Towards Personalized Multilingual Information Access - Exploring the Browsing and Search Behavior of Multilingual Users
The shift from the originally English-language-dominated web towards a truly global world wide web has generated a pressing need to develop novel solutions that address multilingual user diversity. In particular, many web users today are polyglots, i.e. they are proficient in more than one language. However, little is known about the browsing and search habits of such users, and even less about how to best assist their multilingual behaviors through appropriate systems and tools. In order to gain a better understanding, this paper presents a survey of 385 polyglot web users, focusing specifically on the relationship between multiple language proficiency and browsing/search language choice. Results from the survey indicate that polyglot users make significant use of multiple languages during their daily browsing and searching, and that contextual factors such as language proficiency, usage purpose, and topic domain have a significant influence on their language choice and frequency. The paper provides a detailed analysis regarding each of these factors, and offers insights about how to support multilingual users through novel Personalized Multilingual InformationAccess systems.
KeywordsPersonalization Multilingual Information Access User Study
Unable to display preview. Download preview PDF.
- 1.Vallet, D., Cantador, I., Jose, J.M.: Personalizing web search with folksonomy-based user and document profiles. In: Gurrin, C., He, Y., Kazai, G., Kruschwitz, U., Little, S., Roelleke, T., Rüger, S., van Rijsbergen, K. (eds.) ECIR 2010. LNCS, vol. 5993, pp. 420–431. Springer, Heidelberg (2010)CrossRefGoogle Scholar
- 5.Ghorab, M.R., Zhou, D., O’Connor, A., Wade, V.: Personalised Information Retrieval: survey and classification. User Model. User-Adapt. Interact. 23, 381–443 (2013)Google Scholar
- 6.Steichen, B., Ashman, H., Wade, V.: A comparative survey of Personalised Information Retrieval and Adaptive Hypermedia techniques. Inf. Process. Manag. 48, 698–724 (2012)Google Scholar
- 7.Nie, J.-Y.: Cross-Language Information Retrieval. Morgan and Claypool Publishers (2010)Google Scholar
- 9.Gao, W., Niu, C., Nie, J.-Y., Zhou, M., Hu, J., Wong, K.-F., Hon, H.-W.: Cross-lingual query suggestion using query logs of different languages. In: Proc. 30th Int. Conf. on Research and Dev. in Information Retrieval (SIGIR), pp. 463–470 (2007)Google Scholar
- 10.Cao, G., Gao, J., Nie, J.-Y., Bai, J.: Extending query translation to cross-language query expansion with markov chain models. In: Proceedings of the Sixteenth ACM Conf. on Information and Knowledge Management. pp. 351–360 (2007)Google Scholar
- 11.Magdy, W., Jones, G.J.F.: An efficient method for using machine translation technologies in cross-language patent search. In: Proceedings of the 20th ACM Int. Conf. on Information and Knowledge Management. pp. 1925–1928 (2011)Google Scholar
- 12.Amato, G., Cigarrán, J., Gonzalo, J., Peters, C., Savino, P.: MultiMatch – Multilin-gual/Multimedia Access to Cultural Heritage. Research and Advanced Technology for Digital Libraries, pp. 505–508 (2007)Google Scholar
- 18.Geertzen, J.: Inter-Rater Agreement with multiple raters and variables, https://mlnl.net/jg/software/ira/ (retrieved January 31, 2014)