:

The visual representation of the procedures, or activities, that gather, alter, save, and share data
among a system and its surroundings and components appears to be process modeling. The
activity diagram, which is used to represent the system's dynamic features, is another crucial
behavioral diagram in the UML diagram. It explains how the many layers of abstraction of the
college recommendation system's activities are grouped to provide a service. Additionally, it is
utilized to simulate how actors interact together to represent business activities in auction
systems.

13
Figure 3.5: Activity Diagram

14
3.2 System Design
3.2.1 Refinement of Classes and Objects

Figure 3.6: Refinement of class diagram

15
3.3 Algorithm Details
Sentiments analysis

Sentiment analysis is a technique through which you can analyze a piece of text to determine the
sentiment behind it. It combines machine learning and natural language processing (NLP) to
achieve this. Using basic Sentiment analysis, a program can understand whether the sentiment
behind a piece of text is positive, negative, or neutral.

It is a powerful technique in Artificial intelligence that has important business applications.

For example, you can use sentiment analysis to analyze customer feedback. After collecting that
feedback through various mediums like Twitter and Facebook, you can run sentiment analysis
algorithms on those text snippets to understand your customers' attitude towards your product.

There are many types of approach for identifying whether the text is negative positive and
neutral.

Ruled Based Approach

Here, rule-based tokenization, parsing, and the lexicon technique are used. The strategy counts
how many positive and negative terms are present in the sample. If there are more positive words
than negative words, the emotion is positive; otherwise, it is the opposite.

Figure 3.7: Ruled Based Approach in sentimental analysis

16
 Chapter 4: Implementation and Testing
4.1 Implementation
Physical system specifications are transformed into a functional and dependable solution at this
level. The system is developed in this location. The job is divided into modules or units and
actual coding is started as soon as the system design documents are received. Testing comes after
it. During this stage of the software development process, several tools are employed.

Tools Used:
● Python: High-level, general-purpose programming language designed for web development.
● VS Code: Source-code editor made for debugging, syntax highlighting and code refactoring.
● SQLite: Open-source, stand-alone, transaction relational database engine designed to be
embedded into an application.
● Draw.io: Diagram Making Tool
● Front-end: HTML, CSS, JavaScript
● Backend: Python with Django

4.1.2. Implementation Details of Modules

Table 4.0: Details of module

Code Module Name Class Name Function Name

M1 login Login signin()
M2 register Register signUp()
M3 AddCollege AddColleges AddCollege()
M4 models_profile Models_Profile ModelsProfile()
M5 ChangePassword Register changePassword()
M6 collegeReview Review CollegeReview()
M6 recommend_view Recommend Recommend()
M7 Logout User Signout()

17
4.2 Testing
In general, testing is finding out how Ill something works. In terms of human beings, testing tells
what level of knowledge or skill has been acquired. Testing is the process of evaluating the
capability of the system that checks if the system meets its requirements. After the website was
developed, it was tested using unit testing and system testing.

4.2.1 Test Cases for Unit testing

Unit testing is a software development process in which the smallest testable parts of an
application, called units, are individually and independently scrutinized for proper operation.
This testing methodology is done during the development process by the software developers
and sometimes QA staff.
In this process for unit testing 3 major testing are done here and they are:
 Login testing
 Recommend testing
 ExamForm testing
After the completion of these testing we can assure that the system individual part are working
fine and also know that there is no any kind of issue with the system.

18
 Table 4.1 Test-Case for login

  Project Name: College Recommendation System

Test Case

Test Case ID: TC_001 Test Designed by: Suman Rai

Test Priority (Low/Medium/High):

Test Designed date: 2022-12-02
Medium

Module Name: Login Test Executed by: Suman Rai

Test Title: verify valid username and valid

Test Execution date: 2022-12-03
password.

  Description: This test is used to check the login functionality of college recommendation
system with correct username and password.

  Pre-conditions:  Login form must be loaded in the system.

Dependencies:
Test Actual Status
Step Test Steps Expected Result Notes
Data Result (Pass/Fail)

Navigate to login Login form is As

1 “click” Pass
form.  opened. expected

Enter valid
Credentials are As
2 username and “click” Pass
entered. expected
password,

Click on submit User successful As

3 “click” Pass
button. login to system. expected

Post-conditions: User information is matched with system database as user successfully

enter into the system.

19
 Table 4.2: Test-Case for Bid Product

Project Name: College Recommendation System

Test Case

Test Case ID: TC_002 Test Designed by: Suman Rai

Test Priority (Low/Medium/High):

Test Designed date: 2022-06-11
Medium

Module Name: Recommendation Test Executed by: Suman Rai

Test Title: Verify recommendation using old
school name and location
Test Execution date: 2022-07-21

Description: Test and verify the recommendation using old school name and location its
message to users.

Pre-conditions input field to enter school name and location must be loaded in the system and
user must be logged in.

