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A method based on Big data to identify the priority of contacts

IP.com Disclosure Number: IPCOM000243446D
Publication Date: 2015-Sep-22
Document File: 2 page(s) / 66K

Publishing Venue

The IP.com Prior Art Database

Abstract

The patent is mainly to analyze the following data: 1. All kinds of social software group and private chat logs 2. Mobile message record The patent used analysis model is as follows: Select the all chat records of a recent period, build a model, obtain the response time(marked as T). 1) The average response time of all chat records(marked as A) 2) The average response time uder the samples scenario(marked as B), Scenario as follows: a. The particular words that the contacts said in the chat history(As an example in Chinese, such as. The particular words can be given by all sorts of rules engine). b. Group chat, @ by each other c. After a period of time did not chat(such as 0.5h), the response time after the contacts said the fist sentence.

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A method  based on Big data to identify the priority of contacts

We make contact with others by using various social software every day, but there is still no good method to differentiate the importance of the contacts, except for marking one as an important person manually, and then we can't get the priority of the contacts. However, marking manually is not dynamic enough, and it can't differentiate priority between contacts quantitatively either. In the reality, the degree of our commitment is different to different people, which is often reflected on our response time to the communication. And the more quickly we respond to, the higher priority the contact is to us. For example, a stranger and your boss text to you on the same time, you would reply your boss first.

The patent is mainly to analyze the following data:

1. All kinds of social software group and private chat logs

2. Mobile message record

The patent used analysis model is as follows:

Select the all chat records of a recent period, build a model, obtain the response time(marked as T).

1) The average response time of all chat records(marked as A)

2) The average response time uder the samples scenario(marked as B), Scenario as follows:

a. The particular words that the contacts said in the chat history(As an example in Chinese, such as ,,,好不,行不,怎么.The particularwords can be given by all sorts of rules engine).


b. Group chat, @ by each other

c. After a period of time did not chat(such as 0.5h), the response time after the contacts said the fist sentence .

For the above two scenarios, we can use the weighted arithmetic mean to calculate the T, and statistics the totalnumber of chat during this period(marked as N). Is exist a positive integer(marked as m), Make different N in [3^(m - 1), 3^m) range, that said t...