This application relates to a computer-implemented method and system for determining an order of presentation of search results.
When a user submits a search request via a web page, a search engine (e.g., a search engine designed to search for information on the World Wide Web or a search engine designed to search for items available within a particular on-line trading platform) may be able to sort through the vast amount of data and present the user with results that match the terms in the search request. With some search engines, matches may even be ranked, so that the most relevant results are displayed at the top of the search results list presented on the user's display device.
Embodiments of the present invention are illustrated by way of example and not limitation in the figures of the accompanying drawings, in which like reference numbers indicate similar elements and in which:
A method and system for determining an order of presentation of search results is described. In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of an embodiment of the present invention. It will be evident, however, to one skilled in the art, that the present invention may be practiced without these specific details.
In response to a search request, a search engine may return search results that include data items of disparate information formats. For example, where a user is interacting with an on-line trading platform, the formats of search result items may include, for example, an auction format, a known fixed price format, or an unknown fixed-price format. Each of these formats may conceptually be associated with populations or buckets of data items that need to be positioned into a list of search results before they may be presented to a user. Each of the formats are further associated with a different algorithm that is used to compute a score (e.g., a relevance score) for each of the data items for positioning them among the search results. Intermingling of the data items in the search results based on respective scores associated with the data items may not always reflect relative relevance of the items accurately, because a score for a data item from one population (e.g., associated with a first format) may not be directly comparable with a score of a data item from another population (e.g., associated with a second format).
In one example embodiment, a method and system may be implemented to determine an order of presentation in the search results, where the search results include sets of data items (populations) associated with different formats, based on a target ratio that reflects exposure percentage in a list of search results to be presented to a user for each of the populations. For example, population exposure percentages for items associated with different formats may be designated as 60% for the auction bucket (containing items associated with the auction format), 30% for the known fixed-price bucket (containing items associated with the known fixed-price format), and 10% for the unknown fixed-price bucket (containing items associated with the unknown fixed-price format). The known fixed-price population refers to items for sale within an on-line trading platform that have an associated purchase history. For example, an on-line trading platform may have static and dynamic information for an item that was previously sold. Such information may be obtained from the demand side (e.g., buyer) or the supply side (seller). The unknown fixed-price population refers to items that have not been previously identified as being for sale within an on-line trading platform. Accordingly, a purchase history does not exist for such an item.
The method and system for determining an order of presentation in the search results may operate by 1) positioning a data item associated with the dominant format type (in this example, the auction format) as the first item in the search results list; 2) selecting, at random, another format type and the associated candidate bucket; 3) calculating the candidate bucket exposure percentage if an item from the selected format type were to be added to the search results list; and 4) comparing the candidate bucket exposure percentage with the desired bucket exposure percentage. Steps 2-4 may be iterated until a bucket exposure percentage that is closest to the desired bucket exposure percentage is identified. For example, the system may first select a data item from the auction population because the auction format is the dominant format (in this example, 60%). Next, the system may select a data item from the known fixed price population to achieve a ratio of 50%, 50%, 0%, which is closest to the desired ratio (in this example, 60%, 30%, 10%).
A relationship between the bucket exposures of items of any two format types may be expressed as a ratio (termed “target ratio”). In the example above, the target ratio between the number of items in the auction format and the number of items in the fixed-price format is 6:3. An example system for determining an order of presentation in the search results may be configured to first obtain search results in the form of a first set comprising items in the auction format and a second set comprising items in the fixed-price format and then generate a list of search results ordered based on the 6:3 target ratio. As in the example above, the first item selected to be placed in the list of search results is from the auction set (as the auction set is the dominating format type in this example). In order to determine the next item to be added to the list of results, the system may determine respective resulting ratios in the list of results, assuming the next selected item is from the first set or from the second set. The next item is selected from a set if an assumed selection of the next item from that set results in a ratio that is closer to the target ratio.
The target ratio may be optimized by monitoring revenue while adjusting respective exposure percentages for items in different formats. For example, where search results comprise two populations including auction items and fixed priced items, the search results may be experimentally presented to users based on the target ratio or based on exposure percentages. The revenue generated with respect to items associated with different formats may be monitored for a period of time, and, based on the monitored revenue, the target ratio may be adjusted to increase exposure of items in a format that was determined as associated with greater revenue. For example, revenues may be measured for bucket exposure percentages, including 47% auction and 53% fixed price mix, or 48% auction and 52% fixed-price mix, or 49% auction and 51% fixed-price mix, or any other mix that adds up to 100%. The combination of exposure percentages associated with the highest revenue may be used for configuring the system for determining an order of presentation of the search results.
