Sentimental Analysis Opinion Mining for Mobile Networks

Abstract:

Sentimental Analysis and Opinion Mining for Mobile Networks is a project mainly focuses on sharing posts in the application more effectively and easily. In this application, users can share their posts whether they may be images any others.

This application provides a special feature i.e.., when one user shares a post in the application, all the registered user can see the post and leave a comment to the post. By this, all users can easily find the comments for their post very easily.

Existing System:

In the existing system, it takes time for users to find the comment for their post. All the details of the comments should be verified to see whether it is positive or negative which takes a lot of time. All the work in the existing system is done manually which requires a lot of time and effort.

Proposed System:

In the proposed system users can easily find the status of the comment for their post by a user. The user can save a lot of time. The user can easily find the status of their comment on the post with in no time and with less effort.

Modules:

User:

The user should fill all the details in the registration form to get login details. The user should enter unique username and password to get a login to the application. The user can view his profile, add images, view his uploaded images and can change the password. The user can see the positive comments and negative comments of the post and also user has an option to see the graph.

Admin:

Admin can get login by entering a valid username and password. Admin can view all the activities of the users and can view all the posts uploaded by users.

Software Requirement:

Operating System – Windows
Application Server – Tomcat.
Front End – HTML, Java, Jsp
Scripts – Java Script.
Server side Script – Java Server Pages.
Database – My SQL
Database Connectivity – JDBC

Conclusion:

Out project “Sentimental Analysis and Opinion Mining for Mobile Networks” provides easy and fast opinion on the comments made on the post uploaded by the user in the application. Our application saves a lot of time and effort for users in searching the status of the post.

Climate Data Online (CDO) Data Mining Project

OVERVIEW

In this section describe the background for your application or analysis. Be detailed enough to provide the Climate Data online or “CDO” provides access to climate data products through a simple, searchable online web mapping service.

DATA

All data we have taken is be openly available (obtained from public/open systems). We have taken a dataset from WWW.DATA.GOV which gives a detailed description about Climate Normals, monthly climate reports, and drought information, analyses of weather and climate events, increasingly comparing recent events to expectations of future climate conditions, information detailing extreme events such as heat waves, droughts, tornadoes, and hurricanes have affected the North America since the dawn of time and climate information generated from examination of the data in the archives includes record temperatures, record precipitation and snowfall, climate extremes statistics.

All data must be openly available (or obtained from public/open systems). You may use an API to obtain data if the API is free and/or the account to access it is free.

Some climate data online APIS are used to obtain this data for users in variety of formats such as CSV, XML, JSON.

Source : WWW.DATA.GOV

RESEARCH QUESTIONS

The climate of the North America varies by location and by time of year. Our Climate Data Online (CDO) Data Mining Project motivation is to bring Climate Normals, monthly climate reports, and drought information are a few of the many datasets and products found under one climate section.

So users can easily get a publicly access to our web service ‘CDO’ and get the data in a variety of formats such as CSV, XML, JSON.

Data Mining For Automated Personality Classification

Experimental Method

We conduct a set of experiments to examine whether automatically trained models can be used to recognize the personality of unseen subjects. Our approach can be summarized in five steps:

  1. Store Data related to personality in database
  2. Collect associated personality characteristics for each participant;
  3. Extract relevant features from the texts;
  4. Display features relevant to his personality traits
  5. Personality and User Behavior

The following sections describe each of these steps in more detail.

  • Store Data related to personality traits in database

The personality characteristics are stored in database. Later, when user enters his personality characteristics his personality is examined in large pre-existing databases and system will detect the personality of the user.

  • Collect associated personality characteristics for each participant;

Each user will enter his personality characteristics than system will detect the personality of the user, based on the previous data stored in database.

  • Extract relevant features from the texts

System will extract relevant features from the text entered by the user. System will compare this text with data stored in database. After comparison, system will specify the personality of the user.

  • Display features relevant to his personality traits

System will examine the personality of the user based on the personality traits mentioned by the user. And will provide user with various features which is relevant to his personality traits.

  • Personality and User Behavior

The relation between personality and user behavior is tested. The hypothesis is that conscientiousness, agreeableness and neuroticism predict unique variance attitudes.

Feasibility Study

Our Proposed system will provide information about the personality of the user. Based on the personality traits provided by the user, System will match the personality traits with the data stored in database. System will automatically classify the user’s personality and will match the pattern with the stored data. System will examine the data stored in database and will match the personality traits of the user with the data in database. Than system will detect the personality of the user. Based on the personality traits of the user, system will provide other features that are relevant to the user’s personality.

  • Economic Feasibility

This system will help advertisement people to market their products based on the personality of the user which in turn provide income to the firm who is using this system. This system can be embedded with social sites, as many users can buy and sell their product using these social networks.

  • Operational Feasibility
  • Technical Feasibility

The back end of this project is SQL server  which stores data related to personality traits and other details which is related to this project. There are basic requirement of hardware to run this application. This system is developed in .Net Framework using C#. This application will be online so this application can be accessed by using any device like (Personal Computers, Laptop and with some hand held devices).

Future Scope

  • There can be module where user will be provided with career guidance which matches his personality.
  • For example: if a user has the ability to speak well and able to convince opposite person. So, this user will be good in marketing field.

Software Requirements:

  • Windows
  • Sql
  • Visual studio 2010

Hardware Components:

  • Processor – Dual Core
  • Hard Disk – 50 GB
  • Memory – 1GB RAM
  • Internet Connection

Application

  • This system can be helpful for firms to identify the personality of the interviewee based on the personality traits of the interviewee.
  • This system is useful for the firms for marketing their products and helps them to target the correct customers.

References:

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