Dependencies:
Test Actual Status
Step Test Steps Expected Result Notes
Data Result (Pass/Fail)
User already provide school
User must be
name and location directly As
1 logged in into “click” show the data and sentiments Pass
expected
the system. analysis

User enter old User get the college name and

As
2 school name “click” sentiments output of that Pass
respected oldschool.
expected
and location

Submit button is User successfully get the As

3 clicked. “click” output Pass
expected

Post-conditions: User has shown data successfully.

20
 Table 4.3 Test-Case for payment

  Project Name: College Recommendation System

Test Case

Test Case ID: TC_003 Test Designed by: Suman Rai

Test Priority (Low/Medium/High): Medium Test Designed date: 2022-05-20

Module Name: Admission Form Test Executed by: Suman Rai

Test Title: Check for Exam Form Test Execution date: 2022-06-21

  Description: This test is used to get the admission form for the purpose of collecting data
and review.

  Pre-conditions:  User has to fill the admission form to get the 10% discount.
Dependencies:
Test Actual Status
Step Test Steps Expected Result Notes
Data Result (Pass/Fail)
Exam form Check the user provide
As
1 option is “click” feedback or not, if not user Pass
expected
clicked.  take to the review form.
Review User submit the review from
As
2 form is same username that wont Pass
“submit” expected
filled. used for next time.
Exam form After getting the review, As
3 “Click” Pass
displayed exam form is displayed expected

User successfully submit the

Click on
details from college As
4. Submit “Click” Pass
recommendation provided by expected
button
codopark get 10% discount.

Post-conditions: User has submitted the exam form successfully.

21
4.2.2 Test Case for System testing
It is tested at the final stage as a whole by combining all the product modules after integration
testing. The primary aim of conducting this test is that it must fulfill the user requirement
specification. This testing does not depend on system implementations as well.

Table 4.4: System Testing for auction system

Project Name: College Recommendation System

Test Case
Test Case ID: TC_004 Test Designed by: Suman Rai
Test Priority (Low/Medium/High):
Test Designed date: 2022-06-21
High
Module Name: College Recommender
Test Executed by: Suman Rai
system testing

Test Title: Verify recommendation Test Execution date: 2022-06-21

Description: Test the recommendation functionality of CRS.

Pre-conditions: Students review and details are available in the system.

Test Test Expected

Step Actual Result Status Note
Steps Data Result

Login
Login form is
1 button is “Clicked” As Expected Pass
shown
clicked

View
Students Students details
2 “Clicked” As Excepted Pass
details and is shown
review

Enter old User search old

3 school “Clicked” school location As Expected Pass

name and and name

22
 location matched or not
If user put
the old
User show the
school
details with
4 name and “Clicked” As Expected Pass
sentiments
location
output
same in
database.
Post-conditions:
User get the output sentiments of the college review and display in the list form.

23
 Chapter-5 Conclusion and Future Recommendations

5.1 Conclusion
Hence, in our system, students can easily find out the decision by using this college
Recommendation system. After logged in to the system students can check the Recommend by
providing the old school’s name and location. This makes possible by providing review and
rating from old student’s study in college after his/her SEE. This system used sentiments analysis
algorithm to get the review sentiments of old students and listed the name of college in ranking
order.

5.2 Outcome

It is expected that all the requirement and functionality are satisfied in the system which can be
implemented in a proper way and the proposed system works well. We have mentioned that:

1. User add their details inside the registration form

2. The user can login to the system and select past school provided there.
3. User provide some review about their past school and proceed further.
4. User will see the dashboard with college name in a ranking order with details
location.
5. User can find easy way of making decision after SEE.
6. Expected to get good college near me.
7. Expected to solve the student problems of choosing college.
8. No need to follow friends’ decision.
9. Provide college name according to the past data and review.

5.3 Future Recommendations

For the project's design, implementation, monitoring, assessment, and benefits to advance and
run smoothly in the future, the following corrective steps are advised:
 Secure website
 Decision provider for SEE students.
 Students review sentiments
 Simple design of website

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 Advertisement of website
 Review and rating

REFERENCES
[1]"domain object model", slideshare.net, 2019. [Online]. Available:
https://www.slideshare.net/inam15/domain-object-model. [Accessed: 02- Feb- 2022].
[2]"what is class diagram", visual-paradigm.com, 2022. [Online]. Available: https://www.visual-
paradigm.com/guide/uml-unified-modeling-language/what-is-class-diagram/. [Accessed: 02-
Feb- 2022].
https://www.ijert.org/college recommendationsystem#:~:text=This%20system%20is%20made
%20for,recommendation%20systems%20to%20obtain%20data.
https://www.ijert.org/research/college-recommendation-system-IJERTCONV5IS01169.pdf
https://www.researchgate.net/publication/322006324_A_user-
friendly_college_recommending_system_using_user-
profiling_and_matrix_factorization_technique

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