It will be noted that the method and system for determining an order of presentation of the search results may be utilized beneficially outside of the field of electronic commerce, e.g., wherever disparate information formats are identified. An example method and system for determining an order of presentation of the search results may be implemented in the context of a network environment 100 illustrated in
As shown in
The client system 110 may utilize the browser application 112 to access services provided by the server system 140. For example, the client 110 may access services provided by a system associated with the on-line trading platform 142. The server 140 may also host a system 144 for determining an order of presentation of search results. The system 144 may be configured to process search results associated with the on-line trading platform 142 or any results of searching for information on the World Wide Web. While the system 144 is illustrated as a stand-alone module, the system 144 may be implemented, e.g., as part of the on-line trading platform 142. As shown in
The intermingler 206 may be configured to determine an order of presentation of the search results based on the target ratio, which is described in further detail below, with reference to
As shown in
The operation 340, determining of an order of presentation of the search results, may be performed as shown in operations 350-390. At operation 350, an item from the first set is selected and positioned in a list of search results. Then, in operation 360, a first new ratio between items from the first set in the list of search results and items from the second set in the list of search results is determined, assuming the next selected item is from the first set. A second new ratio (between items from the first set in the list of search results and items from the second set in the list of search results), assuming the next selected item is from the second set, is determined at operation 370. At operation 380, the intermingler 206 compares a first difference (between the first new ratio and the target ratio with a second difference between the second new ratio and the target ratio) and selects the next item for positioning in the list of search results, based on a result of the comparing, at operation 390. For example, the intermingler 206 may be configured to select the next item from the first set of items in the first format and position it in the list of search results as the next item if it is determined that the first difference is less than the second difference.
As mentioned above, the target ratio may reflect respective exposure percentages for items in the first format and items in the second format.
As shown in
At operation 442, an item from the first set is selected and positioned in the list of search results. At operation 444, the intermingler 206 determines a first new exposure percentage associated with items in the first format in the list of search results, assuming the next selected item is from the first set. Then the intermingler 206 determines a second new exposure percentage associated with items in the first format in the list of search results, assuming the next selected item is from the second set, at operation 446. The comparing of a first difference between the first new exposure percentage and the target exposure percentage with a second difference between the second new exposure percentage and the target exposure percentage occurs at operation 448. The result of the comparing is used, at operation 449, for selecting the next item for positioning in the list of search results, based on a result of the comparing. Specifically, in one example embodiment, the determination of whether to select the next item to be presented in the list of search results from the first set or from the second set is made such that the resulting exposure of the items in the first format is closer to the target exposure percentage.
As mentioned above, the target ratio and respective exposure percentages for items in different formats may be optimized based on monitored revenue associated with items in these different formats while the target ratio and exposure percentages are being enforced by the intermingler 206 of
As shown in
At operation 560, the revenue associated with the target ratio prior to adjustment (R.old) is compared to the revenue R.new associated with the adjusted target ratio. If the revenue has increased as a result of the adjustment (R.new is greater than R.old), the method 500 proceeds to operation 540 to further increase exposure of items in the first format. Prior to that, however, R.new is saved in R.old (such that R.new becomes the new R.old), and a new “K” may be set at operation 580. If, however, it is determined, at operation 560, that the revenue has not increased as a result of the adjustment (R.new is not greater than R.old), the method 500 proceeds to operation 592 to decrease exposure of items in the first format using a new “K” set at operation 590. R.new is saved in R.old (such that R.new becomes the new R.old), at operation 594. The method 500 may continue to adjust the target ratio periodically in order to optimise revenue derived from items in the first and second formats.
The example computer system 700 includes a processor 702 (e.g., a central processing unit (CPU), a graphics processing unit (GPU) or both), a main memory 704 and a static memory 706, which communicate with each other via a bus 708. The computer system 700 may further include a video display unit 710 (e.g., a liquid crystal display (LCD) or a cathode ray tube (CRT)). The computer system 700 also includes an alpha-numeric input device 712 (e.g., a keyboard), a user interface (UI) navigation device 714 (e.g., a cursor control device), a disk drive unit 716, a signal generation device 718 (e.g., a speaker) and a network interface device 720.
