1
Dwayne E Bowman, Ruben E Ortega, Michael L Hamrick, Joel R Spiegel, Timothy R Kohn: Refining search queries by the suggestion of correlated terms from prior searches. Amazon Com, Knobbe Martens Olson & Bear, December 21, 1999: US06006225 (722 worldwide citation)

A search engine is disclosed which suggests related terms to the user to allow the user to refine a search. The related terms are generated using query term correlation data which reflects the frequencies with which specific terms have previously appeared within the same query. The correlation data ...


2
Dwayne E Bowman, Ruben E Ortega, Michael L Hamrick, Joel R Spiegel, Timothy R Kohn: System and method for refining search queries. Amazon com, Knobbe Martens Olson & Bear, January 2, 2001: US06169986 (333 worldwide citation)

A search engine is disclosed which suggests related terms to the user to allow the user to refine a search. The related terms are generated using query term correlation data which reflects the frequencies with which specific terms have previously appeared within the same query. The correlation data ...


3
Ruben Ernesto Ortega, Dwayne Edward Bowman, Michael L Hamrick, Joel R Spiegel, Timothy R Kohn: System and method for correcting spelling errors in search queries. Amazon com, Knobbe Martens Olson & Bear, November 7, 2000: US06144958 (141 worldwide citation)

A search engine is disclosed that uses correlations between search terms to correct misspelled terms within search queries. The correlations are based at least in-part on historical query submissions to the search engine. Preferably, the correlations reflect the frequencies with which the search ter ...


4
Ruben E Ortega, Dwayne E Bowman, Michael L Hamrick, Joel R Spiegel, Timothy R Kohn: Identifying related search terms based on search behaviors of users. A9 com, Knobbe Martens Olson & Bear, August 9, 2011: US07996398 (2 worldwide citation)

A system is disclosed that identifies related search terms by performing a term co-occurrence analysis of search query submissions of users. The system may give different amounts of weight to different search query submissions based, for example, on whether subsequent user actions reveal that partic ...


5
Kamlesh T Talreja, Timothy R Kohn, Jonathan Joseph Bryak: Systems and methods for offer selection. Amazon Technologies, Kilpatrick Townsend and Stockton, November 12, 2013: US08583513 (1 worldwide citation)

A featured offer for an item in an electronic marketplace is selected based on factors such as estimated conversion rate and contribution profit. Qualified offers from various merchants are analyzed using a variety of filters, algorithms, and/or criteria to select an offer that meets the goal(s) of ...


6
Kamlesh T Talreja, Aditya Vikram Naredi, Timothy R Kohn: System and method for managing a listing of offers between buyers and sellers. Amazon Technologies, Thomas Kayden Horstemeyer & Risley, October 2, 2012: US08280782 (1 worldwide citation)

A computer-implemented system and method for generating and display a listing of offers of items to be sold on a third party marketplace. The system includes a processing unit and a storage device coupled to the processing unit. The processing unit has stored information for configuring the processi ...


7
Robert Kennedy, Timothy R Kohn, Devin Kowatch, Richard A Sheehan: Network change management. Amazon Technologies, Sutherland Asbill & Brennan, March 22, 2016: US09294352

Systems and methods for implementing network changes are described herein. In one aspect, a network change procedure may be comprised of a plurality of scripts that may implement a change in the network. In one embodiment, the deployment may be paused after the script has been executed. During the p ...


8
Ruben E Ortega, Dwayne E Bowman, Michael L Hamrick, Joel R Spiegel, Timothy R Kohn: Identifying related search terms based on search behaviors of users. Knobbe Martens Olson & Bear, February 10, 2011: US20110035370-A1

A system is disclosed that identifies related search terms by performing a term co-occurrence analysis of search query submissions of users. The system may give different amounts of weight to different search query submissions based, for example, on whether subsequent user actions reveal that partic ...



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