Knowledge Sharing Based Online Social Network with Question and Answering System

ABSTRACT:

Online Social Networks (OSNs) have revolutionized the way people connect, communicate, and share information. These platforms facilitate interactions among individuals with common interests, fostering communities that exchange ideas, opinions, and knowledge. Traditional social networks primarily focus on user interactions through messaging, media sharing, and content engagement. However, they often lack structured mechanisms for domain-specific knowledge sharing, leading to scattered and unverified information.

The rapid expansion of digital knowledge and expertise across various domains necessitates a structured system for knowledge dissemination. Social networks provide a vast repository of user-generated content, but the absence of an expert-driven question-and-answer system results in unreliable information. A dedicated mechanism where learners can ask domain-specific questions and receive expert-verified answers enhances the credibility and usability of social networking platforms. Such a system ensures that users can gain knowledge efficiently, bridging the gap between curiosity and expertise.

The proposed system integrates social networking features with an expert-driven Q&A system. Unlike conventional social networks, this platform categorizes users into two types: Learners and Experts. Learners can post questions, which are directed exclusively to experts in the relevant domain, ensuring accuracy and reliability in responses. The system is developed using Java as the coding language, JSP, CSS, and JavaScript for the frontend and MySQL for the database.

The “Knowledge Sharing Based Online Social Network with Question and Answering System” provides an innovative approach to combining social networking with structured knowledge sharing. By implementing a domain-specific expert-driven Q&A mechanism, the platform enhances the reliability of information and promotes intellectual growth among users. This system bridges the gap between learners seeking knowledge and experts willing to share their expertise, fostering a productive and educational online environment.

PROJECT OUTPUT VIDEO:

EXISTING SYSTEM:

The existing online platforms provide various means of information exchange, including forums, discussion boards, and web-based Question and Answer (Q&A) websites. These platforms allow users to post questions and receive responses from a general audience. While factual questions may be answered effectively, non-factual or preference-based queries often do not receive suitable responses that align with the asker’s intent.
The existing web-based Q&A websites cannot easily solve non-factual questions to match askers’ preferences. Recent research efforts have introduced social-based Q&A systems that rely on an asker’s social connections to provide answers. However, these systems are limited in their effectiveness as they rely on the interests of the asker’s social circle. If a question does not belong to the asker’s predefined interests, finding a suitable answerer becomes challenging. This gap highlights the need for a more refined knowledge-sharing system where questions are directed to experts based on expertise rather than social connections.
In recent years, social-based Q&A systems have emerged, utilizing social networks to connect askers with potential responders from their social circles. These systems leverage existing social connections to provide answers, fostering interactive and engaging discussions. Users can receive responses from friends or individuals with shared interests, enhancing the relevance of answers in certain cases.
Traditional web-based Q&A websites and social-based Q&A systems play a crucial role in online knowledge sharing. They provide a platform for users to seek and share information while fostering collaborative learning and engagement within online communities.

DISADVANTAGES OF EXISTING SYSTEM:

Despite their advantages, the existing system with traditional Q&A systems and social-based Q&A platforms face several limitations. One of the primary challenges is the lack of domain-specific expertise in responses. Since questions are open to a general audience, responses may come from individuals who do not have sufficient knowledge or expertise, leading to unreliable or inaccurate information.
Another limitation is the difficulty in obtaining responses to non-factual or preference-based questions. Traditional Q&A websites often struggle to match askers’ preferences, making it challenging to receive subjective yet relevant answers. Social-based Q&A systems attempt to address this by relying on an asker’s social connections; however, this method restricts access to experts outside the asker’s network.
Additionally, there is no structured mechanism to ensure that questions reach the most qualified individuals. Many Q&A platforms operate on a first-come, first-serve basis, meaning that responses may not always be from the most knowledgeable contributors. Furthermore, information overload and duplicate responses can reduce the effectiveness of knowledge retrieval on these platforms.
The existing system cannot easily solve non-factual questions, because followers are unaware of their user’s personnel preferences. The non-factual questions here mean the questions without specific correct answers, such as questions about opinion or suggestion.
Due to the anonymous global users, a question may not receive answers or the response delay may be long, and the provided answers may not be trustable (such as spam) or accurate.
Due to these limitations, there is a need for a more structured knowledge-sharing system that effectively connects askers with experts based on domain-specific expertise. Such a system would enhance the reliability and quality of answers while ensuring that users receive responses tailored to their needs.