The disk drive unit 716 includes a machine-readable medium 722 on which is stored one or more sets of instructions and data structures (e.g., software) 724 embodying or utilized by any one or more of the methodologies or functions described herein. The instructions 724 may also reside, completely or at least partially, within the main memory 704 and/or within the processor 702 during execution thereof by the computer system 700, with the main memory 704 and the processor 702 also constituting machine-readable media.
The instructions 724 may further be transmitted or received over a network 726 via the network interface device 720 utilizing any one of a number of well-known transfer protocols (e.g., Hyper Text Transfer Protocol (HTTP)).
While the machine-readable medium 722 is shown in an example embodiment to be a single medium, the term “machine-readable medium” should be taken to include a single medium or multiple media (e.g., a centralized or distributed database, and/or associated caches and servers) that store the one or more sets of instructions. The term “machine-readable medium” shall also be taken to include any medium that is capable of storing and encoding a set of instructions for execution by the machine and that cause the machine to perform any one or more of the methodologies of embodiments of the present invention, or that is capable of storing and encoding data structures utilized by or associated with such a set of instructions. The term “machine-readable medium” shall accordingly be taken to include, but not be limited to, solid-state memories, optical and magnetic media. Such media may also include, without limitation, hard disks, floppy disks, flash memory cards, digital video disks, random access memory (RAMs), read only memory (ROMs), and the like.
The embodiments described herein may be implemented in an operating environment comprising software installed on a computer, in hardware, or in a combination of software and hardware.
Thus, a method and system for determining an order of presentation of the search results has been described. Although embodiments have been described with reference to specific example embodiments, it will be evident that various modifications and changes may be made to these embodiments without departing from the broader spirit and scope of the inventive subject matter. Accordingly, the specification and drawings are to be regarded in an illustrative rather than a restrictive sense. For example, while an embodiment has been described with reference to an on-line trading platform, a method and system may be implemented and utilized advantageously in the context of various other on-line platforms, as well as a stand-alone application.
Number | Name | Date | Kind |
---|---|---|---|
3573747 | Adams et al. | Apr 1971 | A |
3581072 | Nymeyer | May 1971 | A |
4412287 | Braddock, III | Oct 1983 | A |
4674044 | Kalmus et al. | Jun 1987 | A |
4677552 | Sibley, Jr. | Jun 1987 | A |
4789928 | Fujisaki | Dec 1988 | A |
4799156 | Shavit et al. | Jan 1989 | A |
4823265 | Nelson | Apr 1989 | A |
4864516 | Gaither et al. | Sep 1989 | A |
4903201 | Wagner | Feb 1990 | A |
5063507 | Lindsey et al. | Nov 1991 | A |
5077665 | Silverman et al. | Dec 1991 | A |
5101353 | Lupien et al. | Mar 1992 | A |
5136501 | Silverman et al. | Aug 1992 | A |
5168446 | Wiseman | Dec 1992 | A |
5205200 | Wright | Apr 1993 | A |
5243515 | Lee | Sep 1993 | A |
5258908 | Hartheimer et al. | Nov 1993 | A |
