WO2015070690A1

WO2015070690A1 - Method and system for processing instant messaging messages

Info

Publication number: WO2015070690A1
Application number: PCT/CN2014/089000
Authority: WO
Inventors: Wenbin He
Original assignee: Tencent Technology (Shenzhen) Company Limited
Priority date: 2013-11-15
Filing date: 2014-10-21
Publication date: 2015-05-21
Also published as: CN104639420B; CN104639420A

Abstract

Various examples provide a method and a system for processing instant messaging (IM) messages. An IM chat window is presented. A text message outputted to the IM chat window is received, and processed through semantic analysis to determine whether the text message includes a pre-defined target feature. Push content corresponding to the target feature is obtained and outputted to the IM chat window.

Description

METHOD AND SYSTEM FOR PROCESSING INSTANT MESSAGING MESSAGES

Related documents

The present disclosure claims priority of Chinese patent application No. 201310572317.8 titled “Method and system for processing instant messaging messages” and filed on November 15, 2013 with the Patent Office of the People’s Republic of China, the disclosure of which is incorporated by reference.

Technical Field

The present disclosure relates to human-machine interactions techniques, and particularly to a method and a system for processing instant messaging (IM) messages.

Background

Instant messaging is a set of communication technologies used for text-based communication between two or more participants over the Internet or other types of networks. Short messages are typically transmitted bi-directionally between two parties, when each user chooses to complete a thought and select "send" . IM allows effective and efficient communication, allowing immediate receipt of acknowledgment or reply.

Summary

Various examples of the present disclosure provide a method and a system for processing IM messages, can provide users with contents the users may be interested in by analyzing IM messages of the users.

Various examples provide a method for processing IM messages which may include:

presenting an IM chat window；

receiving a text message fed into the IM chat window；

performing semantic analysis on the text message, judging whether the text message includes a target feature, and obtaining push content corresponding to the target feature if the text message includes the target feature； and

outputting the push content to the IM chat window.

Various examples provide a system for processing IM messages which may include a processor and a memory. The memory stores a series of computer-readable instructions executable by the processor to perform actions of:

presenting an IM chat window；

receiving a text message fed into the IM chat window；

outputting the push content to the IM chat window.

According to various examples, IM tools can perform semantic analysis on texts inputted by users to automatically identify intentions of the users, and provide the users with push contents related to the intentions of the users.

Brief Description of the Drawings

Features of the present disclosure are illustrated by way of example and not limited in the following figures, in which like numerals indicate like elements, in which:

Fig. 1 is a schematic diagram illustrating a communication system in accordance with examples of the present disclosure；

Fig. 2 is a schematic diagram illustrating an example of a computer；

Fig. 3 is a flowchart illustrating a method for processing IM messages in accordance with examples of the present disclosure；

Fig. 4 is a schematic diagram illustrating information presented in an IM chat window in accordance with examples of the present disclosure；

Fig. 5 is a schematic diagram illustrating an IM chat window presenting push content obtained from logic calculations in accordance with examples of the present disclosure；

Fig. 6 is a schematic diagram illustrating an IM chat window presenting push content obtained by searching in a database in accordance with examples of the present disclosure；

Fig. 7 is a schematic diagram illustrating modules of a system for processing IM messages in accordance with examples of the present disclosure.

Detailed Descriptions

For simplicity and illustrative purposes, the present disclosure is described by referring mainly to an example thereof. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present disclosure. It will be readily apparent however, that the present disclosure may be practiced without limitation to these specific details. In other instances, some methods and structures have not been described in detail so as not to unnecessarily obscure the present disclosure. As used herein, the term “includes” means includes but not limited to, the term “including” means including but not limited to. The term “based on” means based at least in part on. Quantities of an element, unless specifically mentioned, may be one or a plurality of, or at least one.

Fig. 1 is a schematic diagram illustrating a communication system in accordance with an example of the present disclosure. As shown in Fig. 1, the communication system includes at least a server 10, a communication network 20 and user terminal devices. The user terminal devices may be a personal computer 30, a mobile phone 40, a tablet computer 50, or other mobile Internet devices (MID) , e.g. , e-book reading devices, portable game consoles and the like that are capable of accessing the Internet via various wireless communications techniques. The user terminal devices may implement the method for processing IM messages of various examples of the present disclosure.

