%0 Book Section %1 citeulike:13232396 %A Anderson, Terry %A Hussam, Ali %A Plummer, Bill %A Jacobs, Nathan %B Digital Libraries: People, Knowledge, and Technology %D 2002 %E Lim, Ee-Peng %E Foo, Schubert %E Khoo, Chris %E Chen, Hsinchun %E Fox, Edward %E Urs, Shalini %E Costantino, Thanos %I Springer Berlin Heidelberg %K information-visualization relevance %P 440--451 %R 10.1007/3-540-36227-4_52 %T Pie Charts for Visualizing Query Term Frequency in Search Results %U http://dx.doi.org/10.1007/3-540-36227-4_52 %V 2555 %X Search engine queries are normally brief but often return unmanageably long results, with which users struggle to determine document quality and relevance. In recent years, many studies have enhanced search results with metadata displayed as visual cues. Their success in helping users make faster and more accurate document judgments has been uneven, reflecting the wide range of information needs and document selection strategies of users, and also the relative effectiveness of different visualization forms. We identify the frequency with which query terms are found in a document as a straightforward and effective way for users to see the relationship between their query and the search results. In our prototype, we display these frequencies using simple pie charts. Despite performance limitations, evaluation with 101 users has been promising and suggests future developments.

@incollection{citeulike:13232396, abstract = {{Search engine queries are normally brief but often return unmanageably long results, with which users struggle to determine document quality and relevance. In recent years, many studies have enhanced search results with metadata displayed as visual cues. Their success in helping users make faster and more accurate document judgments has been uneven, reflecting the wide range of information needs and document selection strategies of users, and also the relative effectiveness of different visualization forms. We identify the frequency with which query terms are found in a document as a straightforward and effective way for users to see the relationship between their query and the search results. In our prototype, we display these frequencies using simple pie charts. Despite performance limitations, evaluation with 101 users has been promising and suggests future developments.}}, added-at = {2017-11-15T17:02:25.000+0100}, author = {Anderson, Terry and Hussam, Ali and Plummer, Bill and Jacobs, Nathan}, biburl = {https://www.bibsonomy.org/bibtex/27a75a449c0db4d765792d104f885df67/brusilovsky}, booktitle = {Digital Libraries: People, Knowledge, and Technology}, citeulike-article-id = {13232396}, citeulike-linkout-0 = {http://dx.doi.org/10.1007/3-540-36227-4_52}, citeulike-linkout-1 = {http://link.springer.com/chapter/10.1007/3-540-36227-4_52}, doi = {10.1007/3-540-36227-4_52}, editor = {Lim, Ee-Peng and Foo, Schubert and Khoo, Chris and Chen, Hsinchun and Fox, Edward and Urs, Shalini and Costantino, Thanos}, interhash = {83a4968c85542dd8eb30aaa52f831dee}, intrahash = {7a75a449c0db4d765792d104f885df67}, keywords = {information-visualization relevance}, pages = {440--451}, posted-at = {2014-06-18 12:49:22}, priority = {2}, publisher = {Springer Berlin Heidelberg}, series = {Lecture Notes in Computer Science}, timestamp = {2020-07-28T17:22:24.000+0200}, title = {{Pie Charts for Visualizing Query Term Frequency in Search Results}}, url = {http://dx.doi.org/10.1007/3-540-36227-4_52}, volume = 2555, year = 2002 }