5280422 | Moe et al. | Jan 1994 | A |
5297031 | Gutterman et al. | Mar 1994 | A |
5297032 | Trojan et al. | Mar 1994 | A |
5305200 | Hartheimer et al. | Apr 1994 | A |
5325297 | Bird et al. | Jun 1994 | A |
5329589 | Fraser et al. | Jul 1994 | A |
5375055 | Togher et al. | Dec 1994 | A |
5394324 | Clearwater | Feb 1995 | A |
5426281 | Abecassis | Jun 1995 | A |
5485510 | Colbert | Jan 1996 | A |
5553145 | Micali | Sep 1996 | A |
5557728 | Garrett et al. | Sep 1996 | A |
5596944 | Massie | Jan 1997 | A |
5596994 | Bro | Jan 1997 | A |
5598557 | Doner et al. | Jan 1997 | A |
5640569 | Miller et al. | Jun 1997 | A |
5657389 | Houvener | Aug 1997 | A |
5664115 | Fraser | Sep 1997 | A |
5666524 | Kunkel et al. | Sep 1997 | A |
5689652 | Lupien et al. | Nov 1997 | A |
5694546 | Reisman | Dec 1997 | A |
5706457 | Dwyer et al. | Jan 1998 | A |
5710889 | Clark et al. | Jan 1998 | A |
5715314 | Payne et al. | Feb 1998 | A |
5715402 | Popolo | Feb 1998 | A |
5717989 | Tozzoli et al. | Feb 1998 | A |
5722418 | Bro | Mar 1998 | A |
5727165 | Ordish et al. | Mar 1998 | A |
5771291 | Newton et al. | Jun 1998 | A |
5771380 | Tanaka et al. | Jun 1998 | A |
5790790 | Smith et al. | Aug 1998 | A |
5794219 | Brown | Aug 1998 | A |
5799285 | Klingman | Aug 1998 | A |
5803500 | Mossberg | Sep 1998 | A |
5818914 | Fujisaki | Oct 1998 | A |
5826244 | Huberman | Oct 1998 | A |
5835896 | Fisher et al. | Nov 1998 | A |
5845265 | Woolston | Dec 1998 | A |
5845266 | Lupien et al. | Dec 1998 | A |
5850442 | Muftic | Dec 1998 | A |
5872848 | Romney et al. | Feb 1999 | A |
5873069 | Reuhl et al. | Feb 1999 | A |
5884056 | Steele | Mar 1999 | A |
5890138 | Godin et al. | Mar 1999 | A |
5905974 | Fraser et al. | May 1999 | A |
5905975 | Ausubel | May 1999 | A |
5922074 | Richard et al. | Jul 1999 | A |
5924072 | Havens | Jul 1999 | A |
5926794 | Fethe | Jul 1999 | A |
5974412 | Hazlehurst et al. | Oct 1999 | A |
5987440 | O'Neil et al. | Nov 1999 | A |
5991739 | Cupps et al. | Nov 1999 | A |
6023683 | Johnson et al. | Feb 2000 | A |
6035402 | Vaeth et al. | Mar 2000 | A |
6044363 | Mori et al. | Mar 2000 | A |
6047264 | Fisher et al. | Apr 2000 | A |
6055518 | Franklin et al. | Apr 2000 | A |
6058417 | Hess et al. | May 2000 | A |
6061448 | Smith et al. | May 2000 | A |
6073117 | Oyanagi et al. | Jun 2000 | A |
6085176 | Woolston | Jul 2000 | A |
6104815 | Alcorn et al. | Aug 2000 | A |
6119137 | Smith et al. | Sep 2000 | A |
6178408 | Copple et al. | Jan 2001 | B1 |
6192407 | Smith et al. | Feb 2001 | B1 |
6202051 | Woolston | Mar 2001 | B1 |
6243691 | Fisher et al. | Jun 2001 | B1 |
6415320 | Hess et al. | Jul 2002 | B1 |
6466918 | Spiegel et al. | Oct 2002 | B1 |
6466919 | Walker et al. | Oct 2002 | B1 |
6587838 | Esposito et al. | Jul 2003 | B1 |
6934690 | Van Horn et al. | Aug 2005 | B1 |
7212996 | Carnahan et al. | May 2007 | B1 |
7373317 | Kopelman et al. | May 2008 | B1 |
7428505 | Levy et al. | Sep 2008 | B1 |
8428996 | Grove et al. | Apr 2013 | B2 |
20010021924 | Ohno | Sep 2001 | A1 |
20020026369 | Miller et al. | Feb 2002 | A1 |
20020082932 | Chinnappan et al. | Jun 2002 | A1 |
20020184059 | Offutt, Jr. et al. | Dec 2002 | A1 |
20070255702 | Orme | Nov 2007 | A1 |
20080046336 | Mosleh | Feb 2008 | A1 |
20100070486 | Punaganti Venkata et al. | Mar 2010 | A1 |
20130018756 | Grove | Jan 2013 | A1 |
Number | Date | Country |
---|---|---|
2253543 | Mar 1997 | CA |
2658635 | Aug 1991 | FR |
11-007452 | Jan 1999 | JP |
19977005795 | Oct 1997 | KR |
20000054343 | Sep 2000 | KR |