In an example, the user terminal device may be a computing device that may execute methods and software systems of various examples of the present disclosure. In an example, a computer executing methods and software systems of the present disclosure may be as shown in Fig. 2. As shown in Fig. 2, computer 200 may be a computing device capable of executing a method and software system of the present disclosure. The computer 200 may, for example, be a device such as a personal desktop computer or a portable device, such as a laptop computer, a tablet computer, a cellular telephone, or a smart phone. The computer 200 may also be a server that connects to the above devices locally or via a network.

The computer 200 may vary in terms of capabilities or features. Claimed subject matter is intended to cover a wide range of potential variations. For example, the computer 200 may include a keypad/keyboard 256. It may also comprise a display 254, such as a liquid crystal display (LCD) , or a display with a high degree of functionality, such as a touch-sensitive color 2D or 3D display. In contrast, however, as another example, a web-enabled computer 200 may include one or more physical or virtual keyboards, and mass storage medium 230.

The computer 200 may also include or may execute a variety of operating systems 241, including an operating system, such as a Windows TM or Linux TM, or a mobile operating system, such as iota, Android TM, or Windows Mobile TM. The computer 200 may include or may execute a variety of possible applications 242, such as an instant messaging application 245.

Further, the computer 200 may include one or more non-transitory processor-readable storage media 230 and one or more processors 222 in communication with the non-transitory processor-readable storage media 230. For example, the non-transitory processor-readable storage media 230 may be a RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of non-transitory storage medium known in the art. The one or more non-transitory processor-readable storage media 230 may store a series of instructions, or units and/or modules that comprise the series of instructions, for conducting operations described in the present disclosure. The one or more processors may be configured to execute the series of instructions and perform the operations in examples of the present application.

Fig. 3 is a flowchart illustrating a method for processing IM messages in accordance with examples of the present disclosure. As shown in Fig. 3, the method may include the following procedures.

At block S31, an IM chat window is presented.

In block S31, the procedure of presenting the IM chat window may include: providing an IM chat window for a user and the communication peer of the user by an IM tool. The communication peer may be a buddy of the user or a certain type of service account, e.g. , a service account of a lottery service system, a service account of an e-store keeper, a subscription account, or the like.

When a user needs to perform IM communication with the communication peer, he/she needs to open an IM chat window in an IM tool. The IM chat window may have functions of conventional IM chat windows, e.g. , providing text, audio or video communications.

At block S32, a text message is fed into the IM chat window.

The text message may be inputted by any one of the two communication parties. When the two parties are performing IM interactions, text messages are inputted by the user into the IM chat window of the user, or forwarded by a system to an IM chat window of the communication peer and displayed, or received by the IM chat window of the user from the communication peer and displayed, to implement bi-directional IM communication. When the two parties are exchanging IM text messages, the system may receive each of the IM text messages inputted by the two parties into respective IM chat windows.

At block S33, semantic analysis is performed on the text message, it is judged whether the text message includes a target feature, and push content corresponding to the target feature is obtained if the text message includes the target feature.

Semantic analysis may be applied to text messages inputted by both parties into the IM chat window, or text messages received from the communication peer, or text messages inputted by the user. A target feature refers to a pre-defined feature. Each feature corresponds to certain push content. For example, Table 1 shows relations which associates target features with push contents.

Table 1

The procedure of judging whether the text message includes a pre-defined target feature may include: traversing pre-defined target features, judging whether the text message includes a keyword corresponding to a target feature. The keyword may be, for example, “buy a lottery ticket” , “buy a mobile phone” , or the like. That the text message includes the keyword may refer to the text message exactly match the whole keyword, e.g. , the text message may be “I want to buy a lottery ticket” , or “I want to buy a mobile phone” , or may refer to the text message approximately match the keyword, e.g. , the text message may be “Should I try a lottery ticket to chance my luck？ ” , or “Paycheck just received, maybe I should get a fancier mobile phone” . If the text message includes a keyword corresponding to a target feature, it is determined the text message includes the target feature. If the text message includes keywords corresponding to plural target features, further calculations may be made to obtain a matching degree between each of the target features and the text message, and the target feature that has the highest matching degree is regarded as the target feature of the text message. Push content corresponding to the target feature is obtained.

The matching degree refers to the similarity between the target feature and the text message. The method of calculating the matching degree may adopt a conventional algorithm or a dedicated algorithm. For example, edit distance, i. e. , wording similarity, between keywords corresponding to the target feature and the text message may be calculated as the matching degree. Other examples may use other algorithms, e.g. , Euclidean distance, topic semantic distance, or the like.

After it is determined the text message includes a target feature, a correspondence table, e.g. , one like Table 1, is searched to find push content corresponding to the target feature.

