Method and system for searching location based information on a mobile device

• US 20040162830A1
• Filed: 02/12/2004
• Published: 08/19/2004
• Est. Priority Date: 02/18/2003
• Status: Abandoned Application

• Current Assignee: Sameer Yami, Sanika Shirwadkar
• Original Assignee: Sameer Yami, Sanika Shirwadkar
• Inventors: Yami, Sameer, Shirwadkar, Sanika
• Application Number:
  US10/777,237
• Publication Number:
  US 20040162830A1
• Time in Patent Office: Days
• US Class Current: 707/10
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 16/9537 Spatial or temporal dependent retrieval, e.g. spatiotemporal queries

Abstract

A method and system for searching location based information on a mobile device is disclosed. The method and system provides for location based resource information retrieval, processing retrieved resource information based on probability of finding them in the given location, a Peer to Peer recommendation system that combines other user'"'"'s real time recommendations with archived recommendations, a virtual social network that creates a dynamic network consisting of user and user'"'"'s acquaintances for refining the resource information, providing a refined set of search results, by considering user'"'"'s privacy choices and personal preferences.

Claims

1. A method comprising:

a retrieval method for resource information based on location, wherein a a resource may be, but is not limited to a product, a product category, a person, a tourist place, an organization, geographic location or other variations;

a virtual social network filter for refining the resource information;

a method for processing and displaying retrieved resource information based on factors such as probability assigned to the resource, whereby a user can make informed location specific decisions; and

a method for creating dynamic location based peer networks to provide resource recommendations and opinions.

2. The method of claim 1, wherein the resource information is pre-fetched and updated periodically from sources such as Internet web pages, organizations'"'"' Web Services, manual entries, etc.

3. The method of claim 1, wherein numeric probabilities are assigned to the resource information and then periodically updated depending on factors such as resource'"'"'s availability in the given location.

4. The method of claim 3, wherein the search results are sorted and displayed based on resource'"'"'s numeric probability in the given location.

5. The method of claim 1, wherein the said recommendations may be provided live, or with values stored earlier by other mobile device users which are in user'"'"'s location based peer network.

6. The method of claim 5, wherein the said recommendations combine other user'"'"'s real time recommendations with archived recommendations.

7. The method of claim 5, wherein some reward may be provided to the user providing live recommendation. The reward is not limited to a point system, virtual currency, virtual credit, actual credit, actual currency or any other similar system.

8. The method of claim 1 wherein the said recommendations are combined with the probabilities assigned to the resources whereby the user is provided with a sorted set of results with the first result being most available and popular in the current location, and is based on user'"'"'s preferences and user specified interests.

9. The method of claim 1, wherein the said recommendation system checks user'"'"'s privacy preferences before retrieving/providing recommendations from or to a user.

10. The method of claim 1, wherein the said virtual social network is a virtual network comprising of user, users'"'"' trusted acquaintances, users with similar interests and in turn their trusted acquaintances.

11. The method of claim 10, wherein based on user'"'"'s choice, the social network can be formed by the user or can be selected by a computer program so as to reflect the user profile and user'"'"'s current and archived queries'"'"' context.

12. The method of claim 10, wherein trust is defined as a quantitative value that is an aggregation of user'"'"'s past interaction experience with that particular acquaintance.

13. The method of claim 12, wherein user can specify trust to be limited to certain resource categories and certain trust value range.

14. The method of claim 12, wherein users with high trust level of trust and having high level of expertise on the resource'"'"'s subject matter are chosen to form the dynamic social network that filters the search results by providing an opinion about the resource.

15. The method of claim 1, wherein resource images are used to assist users to narrow down results with the means of visualization.

16. The method of claim 2, wherein the web pages are classified to indicate the opinion expressed by the web page.

17. The method of claim 15, wherein the opinion is obtained by parsing the web page to establish a correlation between a resource and the opinion expressed.

18. The method of claim 16, wherein the opinion obtained and the numeric weights assigned to web page classification are recalculated and re-classified based on the social network opinion.

19. The method of claim 1, where the resource is identified as location specific or one with global relevance and then the dynamic peer networks/social networks are formed.

20. The method of claim 1, where both the virtual social network and the dynamic Location based peer group work as decision support system for a particular resource.