9300266 | Feb 1993 | NL |
WO-9215174 | Sep 1992 | WO |
WO-9517711 | Jun 1995 | WO |
WO-9607149 | Mar 1996 | WO |
WO-9634356 | Oct 1996 | WO |
WO-9737315 | Oct 1997 | WO |
WO-9963461 | Dec 1999 | WO |
WO-0025218 | May 2000 | WO |
WO-0188796 | Nov 2001 | WO |
WO-2010141473 | Dec 2010 | WO |
Entry |
---|
Hammouda, “Efficient Phrase-Based Document Indexing for Web Document Clustering”, Oct. 2004, Published by: IEEE Transactions on Knowledge and data engineering, vol. 16, No. 10, pp. 1279-1297. |
“U.S. Appl. No. 10/023,583, Advisory Action mailed May 23, 2008”, 3 pgs. |
“U.S. Appl. No. 10/023,583, Final Office Action mailed Apr. 16, 2009”, 14 pgs. |
“U.S. Appl. No. 10/023,583, Final Office Action mailed Nov. 29, 2007”, 12 pgs. |
“U.S. Appl. No. 10/023,583, Non Final Office Action mailed Apr. 9, 2007”, 6 pgs. |
“U.S. Appl. No. 10/023,583, Non Final Office Action mailed Sep. 15, 2008”, 10 pgs. |
“U.S. Appl. No. 10/023,583, Non-Final Office Action mailed Jul. 8, 2010”, 12 pgs. |
“U.S. Appl. No. 10/023,583, Non-Final Office Action mailed Sep. 28, 2009”, 16 pgs. |
“U.S. Appl. No. 10/023,583, Non-Final Office Action mailed Sep. 15, 2008.”, 12 pgs. |
“U.S. Appl. No. 10/023,583, Pre-Appeal Brief Request filed May 28, 2008”, 5 pgs. |
“U.S. Appl. No. 10/023,583, Response filed Jan. 28, 2010 to Non Final Office Action mailed Sep. 28, 2009”, 20 pgs. |
“U.S. Appl. No. 10/023,583, Response filed Jan. 29, 2008 to Final Office Action mailed Nov. 29, 2007”, 19 pgs. |
“U.S. Appl. No. 10/023,583, Response filed Jul. 16, 2009 to Final Office Action mailed Apr. 16, 2009”, 15 pgs. |
“U.S. Appl. No. 10/023,583, Response filed Aug. 9, 2007 to Non-Final Office Action mailed Apr. 9, 2007”, 17 pgs. |
“U.S. Appl. No. 10/023,583, Response filed Nov. 8, 2010 to Non Final Office Action mailed Jul. 8, 2010”, 20 pgs. |
“U.S. Appl. No. 10/023,583, Response filed Dec. 15, 2008 to Non-Final Office Action mailed Sep. 15, 2008”, 20 pgs. |
“U.S. Appl. No. 10/023,583, Supplemental Preliminary Amendment filed Aug. 21, 2006”, 16 pgs. |
“Chinese Application Serial No. 02811759.X, First Office Action mailed Apr. 3, 2007”, 10 pgs. |
“Chinese Application Serial No. 02811759.X, Office Action mailed Jun. 6, 2008”, 5 pgs. |
“Chinese Application Serial No. 02811759.X, Office Action mailed Oct. 21, 2009”, 10 pgs. |
“Chinese ApplicationSerial No. 02811759.X, Office Action mailed on Feb. 27, 2009”, 3 pgs. |
“eDeal Marketplace Internet Site”, eDeal Services Corp., Edeal Auctions-InterActive Classifieds, (Jul. 12, 2002). |
“International Application Serial No. PCT/US02/04600, International Search Report mailed Oct. 2, 2002”, 9 pgs. |
“International Application Serial No. PCT/US10/036907, International Search Report and Written Opinion mailed Jul. 28, 2010”, 9 pgs. |
“International Application Serial No. PCT/US2010/036907 Search Report mailed Jul. 28, 2010”, 30 pgs. |
“InterShopZone, The Online Interactive Marketplace Internet Site”, Auctionweiser Enterprises, Inc., [Online]. Retrieved from the Internet: <URL: Http://www.Auctionweister.com/auction/index.asp>, (Jul. 12, 2002). |
“Introduction for online shopping: a shopping on Internet for first time (written in Japanese language)”, Mobile i, Softbank Publishing K.K., 6 (6), (Jun. 1, 2000), 109. |
“Japanese Application Serial No. 2003-504306, Final Office Action mailed Sep. 9, 2008”, 5 pgs. |
“Japanese Application Serial No. 2003-504306, Office Action mailed Jan. 15, 2008”, 10 pgs. |