The correspondence table may be downloaded and stored by an IM client of the user from a server (e.g. , server 10 as shown in Fig. 1) via a communication network (e.g. , communication network 20 as shown in Fig. 1) , or may be stored in the server and accessible by the IM client via the communication network in real time when there is the need. The server may be an IM server for forwarding IM messages between users, or a server other than the IM server with means of accessing the server configured in IM clients. The method may be implemented by an IM client or an IM server.

At block S34, the push content is outputted to the IM chat window.

In an example, two IM users are performing instant communications in text via respective IM chat window. Supposing the two IM users are user A and user B, Fig. 4 is a schematic diagram illustrating contents displayed in an IM chat window. During the conversation between the users, a system may perform semantic analysis on each text message outputted to the IM chat window. For example, the conversations between the two users are as follows.

User A: What activity was held by your company last weekend？

User B: We had a dinner party. There was a prize draw, too.

User A: Did you win a prize？

User B: I got a first prize.

User A: You are so lucky！ You should buy a lottery ticket.

The system may obtain that the text message sent by user A includes a target feature of “buy *lottery ticket” , search for push content corresponding to the target feature, e.g. , “Please visit lottery website ****to buy lottery tickets” according to the example as shown in Table 1, and output the push content to the IM chat window. The push content may be outputted to the IM chat window of one of the two communication parties and or outputted to the IM chat windows of the two parties respectively. As shown in Fig. 4, a text message “Please visit lottery website ****to buy lottery tickets” may be displayed below the text message of user A. The push content may also include a hyperlink of the recommended lottery website so that the user can directly click on the hyperlink to visit the lottery website. According to the above technical mechanism, conversations of two communicating parties can be analyzed in real time to determine a chatting intention of a user, and push content corresponding to the chatting intention is provided to the user, e.g. , the user B in the above example may browse the lottery website recommended in the push content. As such, time and effort of users searching for target object can be saved, and the amount of human-machine interactions can be reduced which also reduces consumption of resources (e.g. , CPU, memory, network bandwidth or the like) .

According to conventional IM interaction mechanisms, when user A suggests user B to buy a lottery ticket, user B may at least: search for websites selling lottery tickets, e.g. , opening a browser, inputting the web address of a search engine, inputting keywords such as “lottery tickets” and the like, clicking a button to search, looking for a target website in search results displayed in a webpage, and visiting a website to do the purchase after the target website is found. The process includes many procedures and involves a large amount of human-machine interactions, is inefficient and consumes a lot of resources, e.g. , CPU, memory, network bandwidth or the like.

In various examples, push content can be found by searching a correspondence table such as one like Table 1 at block S33 to obtain the push content corresponding to the target feature. In an example, intention of the user may be analyzed to provide more accurate push content. In an example, a processing logic corresponding to a target feature may be set in advance. After it is determined the text message outputted to the IM chat window has the target feature, the processing logic corresponding to the target feature is started to perform calculations to obtain push content corresponding to the target feature. Then the push content is outputted to the IM chat window.

Fig. 5 is a schematic diagram illustrating an IM chat window presenting push content obtained from logic calculations. Supposing the keyword corresponding to the pre-defined target feature is “buy a lottery number” , the processing logic corresponding to the target feature may calculate a lottery number, and output the lottery number to the IM chat window as the push content. In an example as shown in Fig. 5, a user inputted a text message of “which lottery number should I buy this evening？ ” The system obtains keywords “buy” and “lottery number” , obtains a random lottery number by using a processing logic corresponding to the target feature, and outputs the lottery number to the IM chat window, e.g. , lottery number 501 as shown in Fig. 5. In an example, a button for implementing an action may also be pushed to the IM chat window, e.g. , the “buy now” button. The button links to a webpage for implementing the action, e.g. , to a webpage for making a purchase of an e-commerce system. After the user clicks on the button 502, the browser will open a purchasing webpage of the lottery website to facilitate the user making the purchase.

According to an example, a target database may be pre-set for a target feature. After it is determined that a text message outputted to an IM chat window has the target feature, the target database is searched to find an entry matching the target feature. Information recorded in the entry is outputted to the IM chat window as the push content. The target database may be a database of a website in connection with the target feature. Table 2 is an example of mapping relations between target databases and target features.

