Methods and systems for assessing the quality of an item listing

Patent metadata

Field	Value
Publication number	US-9412127-B2
Application number	US-47602809-A
Country	US
Kind code	B2
Filing date	Jun 1, 2009
Priority date	Apr 8, 2009
Publication date	Aug 9, 2016
Grant date	Aug 9, 2016

Abstract

Methods and systems for assessing the quality of an item listing are described. In an example embodiment, a listing quality score for an item listing is derived as a weighted sum of first and second parts. The first part represents a predicted score based on a comparison of item attributes for the item listing that are known at listing time, with item attributes of similar item listings that have historical data available for assessing their actual performance. The second part is based on one or more observed demand metrics representing actual historical performance of the item listing. The weighting factor is derived, such that over time, the emphasis shifts from the predicted to the observed score.

First claim

What is claimed is:

1. A computer-implemented method comprising:
processing a query to identify item listings that satisfy the query, each item listing associated with at least one item being offered for sale;
assigning a score to each item listing that satisfies the query, the score i) representing a measure of the likelihood that an item listing, if presented in a search results page, will result in a transaction being concluded, and ii) derived as a weighted sum of first and second parts, the first part representing a predicted score based on item attributes of the item listing known at listing time, and the second part based on an observed demand metric derived from historical performance data of the item listing, the predicted score being derived based on an analysis of an item attribute specifying an offering price for an item offered via an item listing satisfying the query, the analysis including a comparison of the offering price for the item offered via the item listing satisfying the query with historical data indicating prices at which items determined to be similar to the item offered via the item listing satisfying the query have sold; and
presenting the item listings that satisfy the query in the search results page displayed in a user interface of a client device, each item listing positioned in the search results page based on the score assigned to the item listing.

2. The computer-implemented method of claim 1 , wherein the predicted score based on item attributes known at listing time is derived by comparing item attributes of an item listing satisfying the query with item attributes of similar item listings that have previously concluded transactions.

3. The computer-implemented method of claim 1 , wherein the observed metrics representing actual historical performance of the item listing are based on data generated after the listing time of the item listing satisfying the query.

4. The computer-implemented method of claim 1 , wherein one of the observed metrics representing actual historical performance of the item listing is calculated as a ratio of the number of transactions concluded per the number of search impressions for the item listing.

5. The computer-implemented method of claim 1 , wherein one of the observed metrics representing actual historical performance of the item listing is calculated as a ratio of transactions concluded per duration of time since the item listing was first listed.

6. The computer-implemented method of claim 1 , wherein one of the observed metrics representing actual historical performance of the item listing is calculated as a ratio of the number of times an item listing is selected for viewing per the number of search impressions for the item listing.

7. The computer-implemented method of claim 1 , wherein one of the observed metrics representing actual historical performance of the item listing is calculated as a ratio of the number of times an item listing is added to a watch list per the number of search impressions for the item listing.

8. The computer-implemented method of claim 1 , wherein the first part representing the predicted score is weighted with a weighting factor that is a function of the number of search impressions for the item listing such that the weighting factor for the first part decreases as the number of search impressions for the item listing increases.

9. The computer-implemented method of claim 1 , wherein the second part representing observed metrics is weighted with a weighting factor that is a function of the number of search impressions for the item listing such that the weighting factor for the second part increases as the number of search impressions for the item listing increases.

10. The computer-implemented method of claim 1 , wherein presenting the item listings that satisfy the query in the search results page, each item listing positioned in the search results page based on the score assigned to the item listing includes presenting the item listings as a list such that the item listing assigned the highest score is presented at the top of the list.

11. A server comprising:
a search engine module to process a query to identify item listings that satisfy the query, each item listing associated with at least one item being offered for sale;
a ranking score assignment module to assign a score to each item listing that satisfies the query, the score i) representing a measure of the likelihood that an item listing, if presented in a search results page, will result in a transaction being concluded, and ii) derived as a weighted sum of first and second parts, the first part representing a predicted score based on item attributes of the item listing known at listing time, and the second part based on observed metrics representing actual historical performance of the item listing, the predicted score being derived based on an analysis of an item attribute specifying an offering price for an item offered via an item listing satisfying the query, the analysis including a comparison of the offering price for the item offered via the item listing satisfying the query with historical data indicating prices at which items determined to be similar to the item offered via the item listing satisfying the query have sold; and
a presentation module to present the item listings that satisfy the query in the search results page displayed in a user interface of a client device, each item listing positioned in the search results page based on the score assigned to the item listing, wherein said modules are implemented using one or more hardware-based processors.

12. The server of claim 11 wherein the predicted score based on item attributes known at listing time is derived by comparing item attributes of an item listing satisfying the query with item attributes of similar item listings that, when presented in a search results page, have resulted in transactions.

13. The server of claim 11 , wherein the observed metrics representing actual historical performance of the item listing are based on data generated after the listing time of the item listing satisfying the query.

14. The server of claim 11 , wherein one of the observed metrics representing actual historical performance of the item listing is calculated as a ratio of the number of transactions concluded per the number of search impressions for the item listing.

15. The server of claim 11 , wherein one of the observed metrics representing actual historical performance of the item listing is calculated as a ratio of transactions concluded per duration of time since the item listing was first listed.

16. The server of claim 11 , wherein one of the observed metrics representing actual historical performance of the item listing is calculated as a ratio of the number of times an item listing is selected for viewing per the number of search impressions for the item listing.

17. The server of claim 11 , wherein one of the observed metrics representing actual historical performance of the item listing is calculated as a ratio of the number of times an item listing is added to a watch list per the number of search impressions for the item listing.

18. The server of claim 11 , wherein the first part representing predicted score is weighted with a weighting factor that is a function of the number of search impressions for the item listing such that the weighting factor for the first part decreases as the number of search impressions for the item listing increases.

19. The server of claim 11 , wherein the second part representing obs

Assignees

• Dumon Olivier G
• Mcdonald Ryan
• Rehman Muhammad Faisal
• Ghatare Sanjay Pundlkrao
• Yuan Ted Tao
• Ebay Inc

Inventors

• Dumon Olivier G
• Mcdonald Ryan
• Rehman Muhammad Faisal
• Ghatare Sanjay Pundlkrao
• Yuan Ted Tao

Classifications

• G06Q30/0629 Primary

  by pre-processing results, e.g. ranking or ordering results · CPC title

• G06F17/30979

  Physics · mapped topic

• G06Q30/0256

  User search · CPC title

• G06Q30/0631

  Recommending goods or services · CPC title

• G06Q30/0623

  by investigating goods or services · CPC title