ABSTRACT
Current web search engines return result pages containing mostly text summary even though the matched web pages may contain informative pictures. A text excerpt (i.e. snippet) is generated by selecting keywords around the matched query terms for each returned page to provide context for user's relevance judgment. However, in many scenarios, we found that the pictures in web pages, if selected properly, could be added into search result pages and provide richer contextual description because a picture is worth a thousand words. Such new summary is named as image excerpts. By well designed user study, we demonstrate image excerpts can help users make much quicker relevance judgment of search results for a wide range of query types. To implement this idea, we propose a practicable approach to automatically generate image excerpts in the result pages by considering the dominance of each picture in each web page and the relevance of the picture to the query. We also outline an efficient way to incorporate image excerpts in web search engines. Web search engines can adopt our approach by slightly modifying their index and inserting a few low cost operations in their workflow. Our experiments on a large web dataset indicate the performance of the proposed approach is very promising.
- Google Trends. http://www.google.com/trends.Google Scholar
- D. Cai, X. He, Z. Li, and et al. Hierarchical clustering of www image search results using visual, textual and link information. In Proc. of ACM international conference on Multimedia, 2004. Google Scholar
Digital Library
- T. A. S. Coelho, P. Calado, and et al. Image retrieval using multiple evidence ranking. IEEE Transaction on Knowledge and Data Engineering, 2004. Google Scholar
Digital Library
- Y. Freund, R. Iyer, R. E. Schapire, and Y. Singer. An efficient boosting algorithm for combining preferences. Machine Learning Research, 2003. Google Scholar
Digital Library
- A. Hartmann and R. Lienhart. Automatic classification of images on the web. In Proc. of Storage and Retrieval for Media Databases, 2001.Google Scholar
- T. Joachims. Optimizing search engines using click-through data. In Proceedings of the ACM Conference on Knowledge Discovery and Data Mining, 2002. Google Scholar
Digital Library
- G. Lu and B. Willam. An integrated www image retrieval system. In Proc. Fifth Australian World Wide Web Conference, 2004.Google Scholar
- G. Rätsch, T. Onoda, and K.-R. Müler. Soft margins for adaboost. Machine Learning, 42(3):287--320, 2001. Google Scholar
Digital Library
- H. H. Tong, M. J. Li, H. J. Zhang, and et al. Learning no-reference quality metric by examples. In Proc. Of International Conference on Multi-Media Modeling, 2005. Google Scholar
Digital Library
- V. Vapnik. The nature of statistical learning theory. Statistics for Engineering and Information Science. Springer Verlag, Berlin, 2000. Google Scholar
Digital Library
- Z. Wang, A. Bovik, H. Sheikh, and E. Simoncelli. Image quality assessment: from error visibility to structural similarity. IEEE Transactions on Image Processing, 2004. Google Scholar
Digital Library
- R. Xiao, L. Zhu, and H. Zhang. Boosting chain learning for object detection. In Proc. of International Conference on Computer Vision, 2003. Google Scholar
Digital Library
- A. Woodruff, A. Faulring, R. Rosenholtz, J. Morrison, P. Pirolli, Using Thumbnails to Search the Web. SIGCHI'01, March 31-April 4, 2001, Seattle, USA. Google Scholar
Digital Library
- E. Ayers, and J. Stasko, Using Graphic History in Browsing the World Wide Web. In Proc. 4th Intl. WWW Conf., December 1995.Google Scholar
- A. L. Berger, and V.O. Mittal. OCELOT: A System for Summarizing Web Pages. In Proc. of the 23rd annual international ACM SIGIR, Athens, Greece, 2000. Google Scholar
Digital Library
- O. Buyukkokten, H. Garcia-Molina, and A. Paepcke. Seeing the whole in parts: text summarization for Web browsing on handheld devices. In Proc. of WWW10, Hong Kong, China, May 2001. Google Scholar
