Interest and Evaluation of Aggregated Search

Arlind Kopliku, Firas Damak, Karen Pinel-Sauvagnat, Mohand Boughanem
2011 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology  
Major search engines perform what is known as Aggregated Search (AS). They integrate results coming from different vertical search engines (images, videos, news, etc.) with typical Web search results. Aggregated search is relatively new and its advantages need to be evaluated. Some existing works have already tried to evaluate the interest (usefulness) of aggregated search as well as the effectiveness of the existing approaches. However, most of evaluation methodologies were based (i) on what
more » ... call relevance by intent (i.e. search results were not shown to real users), and (ii) short text queries. In this paper, we conducted a user study which was designed to revisit and compare the interest of aggregated search, by exploiting both relevance by intent and content, and using both short text and fixed need queries. This user study allowed us to analyze the distribution of relevant results across different verticals, and to show that AS helps to identify complementary relevant sources for the same information need. Comparison between relevance by intent and relevance by content showed that relevance by intent introduces a bias in evaluation. Discussion about the results also allowed us to identify some useful thoughts concerning the evaluation of AS approaches.
doi:10.1109/wi-iat.2011.99 dblp:conf/webi/KoplikuDPB11 fatcat:6e4o6ditcratbowp3nq2a2hdai