Penggabungan Pemfilteran Kolaboratif dan Berbasis Konten dengan Konsep Grafik

Zen Munawar, Novianti Indah Putri, Yudi Herdiana

Abstract

Penelitian ini dilakukan untuk menggabungkan pendekatan pemfilteran kolaboratif dan pemfilteran berbasis konten untuk membuat rekomendasi dalam sistem pemberi rekomendasi untuk meningkatkan akurasi rekomendasi. Dimana dua pendekatan tersebut untuk membuat rekomendasi. Dalam penelitian ini, digunakan metode berbasis grafik yang memungkinkan penggabungan informasi konten dan informasi peringkat secara alami. Cara yang digunakan yaitu peringkat pengguna lalu mendeskripsikan konten selanjutnya disimpulkan relasi konten dari pengguna, baru setelah itu dilakukan rekomendasi dengan relasi baru, dan dikombinasikan dengan relasi item pengguna. Dari hasil percobaan diperoleh usulan metode mempunyai kemampuan lebih baik

Keywords

Pemfilteran Kolaboratif; Pemfilteran Berbasis Konten; Pemberi Rekomendasi hibrid; Model Berbasis Grafik

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References

Z. Munawar, “Penggunaan Profil Media Sosial Untuk Memprediksi Kepribadian,†Temat. - J. Teknol. Inf. dan Komun., vol. 4, no. 2 SE-Articles, Dec. 2017.

Z. Munawar, “Keamanan Pada E-Commerce Usaha Kecil dan Menengah,†Temat. - J. Teknol. Inf. dan Komun., vol. 5, no. 1 SE-Articles, Jun. 2018.

Z. Munawar, B. Siswoyo, and N. S. Herman, “Machine learning approach for analysis of social media,†ADRI Int. Journal. Information. Technol., vol. 1, pp. 5–8, 2017.

P. Resnick and H. R. Varian, “Recommender Systems,†Commun. ACM, vol. 40, no. 3, pp. 56–58, 1997.

U. Shardanand and P. Maes, “Social information filltering: Algorithms for automating word of mouth,†1995, pp. 210–217.

M. Balabanovic and Y. Shoham, “Fab:Content-Based, Collaborative Filtering for Recommendation,†in Communications of the ACM, 1997, vol. 40, no. 3, pp. 66–72.

R. J. Mooney and L. Roy, “Content-based book recommending using learning for text categorization,†in Proceedings of the ACM International Conference on Digital Libraries, 2000, pp. 195–204.

A. Adomavicius, G., Tuzhilin, “Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions,†in IEEE Transactions on Knowledge and Data Engineering, 2005, vol. 17, no. 6, pp. 734–749.

R. Komalasari, “Manfaat Teknologi Informasi dan Komunikasi di Masa Pandemi Covid 19,†Temat. Teknol. Inf. Dan Komun., vol. 7, no. 1, pp. 38–50, 2020.

M. Claypool, A. Gokhale, T. Miranda, P. Murnikov, D. Netes, and M. Sartin, “Combining content-based and collaborative filters in an online newspaper,†in Proceedings of the ACM SIGIR ’99 Workshop on Recommender Systems: Algorithms and Evaluation, 1999, p. .

N. I. Munawar, Zen and Putri, “Keamanan Jaringan Komputer Pada Era Big Data,†J-SIKA| J. Sist. Inf. Karya Anak Bangsa, vol. 02, no. 01, pp. 14–20, 2020.

N. I. Putri, “Sistem pakar diagnosa tingkat kecanduan gadget pada remaja menggunakan metode Certainty Factor.†UIN Sunan Gunung Djati Bandung, 2018.

M. J. Pazzani, “Framework for collaborative, content-based and demographic filtering,†Artif. Intell. Rev., vol. 13, no. 5, pp. 393–408, 1999.

P. Melville, R. J. Mooney, and R. Nagarajan, “Content-boosted collaborative filtering for improved recommendations,†in Proceedings of the National Conference on Artificial Intelligence, 2002, no. July, pp. 187–192.

C. Basu, H. Hirsh, and W. Cohen, “Recommendation as classification: Using social and content-based information in recommendation,†in Proceedings of the National Conference on Artificial Intelligence, 1998, pp. 714–720.

A. Popescul, L. Ungar, D. Pennock, and S. Lawrence, “Probabilistic Models for Unified Collaborative and Content-Based Recommendation in Sparse-Data Environments,†in Departmental Papers (CIS), 2001, vol. 2001, no. August, pp. 437–444.

J. Basilico and T. Hofmann, “Unifying collaborative and content-based filtering,†in Proceedings, Twenty-First International Conference on Machine Learning, ICML 2004, 2004, pp. 65–72.

K. Crammer and Y. Singer, “Pranking with ranking,†in Advances in Neural Information Processing Systems, 2002, pp. 641–647.

C. C. Aggarwal, J. L. Wolf, K.-L. Wu, and P. S. Yu, “Horting hatches an egg: A New Graph-Theoretich Approach to Collaborative Filtering,†in Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining - KDD ’99, 1999, pp. 201–212.

Z. Huang, W. Chung, T.-H. Ong, and H. Chen, “A graph-based recommender system for digital library,†in The Second ACM/IEEE-CS Joint Conference on Digital Libraries - JCDL ’02, 2002, p. 65.

Z. Huang, H. Chen, and D. Zeng, “Applying associative retrieval techniques to alleviate the sparsity problem in collaborative filtering,†ACM Trans. Inf. Syst., vol. 22, no. 1, pp. 116–142, 2004.

Z. Munawar, N. Suryana, Z. B. Sa’aya, and Y. Herdiana, “Framework With An Approach To The User As An Evaluation For The Recommender Systems,†in 2020 Fifth International Conference on Informatics and Computing (ICIC), 2020, pp. 1–5.

J. Weston, A. Elisseeff, D. Zhou, C. S. Leslie, and W. S. Noble, “Protein ranking: From local to global structure in the protein similarity network,†in Proceedings of the National Academy of Sciences of the United States of America, 2004, vol. 101, no. 17, pp. 6559–6563.

J. Herlocker, Jonathan L. ; Konstan, Joseph A.; Borchers, Al ; Riedl, “Evaluating Collaborative filtering recommender systems,†ACM Trans. Inf. Syst., vol. 22, no. 1, pp. 5–53, 2004.

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