Digital Library
- A. Chapman (ed.). Making Sense: Teaching critical reading across the curriculum. The College Board: NY, 1993.Google Scholar
- V. Coltheart (ed.). Fleeting Memories: Cognition of Brief Visual Stimuli. MIT Press: Cambridge, MA, 1999 (pp. 32--70).Google Scholar
- M. Czerwinski, M. V. Dantzich, G. Robertson, and H. Hoffman. The contribution of thumbnail image, mouseover text and spatial location memory to web page retrieval in 3D. In Proc. INTERACT '99, 1999, 163--170.Google Scholar
- J. Y. Delort, B. Bouchon-Meunier, and M. Rifqi. Web document summarization by context. In Proc. Of WWW12, 2003.Google Scholar
- S. Dziadosz, and R. Chandraseka, Do Thumbnail Previews Help Users Make Better Relevance Decisions about Web Search Results? In Proc. Of SIGIR'02, August 11-15, 2002, Tampere, Finland. Google Scholar
Digital Library
- Google news search. http://news.google.comGoogle Scholar
- S. Kaasten, and S. Greenberg. Integrating Back, History and Bookmarks in Web Browsers. In Proc. of CHI'01, ACM Press, 379--380. Google Scholar
Digital Library
- T. Kopetzky, and M. Mühlhäuser. Visual Preview for Link Traversal on the WWW. In Proc. 8th Intl. WWW Conf., May 1999, 447--454. Google Scholar
Digital Library
- J. B. Morrison, P. Pirolli, and S. K. Card. A Taxonomic Analysis of What World Wide Web Activities Significantly, Impact People's Decisions and Actions. Xerox PARC Report UIR-R-2000--17.Google Scholar
- A. Paivio. Pictures and Words in Visual Search. Memory & Cognition 2, 3, 515--521, 1974.Google Scholar
- S. Brin, and L. Page, The anatomy of a large-scale hypertextual web search engine. Journal of Computer Networks and ISDN Systems, 1998. Google Scholar
Digital Library
- D. Shen, Z. Chen, Q. Yang, H. J. Zeng, B. Zhang, Y. Lu, and W. Y. Ma. Web-page Classification through Summarization. In Proc. of the 27th ACM International Conference of Information Retrieval (SIGIR-2004). Sheffield, UK. July 2004. Google Scholar
Digital Library
- M. Wynblatt, and D. Benson. Web Page Caricatures Multimedia Summaries for WWW Documents. In Proc. IEEE Intl. Conf. on Multimedia Computing and Systems, June 1998, 194--199. Google Scholar
Digital Library
- D. Shen, J. T. Sun, Q. Yang, and Z. Chen, Building Bridges for Web Query Classification, In Proc. Of SIGIR, 2006 Google Scholar
Digital Library
- A. Broder, A taxonomy of web search, SIGIR Forum, 2002 Google Scholar
Digital Library
- B. Wang, Z. Li, M. Li, W. Y. Ma. Large-scale Duplicate Detection for Web Image Search. In Proc. of ICME, 2006Google Scholar
Cross Ref
Index Terms
Improving relevance judgment of web search results with image excerpts
Recommendations
Improving Ranking Consistency for Web Search by Leveraging a Knowledge Base and Search Logs
CIKM '15: Proceedings of the 24th ACM International on Conference on Information and Knowledge ManagementIn this paper, we propose a new idea called ranking consistency in web search. Relevance ranking is one of the biggest problems in creating an effective web search system. Given some queries with similar search intents, conventional approaches typically ...
Intent-based diversification of web search results: metrics and algorithms
We study the problem of web search result diversification in the case where intent based relevance scores are available. A diversified search result will hopefully satisfy the information need of user-L.s who may have different intents. In this context, ...
A Study of Distinctiveness in Web Results of Two Search Engines
WWW '15 Companion: Proceedings of the 24th International Conference on World Wide WebGoogle and Bing have emerged as the diarchy that arbitrates what documents are seen by Web searchers, particularly those desiring English language documents. We seek to study how distinctive are the top results presented to the users by the two search ...





Comments