Blanco, Roi and Ceccarelli, Diego and Lucchese, Claudio and Perego, Raffaele and Silvestri, Fabrizio You should read this! let me explain you why: explaining news recommendations to users. In: CIKM '12 Proceedings of the 21st ACM international conference on Information and knowledge management. ACM, New York, pp. 1995-1999. ISBN 978-1-4503-1156-4 (2012)Full text not available from this repository.
Recommender systems have become ubiquitous in contentbased web applications, from news to shopping sites. Nonetheless, an aspect that has been largely overlooked so far in the recommender system literature is that of automatically building explanations for a particular recommendation. This paper focuses on the news domain, and proposes to enhance effectiveness of news recommender systems by adding, to each recommendation, an explanatory statement to help the user to better understand if, and why, the item can be her interest. We consider the news recommender system as a black-box, and generate different types of explanations employing pieces of information associated with the news. In particular, we engineer text-based, entity-based, and usagebased explanations, and make use of a Markov Logic Networks to rank the explanations on the basis of their effectiveness. The assessment of the model is conducted via a user study on a dataset of news read consecutively by actual users. Experiments show that news recommender systems can greatly benefit from our explanation module.
|Item Type:||Book Section|
|Additional Information:||CIKM ’12: 21st ACM Conference on Information and Knowledge Management », Maui, Hawaii, October 2012.|
|Uncontrolled Keywords:||Markov logic networks, news recommendation, query log analysis, recommendation snippets|
|Subjects:||Q Science > QA Mathematics > QA75 Electronic computers. Computer science|
|Research Area:||Economics and Institutional Change|
|Depositing User:||Users 43 not found.|
|Date Deposited:||19 Dec 2012 11:09|
|Last Modified:||12 Mar 2013 14:57|
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