Analyzing category correlations for recommendation system

Bernhard Scholz, Sang Min Choi, Sang Ki Ko, Hae Sung Eom, Yo Sub Han

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Since the late 20th century, the Internet users have noticeably increased and these users have provided lots of information on the Web and searched for information from the Web. Now there are huge amount of new information on the Web everyday. However, not all data are reliable and valuable. This implies that it becomes more and more difficult to find a satisfactory result from the Web. We often iterate searching several times to find what we are looking for. Researcher suggests a recommendation system to solve this problem. Instead of searching several times, a recommendation system proposes relevant information. In the Web 2.0 era, a recommendation system often relies on the collaborative filtering from users. In general, the collaborative filtering approach works based on user information such as gender, location or preference. However, it may cause the cold-star problem or the sparsity problem since it requires initial user information. Recently, there are several attempts to tackle these collaborative filtering problems. One of such attempts is to use category correlation of contents. For instance, a movie has genre information given by movie experts and directors. We notice that these category information are more reliable compared with user ratings. Moreover, a newly created content always has category information; namely, we can avoid the cold-start problem. We consider a movie recommendation system. We revisit the previous algorithm using genre correlation and improve the algorithm. We also test the modified algorithm and analyze the results with respect to a characteristic of genre correlations.

Original languageEnglish
Title of host publicationProceedings of the 5th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2011
DOIs
Publication statusPublished - 2011 May 20
Event5th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2011 - Seoul, Korea, Republic of
Duration: 2011 Feb 212011 Feb 23

Publication series

NameProceedings of the 5th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2011

Other

Other5th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2011
CountryKorea, Republic of
CitySeoul
Period11/2/2111/2/23

Fingerprint

Recommender systems
Collaborative filtering
Stars
Internet

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Information Systems

Cite this

Scholz, B., Choi, S. M., Ko, S. K., Eom, H. S., & Han, Y. S. (2011). Analyzing category correlations for recommendation system. In Proceedings of the 5th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2011 [1] (Proceedings of the 5th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2011). https://doi.org/10.1145/1968613.1968615
Scholz, Bernhard ; Choi, Sang Min ; Ko, Sang Ki ; Eom, Hae Sung ; Han, Yo Sub. / Analyzing category correlations for recommendation system. Proceedings of the 5th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2011. 2011. (Proceedings of the 5th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2011).
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Scholz, B, Choi, SM, Ko, SK, Eom, HS & Han, YS 2011, Analyzing category correlations for recommendation system. in Proceedings of the 5th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2011., 1, Proceedings of the 5th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2011, 5th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2011, Seoul, Korea, Republic of, 11/2/21. https://doi.org/10.1145/1968613.1968615

Analyzing category correlations for recommendation system. / Scholz, Bernhard; Choi, Sang Min; Ko, Sang Ki; Eom, Hae Sung; Han, Yo Sub.

Proceedings of the 5th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2011. 2011. 1 (Proceedings of the 5th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2011).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Scholz B, Choi SM, Ko SK, Eom HS, Han YS. Analyzing category correlations for recommendation system. In Proceedings of the 5th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2011. 2011. 1. (Proceedings of the 5th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2011). https://doi.org/10.1145/1968613.1968615