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Short message identification method and equipment

An identification method and a technology for identifying equipment, which are applied in wireless communication, electrical components, safety devices, etc., and can solve problems such as irretrievable losses, unacceptable reception, and high risks for users

Inactive Publication Date: 2011-05-18
HUAWEI TECH CO LTD +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

When it is judged as a spam message, the server side will directly put the message into the spam message database, and the mobile terminal will not be able to receive the message
[0008] However, whether the message is a spam message varies from person to person. Therefore, once the message is judged as a spam message, the user will not be able to receive this message
Therefore, once the classifier makes a wrong judgment, the user will not be able to recover the loss, and there is a high risk in such SMS filtering

Method used

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  • Short message identification method and equipment

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0029] see figure 1 , which is a flow chart of Embodiment 1 of the method of the present invention.

[0030] S101: The mobile phone receives the short message sent by the server and the probability feature vector of the short message.

[0031] The probability feature vector of the short message is calculated by the server. In order to enable those skilled in the art to better understand and implement the present invention, the calculation method of the probability feature vector will be introduced in detail below.

[0032] First, the pre-training process on the server side is introduced.

[0033] The original text message model of each category is counted from the marked text message set.

[0034] The original short message model refers to the word frequency distribution vector of a category short message in the word feature space, using (N k (t 1 ),...,N k (t i ),...,N k (t n )), 0≤i≤n. said. Among them, n refers to the number of all words in a vocabulary, and k is t...

example 2

[0061] For example, if there are 5 samples with a1 in the range of (0.4, 0.5] in the training samples, and the total number of training samples is 14, then the probability of P(a1|normal SMS) (0.4

[0062] For the convenience of description, Table 1 only shows P(a 1 |Normal SMS) calculation method, according to the same calculation method can be calculated P(a 2 |Normal SMS), P(a 3 |Normal SMS), P(a 4 |Normal SMS) and P(a 5 |Normal SMS). Then the first generation probability can be obtained by multiplying these probabilities.

[0063] Similarly, the second generation probability can be calculated.

[0064] Then calculate the first joint distribution probability P ...

Embodiment 2

[0082] see figure 2 , which is a flow chart of the second embodiment of the method of the present invention.

[0083] The difference between this embodiment and the method embodiment 1 is that the interaction between the user and the mobile phone is added, and the short message model is updated through the user's feedback.

[0084] S201-S203 are the same as S101-S103 in the first method embodiment, and will not be repeated here.

[0085] S204: The mobile phone presents the identification result of the short message, that is, whether the short message is a normal short message or a spam short message, to the user.

[0086] For example: the display screen of the mobile phone will display the prompt of "received spam text message" or "received normal text message".

[0087] S205: The mobile phone receives a judgment result fed back by the user according to the recognition result, the judgment result being that the short message is a normal short message or a spam short message...

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Abstract

The invention provides a short message identification method and short message identification equipment. The method comprises the following steps of: receiving a short message and a probability characteristic vector of the short message, which are sent by a server; respectively calculating a first generating probability of the short message under a normal short message model and a second generating probability of the short message under a spam message model by utilizing the probability characteristic vector; obtaining a first joint distribution probability through the first generating probability and a normal message priori probability, and obtaining a second joint distribution probability through the second generating probability and a spam message priori probability; and when the first joint distribution probability is more than or equal to the second joint distribution probability, identifying the short message as a normal message, otherwise, identifying the short message as a spammessage. Once a terminal falsely judges a normal message as a spam message, a user still can retrieve the short message from a trash; therefore, the risk of falsely identifying spam messages is reduced. The probability characteristic vector is calculated by the server and is sent to the terminal, so the requirement on computing power of the terminal is reduced.

Description

technical field [0001] The invention relates to the technical field of mobile communication, in particular to a short message identification method and device. Background technique [0002] From a technical point of view, the identification of spam text messages needs to solve two core problems: [0003] The first personalization: how to use the least labeled samples to adapt to the personalized needs of users. [0004] Actual research has found that people's cognition of garbage is not consistent, and some information may be garbage to some people, while it may be non-garbage to others. For example, some people regard mobile phone text messages such as weather forecast, financial information, and news bulletins as garbage, while others urgently need them. Therefore, different filters should be designed according to individual needs, which is personalized filtering. [0005] Second Accuracy: The primary requirement for information filtering is high accuracy. However, the...

Claims

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Application Information

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IPC IPC(8): H04W4/14H04W12/00H04W12/128
Inventor 徐蔚然王占一刘东鑫方琦
Owner HUAWEI TECH CO LTD
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