“Korean Application Serial No. 10-2007-7029722, Office Action mailed Mar. 13, 2008”, 16 pgs. |
“Korean Application Serial No. 10-2007-7029722, Supplemental Appeal Brief filed Mar. 19, 2010”, 14 pgs. |
“Korean Application Serial No. 10-2009-7007814, Office Action mailed Jul. 15, 2009”, 9 pgs. |
“Korean Application Serial No. 2003-7016152 Trial Decision mailed Jul. 8, 2008”, 10 pgs. |
“Korean Application Serial No. 2007-7029722, Office Action mailed Mar. 7, 2009”, 16 pgs. |
“Korean Application Serial No. 2007-7029722, Office Action mailed Jun. 19, 2009”, 10 pgs. |
“Onsale Joins Fray as Online Shopping Picks Up Speed: Internet Booms”, Computer Reseller News, CMP Publications, Inc., USA, (Jun. 5, 1995), 1 pg. |
“Onsale: Onsale Brings Thrill of Auctions and Bargain Hunting Online; Unique Internet retail service debuts with week-long charity auction for The Computer Museum in Boston”, Business Wire, Dialog Web. 0489267 BW0022, (May 24, 1995), 3 pages. |
Baumann, G. W, “Personal Optimized Decision/Transaction Program”, IBM Technical Disclosure Bulletin (Jan. 1995), 83-84. |
Business Wire, “Mediappraise Receives National Award for Web-based Technology That Enables Companies to Solve Thorny HR Problem”, Business Wire, (Dec. 14, 1998), 1-2. |
Clemons, E, “Evaluating the prospects for alternative electronic securities”, Proceedings of ICIS 91: 12th International Conference on Information Systems, (Dec. 16-18, 1991), 53-61. |
Graham, I, “The Emergence of Linked Fish Markets in Europe”, Focus Theme, 1-3. |
Hammouda, et al., “Efficient Phrase-Based Document Indexing for Web Document Oustering in”, IEEE Transactions on Knowledge and Data Engineering, Oct. 2004, vol. 16, No. 10, [Online]. Retrieved from the Internet: <URL: http://watnow.uwaterloo.calpubhammouda/hammouda-ieee-tkde-oct04.pdf>, (Oct. 2004), pp. 1279-1296. |
Hauser, R, “Anonymous Delivery of Goods in Electronic Commerce”, IBM Technical Disclosure Bulletin, 39(3), (Mar. 1996), 363-366. |
Hess, C M, et al., “Computerized Loan Organization System: An Industry Case Study of the Electronic Markets Hypothesis”, MIS Quarterly, vol. 18(3), (Sep. 1994), 251-274. |
Jiro, M., et al., “Thorough guide for Net auction: Yahoo! Auction, eBay Japan (written in Japanese language)”, 1st Edition, Sotechsha (Publisher), (Jun. 1, 2000), 39-41. |
Klein, S, “Introduction to Electronic Auctions”, Focus Theme, 1-4. |
Lee, H G, “Aucnet: Electronic Intermediary for Used-Car Transactions”, Focus Theme, 1-5. |
Lee, H. G, “Electronic brokerage and electronic auction: the impact of IT on market structures”, Proceedings of the Twenty-Ninth Hawaii International Conference on System Sciences, vol. 4, (1996), 397-406. |
Malone, T., et al., “Electronic Markets and Electronic Hierarchies”, Communications of the ACM, 14(25), (Jun. 1987), 484-497. |
Mardesich, Jodi, “Site Offers Clearance for End-of-Life Products—Onsale Takes Auction Gavel Electronic”, Computer Reseller News, (Jul. 8, 1996), 2 pps. |
Massimb, Marcel, “Electronic Trading, Market Structure and Liquidity”, Financial Analysts Journal, 50(1), (Jan./Feb. 1994), 39-50. |
Meade, J., “Visual 360: A Performance Appraisal System That's ‘Fun’”, HR Magazine, Society for Human Resource Management., (Jul. 1999), 3 pgs. |
Neo, B S, “The implementation of an electronic market for pig trading in Singapore”, Journal of Strategic Information Systems; vol. 1(5), (Dec. 1992), 278-288. |
Nobuhiro, S., “What site is influential as a portal (Japanese w/translation)”, Nikkei Computer, Nikkei Business Publication Inc. (Publisher), 454, (Oct. 12, 1998), 98-99. |
