A Task-Based Evaluation of an Aggregated Search Interface

1. Radlinski, F., Dumais, S.: Improving personalized web search using result diversification. In: ACM SIGIR conference on Research and development in information retrieval, pp. 691–692 (2006)

   Google Scholar 

2. Coyle, M., Smyth, B.: On the importance of being diverse: analysing similarity and diversity in web search. In: Source Intelligent Information Processing II, pp. 341–350 (2004)

   Google Scholar 

3. Yee, K.P., Swearingen, K., Li, K., Hearst, M.: Faceted metadata for image search and browsing. In: SIGCHI conference on Human factors in computing systems, pp. 401–408 (2003)

   Google Scholar 

4. Sanderson, M., Tang, J., Arni, T., Clough, P.: What Else Is There? Search Diversity Examined. In: Boughanem, M., et al. (eds.) ECIR 2009. LNCS, vol. 5478, pp. 562–569. Springer, Heidelberg (2009)

   Google Scholar 

5. Zamir, O., Etzioni, O.: Grouper: a dynamic clustering interface to Web search results. Computer Networks: The International Journal of Computer and Telecommunications Networking (1999)

   Google Scholar 

6. Heimonen, T., Aula, A., Hutchinson, H., Granka, L.: Comparing the User Experience of Search User Interface Designs. In: CHI 2008 Workshop on User Experience Evaluation Methods in Product Development (2008)

   Google Scholar 

7. Wilson, M.L., Schraefel, M.C., White, R.W.: Evaluating Advanced Search Interfaces using Established Information-Seeking Models. Journal of the American Society for Information Science and Technology (2009)

   Google Scholar 

8. Hoeber, O., Yang, X.D.: User-Oriented Evaluation Methods for Interactive Web Search Interfaces. In: IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops, pp. 239–243 (2007)

   Google Scholar 

9. Beaulieu, M.: Experiments with interfaces to support query expansion. Journal of Documentation 53(1), 8–19 (1997)

   Article  Google Scholar 

10. Borlund, P.: Experimental components for the evaluations of interactive information retrieval systems. Journal of Documentation 56(1), 71–90 (2000)

    Article  MATH  Google Scholar 

11. Callan, J.: Distributed Information Retrieval. In: Advances in Information Retrieval, vol. 5, pp. 127–150. Kluwer Academic Publishers, Dordrecht (2000)

    Google Scholar 

12. Diaz, F.: Integration of news content into web results. In: ACM International Conference on Web Search and Data Mining, pp. 182–191 (2009)

    Google Scholar 

13. Dumais, S., Cutrell, E., Chen, H.: Optimizing search by showing results in context. In: SIGCHI Conference on Human Factors in Computing Systems, pp. 277–284 (2001)

    Google Scholar 

14. Jansen, B.J., Booth, D.L., Spink, A.: Determining the informational, navigational, and transactional intent of web queries. Inf. Process. Manage. 44(3), 1251–1266 (2008)

    Article  Google Scholar 

15. Kural, Y., Robertson, S., Jones, S.: Deciphering cluster representations. Inf. Process. Manage. 37(4), 593–601 (2001)

    Article  MATH  Google Scholar 

16. Shokouhi, M., Baillie, M., Azzopardi, L.: Updating collection representations for federated search. In: ACM SIGIR conference on Research and development in information retrieval, pp. 511–518 (2007)

    Google Scholar 

17. Si, L., Callan, J.: Relevant document distribution estimation method for resource selection. In: ACM SIGIR conference on Research and development in informaion retrieval, pp. 298–305 (2003)

    Google Scholar 

18. Si, L., Lu, J., Callan, J.: Distributed information retrieval with skewed database size distributions. In: dg.o 2003: Annual national conference on Digital government research, pp. 1–6. Digital Government Society of North America (2003)

    Google Scholar 

19. Sushmita, S., Joho, H., Lalmas, M., Jose, J.M.: Understanding domain “relevance” in web search. In: WWW 2009 Workshop on Web Search Result Summarization and Presentation (2009)

    Google Scholar 

Download references