Intelligent shopping search system

• US 20090037292A1
• Filed: 07/30/2007
• Published: 02/05/2009
• Est. Priority Date: 07/30/2007
• Status: Abandoned Application

• Current Assignee: NEO Notion Incorporated
• Original Assignee: NEO Notion Incorporated
• Inventors: Panjwani, Dileep Kumar
• Application Number:
  US11/881,859
• Publication Number:
  US 20090037292A1
• Time in Patent Office: Days
• US Class Current: 705/27
• CPC Class Codes: G06Q 30/06 Buying, selling or leasing transactions
• CPC Class Codes: G06Q 30/0629 for generating comparisons
• CPC Class Codes: G06Q 30/0643 Graphical representation of items or shoppers

Abstract

This invention provides a method of building an intelligent electronic shopping search system that helps a customer search and shop items which have the best match for him/her using a programmed computer, CD-ROM, television, Internet or other electronic medium such as video. The method comprises receiving personal information including body characteristics, personal preferences and style from the customer; making the customer selects the item he wants to shop or search; using expert and fashion knowledge rules which contain information of what works best for people along with his personal preferences to find the items in the descending order of their personal scores for the customer; and presenting the shopping search items to the customer in the descending order of their personal scores, such that the items with higher personal score come before the items with lower scores.

Claims

1. A method of an electronic shopping search that helps a customer search and shop items which match best for him/her using a programmed computer, cell phone, CD-ROM, television, Internet or any other electronic medium, comprising:

receiving personal information from a customer;

receiving item type to shop from the customer;

using the expert and fashion knowledge about what will be the best match for the customer along with his preferences to find the items in the descending order of the personal scores for the customer; and

outputting plurality of items from the database of items such that the items with the higher personal scores are retrieved and displayed before the items with the lower personal scores.

2. The method defined in claim 1, wherein the shopping search system helps customers search and shop items over the Internet, the method further comprising using fashion knowledge about what looks good from fashion point of view for customers with different body characteristics to search fashion items such that the items which will good for the customers are outputted first.

3. The method defined in claim 1, wherein the shopping search system helps customers search and shop items over the Internet, the method further comprising:

including fashion knowledge about what looks good (physical attractiveness) for different body types and personal styles of customers, and

making physical attractiveness as one of the key component for the personal score of fashion items such that the items which will look good from fashion point of view for the customer will get higher scores.

4. The method defined in claim 1, wherein the shopping search system helps customers search and shop items over the Internet, the method further comprising:

using fashion trends knowledge about people of various personal styles to find what will be fashionable items for the customer; and

continuously updating the fashion trend knowledge as it changes with time.

5. The method defined in claim 1, wherein the shopping search system helps customers search and shop items over the Internet, the method further comprising:

including knowledge about fashion trends for different personal styles of customers;

making fashion trend as one of the key component of the personal score for the fashion items such that the items which are in trend will get higher scores for the customer who care for such trends; and

continuously updating the fashion trend knowledge rules as this information changes with time.

6. The method defined in claim 1, wherein the shopping search system helps customers search and shop items over the Internet, the method further comprising using expert knowledge about the benefits, quality, and side effects of the item materials, ingredient, and components for people with different body characteristics and problems to find the items with maximum benefits, higher quality and low side effect for the customer.

7. The method defined in claim 1, wherein the shopping search system helps customers search and shop items over the Internet, the method further comprising:

including expert knowledge rules in the knowledge store about the benefits, quality, and side effects of the item materials and ingredient for people with different body characteristics and problems; and

making the benefits, quality, and side effects of the item ingredients and materials as one of the key component for the personal score of search items such that the items with maximum benefits, higher quality, and fewer side effects will get higher scores

8. The method defined in claim 1, wherein the shopping search system helps customers search and shop items over the Internet, the method further comprising using market price of the components used by an item to estimate the total market value of the item and helping the customer find items where the price of the item is lower or similar to the market price of the item.

9. The method defined in claim 1, wherein the shopping search system helps customers search and shop items over the Internet, the method further comprising:

including market price of ingredients and components of shopping items;

including expert knowledge about evaluating the market price of items using the market price of its components such as diamonds and gems; and

making the value of items (price vs market value) as one of the key component for the personal score of search items such that the items whose price is lower or same as the market value of items get higher scores.

