Abstract
The World Wide Web has become a platform for news publication in the past few years. Many television channels, magazines and newspapers have started publishing digital versions of the news stories online. It is observed that recommendation systems can automatically process lengthy articles and identify similar articles to readers based on a predefined criteria i.e. collaborative filtering, content-based filtering approach. The paper presents a content-based similarity measure for linking digital news stories published in various newspapers during the preservation process. The study compares similarity of news articles based on human judgment with a similarity value computed automatically using common ratio measure for stories. The results are generalized by defining a threshold value based on multiple experimental results using the proposed approach.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Agarwal, D., Chen, B.-C., Elango, P., Wang, X.: Personalized click shaping through lagrangian duality for online recommendation. In Proceedings of the 35th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 485–494. ACM (2012)
Athalye, S.: Recommendation system for news reader (2013)
Burda, D., Teuteberg, F.: Sustaining accessibility of information through digital preservation: a literature review. J. Inf. Sci. 39(4), 442–458 (2013)
Chun, D.: On indexing of key words. Acta Editologica 16(2), 105–106 (2004)
da Silva, J.R., Ribeiro, C., Lopes, J.C.: A data curation experiment at U. Porto using DSpace (2011)
Doychev, D., Lawlor, A., Rafter, R., Smyth, B.: An analysis of recommender algorithms for online news. In: CLEF (Working Notes), pp. 825–836. Citeseer (2014)
Fortuna, B., Fortuna, C., Mladenić, D.: Real-time news recommender system. In: Balcázar, J.L., Bonchi, F., Gionis, A., Sebag, M. (eds.) ECML PKDD 2010. LNCS (LNAI), vol. 6323, pp. 583–586. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-15939-8_38
Khan, M., Ur Rahman, A.: Digital news story preservation framework. In: Proceedings of Digital Libraries: Providing Quality Information: 17th International Conference on Asia-Pacific Digital Libraries, ICADL 2015, Seoul, Korea, 9–12 December 2015, vol. 9469, p. 350. Springer (2015). https://doi.org/10.1007/978-3-319-27974-9
Khan, M., Ur Rahman, A., Daud Awan, M., Alam, S.M.: Normalizing digital news-stories for preservation. In: 2016 Eleventh International Conference on Digital Information Management (ICDIM), pp. 85–90. IEEE (2016)
Li, L., Li, T.: News recommendation via hypergraph learning: encapsulation of user behavior and news content. In: Proceedings of the Sixth ACM International Conference on Web Search and Data Mining, pp. 305–314. ACM (2013)
Li, L., Wang, D.-D., Zhu, S.-Z., Li, T.: Personalized news recommendation: a review and an experimental investigation. J. Comput. Sci. Technol. 26(5), 754–766 (2011)
Li, L., Zheng, L., Yang, F., Li, T.: Modeling and broadening temporal user interest in personalized news recommendation. Expert Syst. Appl. 41(7), 3168–3177 (2014)
Melville, P., Sindhwani, V.: Recommender systems. In: Sammut, C., Webb, G.I. (eds.) Encyclopedia of Machine Learning, pp. 829–838. Springer, Heidelberg (2011). https://doi.org/10.1007/978-0-387-30164-8_705
Pu, P., Chen, L., Hu, R.: A user-centric evaluation framework for recommender systems. In: Proceedings of the Fifth ACM Conference on Recommender Systems, pp. 157–164. ACM (2011)
Ur Rahman, A.: Data warehouses in the path from databases to archives. Ph.D. thesis, Faculty of Engineering, University of Porto, July 2013
Said, A., BellogĂn, A., Lin, J., de Vries, A.: Do recommendations matter?: news recommendation in real life. In: Proceedings of the Companion Publication of the 17th ACM Conference on Computer Supported Cooperative Work & Social Computing, pp. 237–240. ACM (2014)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Khan, M., Ur Rahman, A., Daud Awan, M. (2018). Term-Based Approach for Linking Digital News Stories. In: Serra, G., Tasso, C. (eds) Digital Libraries and Multimedia Archives. IRCDL 2018. Communications in Computer and Information Science, vol 806. Springer, Cham. https://doi.org/10.1007/978-3-319-73165-0_13
Download citation
DOI: https://doi.org/10.1007/978-3-319-73165-0_13
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-73164-3
Online ISBN: 978-3-319-73165-0
eBook Packages: Computer ScienceComputer Science (R0)