TY - GEN
T1 - Topic-specific Analysis of search queries
AU - Bar-Ilan, Judit
AU - Zhu, Zheng
AU - Levene, Mark
PY - 2009
Y1 - 2009
N2 - The analysis of search engine logs is important in order to understand how users interact with a search engine. Conventional analysis of search engine log data looks at various metrics such as query and session length aggregated over the full data set. Here we segment the data according to a top-level ontology of web search and compute the metrics on a topic by topic basis. Our results show that although for a given metric, such as query length, the statistics of most classes are similar to the aggregate statistic; there are usually some outlier classes which exhibit deviant behavior.
AB - The analysis of search engine logs is important in order to understand how users interact with a search engine. Conventional analysis of search engine log data looks at various metrics such as query and session length aggregated over the full data set. Here we segment the data according to a top-level ontology of web search and compute the metrics on a topic by topic basis. Our results show that although for a given metric, such as query length, the statistics of most classes are similar to the aggregate statistic; there are usually some outlier classes which exhibit deviant behavior.
UR - http://www.scopus.com/inward/record.url?scp=67650097035&partnerID=8YFLogxK
U2 - 10.1145/1507509.1507515
DO - 10.1145/1507509.1507515
M3 - ???researchoutput.researchoutputtypes.contributiontobookanthology.conference???
AN - SCOPUS:67650097035
SN - 9781605584348
T3 - Proceedings of Workshop on Web Search Click Data, WSCD'09
SP - 35
EP - 42
BT - Proceedings of Workshop on Web Search Click Data, WSCD'09
T2 - Workshop on Web Search Click Data, WSCD'09
Y2 - 9 February 2009 through 9 February 2009
ER -