10. The method defined in claim 1, wherein the shopping search system helps customers search and shop items over the Internet, the method further comprising including customer ratings, editorial ratings, and expert ratings as components of the personal score for the customer such that the items with higher ratings get higher scores

11. The method defined in claim 1, wherein the shopping search system helps customers search and shop items over the Internet, the method further comprising including knowledge about the quality, performance, and other attributes of brands for shopping items and using this knowledge to search items which have the best match for the customer

12. The method defined in claim 1, wherein the shopping search system helps customers search and shop items over the Internet, the method further comprising including reliability and quality of products based on the tests done by certified authorities and experience of real users into the personal score for items for the customer such that the items with the higher reliability and quality get higher scores

13. The method defined in claim 1, wherein the shopping search system continuously learns customer preferences, the method further comprising:

allowing user to select likeness or dislike-ness of an item from search result;

showing user various attributes of a liked item and allowing him to select the attributes that he liked about the item, and storing these preferences in the profile for the user as liked attributes of the item;

showing user various attributes of a disliked item and allowing him to select the attributes that he disliked about the item, and storing these preferences in the profile for the user as the disliked attributes of the item;

14. The method defined in claim 1, wherein the shopping search system continuously learns customer preferences and assigns a personal score to items, the method further comprising:

including user preferences in the personal score for items such that the items which meet user preference criteria get higher scores;

including the liked attributes in the personal score such that the items which have liked attributes get higher scores;

including the disliked attributes in the personal score such that the items which have disliked attributes get very low scores;

15. The method defined in claim 1, wherein the shopping search system shows the items with the higher utility first for the customer;

the method further comprising;

selecting the most suitable matching item types for a given item;

including matching knowledge rules for these item types such that the selected item has good match with these item types;

making the matching analysis as one of the key component for the personal score of the matching search items such that the items with higher matching attributes will get higher scores

displaying matching items with high personal score along with the selected search item such that the personal score of matching items includes matching analysis as well as other analysis

16. The method defined in claim 1, wherein the shopping search system shows the items with the higher utility first for the customer, the method further comprising:

using knowledge store to find the attributes which are good for the customer and their degree of goodness;

using knowledge store to find attributes which are bad for the customer and their degree of badness;

building ranked combination of attributes such that the combination with better match for the customer are ranked higher

using the ranked combinations of attributes to retrieve items from the database such that the item with the higher ranked combinations of attributes are retrieved before the items with lower ranked combinations of attributes

sorting retrieved items in the descending order of personal score

17. A method of continuously learning customer preferences and using them to improve the quality of search results of a shopping search system that helps customers search and shop items over the Internet using a programmed computer, CD-ROM, television, Internet or other electronic medium such as video, comprising:

allowing user to select likeness or dislike-ness of an item from search results displayed by the shopping search system;

displaying user various attributes of a liked item and allowing him to select the attributes that he liked about the item, and storing these preferences in the profile for the user as liked attributes of the item;

displaying user various attributes of a disliked item and allowing him to select the attributes that he disliked about the item, and storing these preferences in the profile for the user as the disliked attributes of the item;

including the liked attributes in the future searches for similar items such that the items which have liked attributes show up in the top results;

including the disliked attributes in the search for similar items such that the items which have disliked attributes show up last.

18. A method of Internet shopping system that helps a customer shop items which are best match for him/her using a programmed computer, cell phone, CD-ROM, television, Internet or any other electronic medium, comprising:

receiving personal information from a customer;

receiving item type to shop from the customer;

using the expert and fashion knowledge about what will be the best match for the customer along with his preferences to find the items in the descending order of the personal scores for the customer;

outputting plurality of items from the database of items such that the items with the higher personal scores are retrieved and displayed before the items with the lower personal scores; and

receiving item selection and order processing information from the customer;

processing the order information for the selected item

19. A method of an electronic shopping search that helps a customer search and shop items which match best for his friend using a programmed computer, cell phone, CD-ROM, television, Internet or any other electronic medium, comprising:

receiving personal information from a customer about his friend;

receiving item type to shop from the customer;

using the expert and fashion knowledge about what will be the best match for the friend along with his preferences to find the items in the descending order of the personal scores for the customer; and

outputting plurality of items from the database of items such that the items with the higher personal scores are retrieved and displayed before the items with the lower personal scores.

20. The method defined in claim 19, wherein the shopping search system helps customers search and shop items over the Internet for his friend, the method further comprising:

sending request to share personal information with a friend for the purpose of shopping for the friend; and

the friend approving the request to share personal information; and

using the shared personal information to shop for the friend

21. The method defined in claim 19, wherein the shopping search system helps customers search and shop items over the Internet for his friend, the method further comprising:

receiving request to share personal information from a friend for the purpose of shopping for the friend; and

approving the friend'"'"'s request to share personal information; and

using the shared personal information to shop for the friend