PROPOSED SYSTEM:

The proposed system is an advanced knowledge-sharing platform integrated within an online social networking environment. It introduces a structured mechanism for connecting learners with domain-specific experts, ensuring that questions are directed to the most qualified individuals. This system allows users to register as either Learners or Experts, enabling a streamlined question-answering process based on expertise.
During registration, users provide personal details, including their name, email, profile description, and interests in categories such as Music, Books, Movies, Television, and Research. If a user selects the Expert role, they must specify their domain of expertise. This classification ensures that only relevant experts receive and respond to questions within their specialized field.
Once logged in, learners can access features such as News Feed, Find Friends, Ask Questions, View Profile, and manage Friend Requests. The system enables learners to ask questions, which are then filtered and directed only to experts in the corresponding domain. Experts, on the other hand, have access to News Feed, where they can view and answer domain-specific questions, interact with other experts, and manage their profiles.
Interest topics are:
- MUSIC: Classical, Techno, Trance, Blues, Hip Hop, Jass, Pop, Rock.
- BOOK: Science Fiction, Drama, Action & Adventure, Romance, Mystery, Comics, Journals, Horror.
- MOVIE: Action, Adventure, Comedy, Crime, Drama, Fantasy, Historical, Horror, Mystery, Philosophical, Romance, Science fiction.
- TELEVISION: Animation, Documentary, Educational, News show, Reality, Game show, Rom-com.
- RESEARCH: Artificial Intelligence (AI), Data Mining, Big data analytics, Cyber security, Bioinformatics, Embedded Systems, Healthcare.
The system is developed using Java as the coding language, JSP, CSS, and JavaScript for the frontend, and MySQL as the database. The backend efficiently manages user roles, question routing, and response handling to ensure seamless interaction between learners and experts. By integrating structured knowledge-sharing functionalities within a social networking framework, the system fosters an environment where users can gain valuable insights from experienced professionals in their respective fields.

ADVANTAGES OF PROPOSED SYSTEM:

Domain-Specific Expertise: The system ensures that questions are directed to experts in the relevant domain, improving the accuracy and reliability of responses.
Efficient Knowledge Sharing: By categorizing users as Learners or Experts, the platform streamlines the question-answering process, making it more structured and effective.
Enhanced User Engagement: The integration with a social networking platform increases user interaction, encouraging active participation from both learners and experts.
Personalized Experience: Users can specify their interests and expertise during registration, ensuring that they receive content and interactions relevant to their knowledge area.
Filtered Question Distribution: Unlike traditional Q&A systems, this platform ensures that only the relevant experts receive and respond to questions, preventing unnecessary clutter.
User-Friendly Interface: The system provides an intuitive interface with features such as NewsFeed, Profile Management, and Question Posting, enhancing the user experience.
Secure and Organized Data Management: Utilizing MySQL as the database ensures efficient data storage and retrieval, maintaining a well-structured knowledge-sharing platform.
Encourages Professional Networking: Experts can view and interact with other experts in their domain, fostering professional connections and collaborations.
Improved Answer Quality: Since only domain-specific experts answer questions, the responses are more accurate, relevant, and insightful compared to general Q&A platforms.
Scalability and Future Expansion: The system is designed to accommodate a growing user base, with potential future enhancements such as AI-based recommendations and automated question categorization.

SYSTEM REQUIREMENTS:

HARDWARE REQUIREMENTS:

System : Pentium i3 Processor.
Hard Disk : 20 GB.
Monitor : 15’’ LED.
Input Devices : Keyboard, Mouse.
Ram : 4 GB.

SOFTWARE REQUIREMENTS:

Operating system : Windows 10/11.
Coding Language : JAVA.
Frontend : JSP, CSS, JavaScript.
JDK Version : JDK 23.0.1.
IDE Tool : Apache Netbeans IDE 24.
Tomcat Server Version : Apache Tomcat 9.0.84
Database : MYSQL.

Java Projects

Knowledge Sharing Based Online Social Network with Question and Answering System