Pre-defined target feature	Corresponding target database
Pre-defined target feature	Corresponding target database	buy a mobile phone	commodity database of e-commerce website ****

ticket for China Open

ticket database of ticket service website ****

Table 2

Fig. 6 is a schematic diagram illustrating an IM chat window presenting push content obtained by searching in a database. For example, after a user inputs “Paycheck just received, I want a new mobile phone” , the system may analyze the text message and obtain that the target feature of the text message is “buy a mobile phone” . The system then searches the “commodity database of e-commerce website ****” to obtain commodity items matching the keyword “buy a mobile phone” , and presents information of one or multiple of the commodity items in the IM chat window as the push content. In the example as shown in Fig. 6, the push content 601 includes information of the most popular mobile phone commodities. A hyperlink of each of the mobile phone commodities may also be presented. The user may click on the hyperlink to visit a webpage providing product introduction of the mobile phone commodity. In an example, a button for implementing an online purchase may also be presented in the IM chat window, e.g. , the “Buy now” button 602 as shown in Fig. 6. The user may click on the button 602 to visit a webpage of the e-commerce system for purchasing the mobile phone, therefore the user can do the purchase at one simple click.

Various examples also provide a system for processing IM messages which can implement the method of various examples. Fig. 7 is a schematic diagram illustrating modules of a system for processing IM messages in accordance with examples of the present disclosure. The system may be implemented by one or multiple of an IM client, a user terminal device, and an IM server. As shown in Fig. 7, the system 700 may include the following components.

A chatting module 701 is configured to present an IM chat window.

A receiving module 702 is configured to receive a text message fed into the IM chat window.

A semantic analyzing module 703 is configured to perform semantic analysis on the text message, judge whether the text message includes a target feature, and obtain push content corresponding to the target feature if the text message includes the target feature.

A responding module 704 is configured to output the push content to the IM chat window.

The system may also include modules of conventional IM systems that implement functions of conventional IM services.

In an example, the semantic analyzing module 703 may perform semantic analysis on each text message outputted by two communicating users into the IM chat window, determine whether the text message includes the pre-defined target feature, and obtain push content corresponding to the target feature.

In an example, the semantic analyzing module 703 may traverse pre-defined plural target features, judge whether the text message includes a keyword corresponding to a target feature of the plural target features, determine the text message includes the target feature if the text message includes the keyword, and obtain push content corresponding to the target feature.

In an example, the semantic analyzing module 703 may perform calculations to obtain a matching degree between each of plural target features and the text message if the text message includes keywords corresponding to the target features, determine the target feature that has the highest matching degree as the target feature of the text message, and obtain push content corresponding to the target feature.

In an example, the semantic analyzing module 703 may perform calculations using a processing logic pre-set for the target feature to obtain the push content after determining the text message includes the target feature, and provide the push content for the responding module 704.

According to an example, the semantic analyzing module 704 may search a target database pre-set for the target feature to find an entry matching the target feature after determining that the text message outputted to an IM chat window has the target feature, and send information recorded in the entry to the responding module 704 as the push content.

In an example, the technical mechanism may be applied to instant messaging scenarios involving online shopping, the system of various examples can automatically obtain a shopping target by applying semantic analysis to text messages inputted by two communicating users, find out information of an item which is the topic of the chat session, and output the information of the item to the IM chat window of the users. During the whole process, the user does not need to open a new application or a webpage, thus consumption of resources of the terminal device is reduced. The user also does not need to perform interactions with a new application or a webpage nor need to input information into a new application or a webpage. Instead, the IM text messages inputted can directly result in the online purchase, thus online purchase can become easier and efficient, time and effort of the user are also reduced.

It should be understood that in the above processes and structures, not all of the procedures and modules are necessary. Certain procedures or modules may be omitted according to the needs. The order of the procedures is not fixed, and can be adjusted according to the needs. The modules are defined based on function simply for facilitating description. In implementation, a module may be implemented by multiple modules, and functions of multiple modules may be implemented by the same module. The modules may reside in the same device or distribute in different devices. The “first” , “second” in the above descriptions are merely for distinguishing two similar objects, and have no substantial meanings.

The hardware modules according to various examples may be implemented by hardware or a hardware platform with necessary software. The software may include machine-readable instructions which are stored in a non-statutory storage medium. Thus, the examples may be embodied as software products.

In various examples, the hardware may be dedicated hardware or general-purpose hardware executing machine-readable instruction. For example, a hardware module may comprise dedicated circuitry or logic that is permanently configured (e.g. , as a special-purpose processor, such as a field programmable gate array (FPGA) or an application-specific integrated circuit (ASIC) ) to perform certain operations. A module may also comprise programmable logic or circuitry (e.g. , as encompassed within a general-purpose processor or other programmable processor) that is temporarily configured by software to perform certain operations. It will be appreciated that the decision to implement a hardware module mechanically, in dedicated and permanently configured circuitry, or in temporarily configured circuitry (e.g. , configured by software) may be driven by cost and time considerations.

