Content-Based News Recommendation
The information overloading is one of the serious problems nowadays. We can see it in various domains including business. Especially news represent area where information overload currently prevents effective information gathering on daily basis. This is more significant in connection to the web and news web-based portals, where the quality of the news portal is commonly measured mainly by the amount of news added to the site. Then the most renowned news portals add hundreds of new articles daily. The classical solution usually used to solve the information overload is a recommendation, especially personalized recommendation. In this paper we present an approach for fast content-based news recommendation based on cosine-similarity search and effective representation of the news. We experimented with proposed method in an environment of largest electronic Slovakia newspaper and present results of the experiments.
Keywordsnews recommendation personalization vector representation user model article similarity
Unable to display preview. Download preview PDF.
- 2.Barla, M., Kompan, M., Suchal, J., Vojtek, P., Zeleník, D., Bieliková, M.: News recommendation. In: Proc. of the 9th Znalosti, VSE Prague, pp. 171–174 (2010)Google Scholar
- 4.Dakka, W., Gravano, L.: Efficient summarization-aware search for online news articles. In: Proc. of the 7th ACM/IEEE-CS Joint Conf. on Digital Libraries, JCDL ’07, pp. 63–72. ACM, New York (2007)Google Scholar
- 7.Kou, H., Gardarin, G.: Keywords Extraction, Document Similarity and Categorization. Tech.rep., PRiSM Laboratory of Versailles Univ., No.2002/22 (2009)Google Scholar
- 9.Melville, P., Mooney, R.J., Nagarajan, R.: Content-boosted collaborative filtering for improved recommendation. In: Proc. of 18th National Conf. on Artificial Intelligence, Edmonton, Alberta, Canada, pp. 187–192. AAAI, Menlo Park (2002)Google Scholar
- 12.Ramos, J.: Using TF-IDF to Determine Word Relevance in Document Queries. Tech. rep., Departament of Computer science. Rutgers University (2000)Google Scholar
- 13.Suchal, J., Návrat, P.: Full text search engine as scalable k-nearest neighbor recommendation system. In: Proc. of the Artificial Intelligence in Theory and Practice 2010. World Computer Congress. Springer, Boston (2010)Google Scholar
- 16.Wu, Y., Chen, Y., Chen, A.L.: Enabling Personalized Recommendation on the Web Based on User Interests and Behaviors. In: Proc. of the 11th Int. Workshop on Research Issues in Data Engineering, RIDE, p. 17. IEEE Computer Society, Washington (2001)Google Scholar
- 17.Yoneya, T., Mamitsuka, H.: Pure: a pubmed article recommendation system based on content-based filtering. Genome informatics. In: International Conference on Genome Informatics, vol. 18, pp. 267–276. Imperial College Press, London (2007)Google Scholar
- 18.Zeleník, D., Bieliková, M.: Dynamics in hierarchical classification of news. In: Proc. of the 4th Work. on Intel. and Knowledge Oriented Technologies. Equilibria, pp. 83–87 (2009)Google Scholar