User Profiling Based on Keyword Clusters for Improved Recommendations-Reference-Cited by-同舟云学术

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User Profiling Based on Keyword Clusters for Improved Recommendations

Published:2014 Issue: Volume: Page:176-187
ISSN:0302-9743
Container-title:Distributed Computing and Internet Technology
language:
Short-container-title:

Author:

Anand Deepa,Mampilli Bonson Sebastian

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-04483-5_19

Reference11 articles.

1. Lecture Notes in Computer Science;M.J. Pazzani,2007

2. Anand, D.: Group movie recommendations via content based feature preferences. International Journal of Scientific & Engineering Research 4, 1–5 (2013)

3. Al-Shamri, M.Y.H., Bharadwaj, K.K.: Fuzzy-genetic approach to recommender systems based on a novel hybrid user model. Expert Systems with Applications 35, 1386–1399 (2008)

4. Liang, H., Xu, Y., Li, Y., Nayak, R., Shaw, G.: A hybrid recommender systems based on weighted tags. In: 10th SIAM International Conference on Data Mining, SDM 2010 (2010)

5. Nagar, S.: A hybrid recommender: user profiling from tags/keywords and ratings. PhD thesis, Kansas State University (2012)

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1. Classification and Clustering of Emotive Microblogs in Albanian: Two User-Oriented Tasks;Complex Pattern Mining;2020

2. A Deep Learning Framework to Predict Rating for Cold Start Item Using Item Metadata;2019 IEEE 28th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE);2019-06

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