A machine-readable storage medium is also provided, which is to store instructions to cause a machine to execute a method as described herein. Specifically, a system or apparatus having a storage medium which stores machine-readable program codes for implementing functions of any of the above examples and which may make the system or the apparatus (or CPU or MPU) read and execute the program codes stored in the storage medium. Computer readable instructions may make an operating system in a computer to implement part or all of the above described operations. A non-statutory computer-readable storage medium may be a storage device in an extension board inserted in the computer or a storage in an extension unit connected to the computer. Program codes-based instructions can make a CPU or a processor installed in an extension board or an extension unit to implement part or all of the operations to implement any example of the present disclosure.

The non-statutory computer-readable storage medium for providing the program codes may include floppy disk, hard drive, magneto-optical disk, compact disk (such as CD-ROM, CD-R, CD-RW, DVD-ROM, DVD-RAM, DVD-RW, DVD+RW) , magnetic tape drive, Flash card, ROM and so on. Optionally, the program code may be downloaded from a server computer via a communication network.

The scope of the claims should not be limited by the embodiments set forth in the examples, but should be given the broadest interpretation consistent with the description as a whole.

Claims

A method for processing instant messaging (IM) messages, comprising:

presenting an IM chat window；

receiving a text message fed into the IM chat window；

performing semantic analysis on the text message, judging whether the text message includes a pre-defined target feature, and obtaining push content corresponding to the target feature if the text message includes the target feature； and

outputting the push content to the IM chat window.
The method of claim 1, wherein the performing semantic analysis on the text message comprises: performing semantic analysis on each text message outputted by two communicating users to the IM chat window.
The method of claim 1, wherein the judging whether the text message includes a pre-defined target feature comprises:

traversing plural pre-defined target features, judging whether the text message includes a keyword corresponding to a target feature of the plural target features, and determining the text message includes the target feature if the text message includes the keyword corresponding to the target feature.
The method of claim 3, further comprising: calculating a matching degree between each of plural target features and the text message if the text message includes keywords corresponding to the plural target features, determining a target feature that has the highest matching degree as the target feature of the text message, and obtaining push content corresponding to the target feature.
The method of claim 1, further comprising:

pre-defining a processing logic corresponding to the target feature； performing calculations by using the processing logic to obtain the push content when the text message includes the target feature, and outputting the push content to the IM chat window.
The method of claim 1, further comprising: pre-defining a target database for a target feature； searching the target database to find an entry matching the target feature after it is determined that a text message outputted to an IM chat window includes the target feature, outputting information recorded in the entry to the IM chat window as the push content.
A system for processing instant messaging (IM) messages, comprising a processor and a memory； the memory storing a series of computer-readable instructions executable by the processor to perform actions of:

presenting an IM chat window；

receiving a text message fed into the IM chat window；

performing semantic analysis on the text message, judging whether the text message includes a target feature, and obtaining push content corresponding to the target feature if the text message includes the target feature； and

outputting the push content to the IM chat window.
The system of claim 7, wherein the computer-readable instructions are executable by the processor to perform actions of: performing semantic analysis on each text message outputted by two communicating users to the IM chat window to determine whether the text message includes the target feature, and obtaining the push content corresponding to the target feature if the text message includes the target feature.
The system of claim 7, wherein the computer-readable instructions are executable by the processor to perform actions of: traversing plural pre-defined target features, judging whether the text message includes a keyword corresponding to a target feature of the plural target features, determining the text message includes the target feature if the text message includes the keyword, and obtaining push content corresponding to the target feature.
The system of claim 9, wherein the computer-readable instructions are executable by the processor to perform actions of: performing calculations to obtain a matching degree between each of plural target features and the text message if the text message includes keywords corresponding to the plural target features, determining a target feature that has the highest matching degree as the target feature of the text message, and obtaining push content corresponding to the target feature.
The system of claim 7, wherein the computer-readable instructions are executable by the processor to perform actions of: pre-defining a processing logic for a target feature； performing calculations by using the processing logic to obtain the push content corresponding to the target feature when the text message includes the target feature, and outputting the push content to the IM chat window.
The system of claim 7, wherein the computer-readable instructions are executable by the processor to perform actions of: pre-defining a target database for a target feature； searching the target database to find an entry matching the target feature after it is determined that a text message outputted to an IM chat window has the target feature, outputting information recorded in the entry to the IM chat window as the push content.