Mood-Based Recommender: Music And Book Recommendations

Registration ID: IJNRD_218740

Published ID: IJNRD2405079

DOI: Click Here to Get

Nandhana A R , Musharaf K K , Meenakshy N S , Neeraja Krishnakumar , Sivadasan E T

recommendation systems, mood analysis, logistic regression, personalized experience, API (Appli- cation Programming Interface), Spotify, Google books, collaborative filtering.

This paper presents a comprehensive system which recommends both songs and books according to the user’s current mood. It can overcome the limitations of existing recommendation systems, which commonly overlook key factors like personal preferences and user’s mood in both books and songs. Different from conventional genre-centric techniques, our system effortlessly includes analysis of mood via logistic regression giving a tailored experience. Utilizing the Spotify API along with Google Books API, the system is able to recommend tracks along with publications aligned to the user’s current mood. The system also allows the listeners to explore as well as going through the same songs as one wants to, which gives the user much of a freedom to create their own playlists. In addition to this, aesthetically attractive publication referrals can also boost the general user experience. This innovation in recommendation systems not just links the books and songs but also helps the users to recognize what they need with a choice of exploration. Compared to the prevailing systems, the advantage is that both books and songs are recommended in a single system which is efficient enough to act according to user’s preferences as it caters the capabilities of two most strong and efficient API’s.

Published Paper   E-Certificate

Nandhana A R, Musharaf K K, Meenakshy N S, Neeraja Krishnakumar, & Sivadasan E T (May-2024). Mood-Based Recommender: Music And Book Recommendations. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(5), a737-a743. https://ijnrd.org/papers/IJNRD2405079.pdf

Volume 9 Issue 5, May-2024

Pages : a737-a743

Paper Reg. ID: IJNRD_218740

Published Paper Id: IJNRD2405079

Downloads: 000121983

Research Area: Science & Technology

Country: Thrissur, Kerala, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2405079.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2405079

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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