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A new method to list mobilephone numbers

IP.com Disclosure Number: IPCOM000250366D
Publication Date: 2017-Jul-06
Document File: 5 page(s) / 98K

Publishing Venue

The IP.com Prior Art Database

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A new method to list mobilephone numbers

Abstract Disclosed is a method of designing a score system for each phone number. And this score is related to the location, time and weather, etc.,. User can manually initialize the score or just use the default setting. In addition, a new module is introduced to optimize the score for each number based on the call history information and the current location, time and weather conditions, then to re-sort the list by this score.

Description Currently, the users often find a phone number which is at the bottom of the list of dialed phone numbers and they have to slide the screen up and up and then finally found the right number, it is not convenient. For example: A weekly meeting number, when you want to find it at next meeting time, it may already be buried under many of other numbers, furthermore, it may be similar with an another weekly meeting number, so, it is possible to choose the wrong number to call back even you slide up many times. Monday,morning, in the office, will have a weekly meeting with USA, the list is like this:

It is hard to find the right number 'weekly meeting USA' . -:(. Our idea includesa. Design a score for each number, this score is related to the location, time and weather, etc., user can manually initialize the score or just use the default setting. b. Add a new module which can optimize the score for each number based on the call history information and the current location, time and weather conditions, then to re-sort the list by this score. The details contains a. Each number will have a score which is related to some items like location, time and weather conditions, etc. Currently, those items can be obtained easily through the smart phone. When a user is calling a number, the items(location, time, weather, etc.) and the number can be saved as history information which can be analyzed before the next calling occurred. b. Add a module M in the mobile phone which will analyze those call history information including the number, location, time, and weather, etc., to calculate the score for each number, then to sort all of the numbers on the score in descending order, finally, the number which most likely to be used always is at the top of the list.

For conveniently describing, we just select 3 items: location, time and weather and a calculation rule in the following sample: 1)Initializing the rate(weight) for each item item1(location):rate10 item2(time):rate20 item3(weather):rate30 rate10 + rate20 + rate30 = 100% User can manually initialize the rate for each item or just use the default setting. Default settings: rate10 = 20%, rate20 = 20%, rate30 = 60% These rates can be optimized according to some rules, for example, increasing the maximal rate while the recommendation is successful, otherwise decreasing it, etc. 2)Organizing the call history information for each number, as follows: number: item1: (location1, location1_v(=0 or 1), rate11), (location2, location2_v(=0 or...