Post, D L, et al., “Application of auctions as a pricing mechanism for the interchange of electric power”, IEEE Transactions on Power Systems, 10(3), (Aug. 1995), 1580-1584. |
Preist, Chris, et al., “Adaptive Agents in a Persistent Shout Double Auction”, International Conference on Information and Computation Economies, Proceedings of the first international conference on Information and computation economies, (1999), 11-18. |
Reck, M., “Formally Specifying an Automated Trade Execution System”, The Journal of Systems and Software, 1993, Elsevier Science Publishing, USA, (1993), 245-252. |
Reck, Martin, “Trading-Process Characteristics of Electronic Auctions”, Focus Theme, 1-7. |
Resnick, Paul, “Reputation systems”, Communications of the ACM, 43(12), (Dec. 2000), 45-48. |
Rockoff, T E, et al., “Design of an Internet-based system for remote Dutch auctions”, Internet Research: Electronic Networking Applications and Policy, vol. 5(4), (Jan. 1, 1995), 10-16. |
Schmid, B F, “The Development of Electronic Commerce”, EM—Electronic Markets, No. 9-10, (Oct. 1993), 2 pgs. |
Siegmann, Ken, “Nowhere to go but up”, PC Week; vol. 12(42), Ziff-Davis Publishing Company, (Oct. 23, 1995), 1-3. |
Takehiko, O., et al., “How to receive benefits in Auction: Yahoo! Auction—50 hints for sales and auctions”, Ascii Net J, Ascii Corp. (Publisher), 5, (Dec. 22, 2000), 2 pgs. |
Tjostheim, Ingvar, “A case study of an on-line auction for the World Wide Web”, Norwegian Computing Center (NR), 1-10. |
Turban, E, “Auctions and Bidding on the Internet: An Assessment”, Focus Theme, 1-5. |
Van Heck, E., et al., “Experiences with Electronic Auctions in the Dutch Flower Industry”, Focus Theme, Erasmus University, The Netherlands, 6 pgs. |
Warbelow, A, et al., “Aucnet: TV Auction Network System”, Harvard Business School Case/Study, HBVR#9-190-001, USA, (Jul. 1989), 1-15. |
Zwass, V., “Electronic Commerce: Structures and Issues”, International Journal of Electronic Commerce, Fall 1996, vol. 1, No. 1, (Fall 1996), 3-23. |
“U.S. Appl. No. 10/023,583, Final Office Action mailed Feb. 3, 2011”, 13 pgs. |
“U.S. Appl. No. 10/023,583, Non Final Office Action mailed Oct. 20, 2011”,14 pgs. |
“U.S. Appl. No. 10/023,583, Pre-Appeal Brief Request mailed Aug. 3, 2011”, 5 pgs. |
“International Application Serial No. PCT/US2010/036907, International Preliminary Report on Patentability mailed Dec. 15, 2011”, 8 pgs. |
“U.S. Appl. No. 10/023,583, Notice of Allowance mailed Jan. 25, 2013”, 9 pgs. |
“U.S. Appl. No. 13/621,092, Preliminary Amendment filed Mar. 7, 2013”, 10 pgs. |
“U.S. Appl. No. 13/621,092, Examiner Interview Summary mailed Sep. 17, 2013”, 3 pgs. |
“U.S. Appl. No. 13/621,092, Non Final Office Action mailed Jun. 14, 2013”, 17 pgs. |
“U.S. Appl. No. 13/621,092, to Non Final Office Action mailed Sep. 16, 2013”, 21 pgs. |
“U.S. Appl. No. 13/621,092, Notice of Allowance mailed Dec. 6, 2013”, 12 pgs. |
“European Application Serial No. 10783927.6, Office Action mailed Jan. 24, 2012”, 2 pgs. |
“European Application Serial No. 10783927.6, Response filed Jun. 8, 2012 to Office Action mailed Jan. 24, 2012”, 11 pgs. |
“U.S. Appl. No. 10/023,583 , Appeal Brief filed Aug. 21, 2012”, 28 pgs. |
“U.S. Appl. No. 10/023,583, Decision on Pre-Appeal Brief Request mailed Sep. 7, 2011”, 2 pgs. |
“U.S. Appl. No. 10/023,583, Notice of Allowance mailed Sep. 26, 2012”, 9 pgs. |
Number | Date | Country | |
---|---|---|---|
20100306205 A1 | Dec 2010 | US |