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@article{179218,
        author = {SWETHA A and SUBHASHREE P and SRI LAKSHMI PRABA M and SANDHIYA S},
        title = {INTEGRATED FREELANCING AND QNA SYSTEM WITH TASK BIDDING AND ANSWER RANKING},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {5732-5736},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=179218},
        abstract = {Identifying inefficiencies in separate freelancing and Q&A platforms is critical for delivering streamlined digital services across various user-driven applications. Traditional methods tend to be slow, fragmented, and prone to inconsistent user outcomes. To overcome these challenges, this project introduces a unified solution that merges a freelance job board with a dynamic question-and-answer module to boost functionality and user engagement. The platform enables users to post technical or development-related tasks, with freelancers bidding to complete them and uploading video proofs of their work. Simultaneously, a ranking model predicts the most relevant responses to user queries by analysing factors such as upvotes, contributor reputation, and content clarity. This integrated system improves response accuracy and reduces the time users spend resolving issues. Furthermore, enhancements such as data filtering and intelligent job-user matching support more accurate task allocation, even in complex use cases. The proposed multi-functional approach demonstrates an accuracy level above 91%, offering a cost-effective, time-saving alternative to conventional methods.},
        keywords = {Freelance integration, Answer prediction, Smart bidding, Video-based tasks, Response optimization},
        month = {May},
        }