Webarc:Temporally Anchored Scoring Experiments: Difference between revisions
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==Queries== | ==Queries== | ||
Based on the AOL query log made available | Based on the AOL query log made briefly available in 2005, we built our temporal query load by extracting multi-term query phrases where the user selected an English Wikipedia article among the search results. Note that the different temporal contexts give different relative weights to each of the query terms, yielding different result rankings. In other words, for a query phrase with term t1 and t2, t1 may be given more weight than t2 at a certain query time span qts1, but it may be opposite at a different query time span qts2. This means that two document versions that belong to both qts1 and qts2 can have different rankings depending on the specified query time span. However, in the case of single-term queries, any two document versions will retain their ranking regardless of the specified query time span, as long as both belong to the query time span. In our experiments, we highlight the impact on the search results from different query time spans by focusing only on multi-term queries. The more general case where single-term queries are also included will be able to be inferred from the results from query log analysis studies that report about 80% of web queries are multi-termed. | ||
Once we extracted qualified query phrases, we further filtered out less frequently appearing phrases. In particular, we took the query phrases that appear 10 times or more in the log. We gathered a total of 223 such query phrases. | |||
Using the 223 query phrases, we constructed a temporal query load by combining query time spans with each of the query phrases. Specifically, we used 8 query time span lengths - 1, 2, 4, 8, 16, 32, 64, and 83 months. For each query time span length, we made all possible query time spans, starting from the first month. For example, for the query time span length of 1 month, we made 83 query time spans, starting from (February 1st 2001 ~ February 28th 2001), ending at (December 1st 2007 ~ December 31st 2007). A total of 462 different query time spans were resulted. To sum up, we generated 103,026 (= 223 x 462)queries in each experiment session. | |||
==Further Information== | ==Further Information== | ||
* [[Webarc:Input Dataset Statistics |[1] Input Dataset Statistics]] | * [[Webarc:Input Dataset Statistics |[1] Input Dataset Statistics]] | ||
* [[Webarc:Tools Developed |[2] Tools Developed]] | * [[Webarc:Tools Developed |[2] Tools Developed]] | ||
Revision as of 18:41, 18 November 2009
Input Dataset
We preprocessed the entire revision history of the English Wikipedia from 2001 to 2007 (available at http://www.archive.org/details/enwiki-20080425). After preprocessing, we obtained 84 monthly snapshots starting from January 2001 ending in December 2007. Included in each monthly snapshot are the latest revision of existing articles at the end of the month. For example, the Wikipedia article 'Economy of the United States' created on August 21 2002 was included in the six monthly snapshots of August 2002, September 2002, ..., January 2003 since there is no newer revision made until February 7 2003, whereas the same article revised on August 16 2002 was not included in any of the snapshots. This page shows further details on the monthly snapshots.
Queries
Based on the AOL query log made briefly available in 2005, we built our temporal query load by extracting multi-term query phrases where the user selected an English Wikipedia article among the search results. Note that the different temporal contexts give different relative weights to each of the query terms, yielding different result rankings. In other words, for a query phrase with term t1 and t2, t1 may be given more weight than t2 at a certain query time span qts1, but it may be opposite at a different query time span qts2. This means that two document versions that belong to both qts1 and qts2 can have different rankings depending on the specified query time span. However, in the case of single-term queries, any two document versions will retain their ranking regardless of the specified query time span, as long as both belong to the query time span. In our experiments, we highlight the impact on the search results from different query time spans by focusing only on multi-term queries. The more general case where single-term queries are also included will be able to be inferred from the results from query log analysis studies that report about 80% of web queries are multi-termed.
Once we extracted qualified query phrases, we further filtered out less frequently appearing phrases. In particular, we took the query phrases that appear 10 times or more in the log. We gathered a total of 223 such query phrases.
Using the 223 query phrases, we constructed a temporal query load by combining query time spans with each of the query phrases. Specifically, we used 8 query time span lengths - 1, 2, 4, 8, 16, 32, 64, and 83 months. For each query time span length, we made all possible query time spans, starting from the first month. For example, for the query time span length of 1 month, we made 83 query time spans, starting from (February 1st 2001 ~ February 28th 2001), ending at (December 1st 2007 ~ December 31st 2007). A total of 462 different query time spans were resulted. To sum up, we generated 103,026 (= 223 x 462)queries in each experiment session.
