CN108197298A - A kind of smart shopper exchange method and system based on natural language processing - Google Patents
A kind of smart shopper exchange method and system based on natural language processing Download PDFInfo
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Abstract
The invention belongs to smart shopper fields, specifically disclose a kind of smart shopper exchange method based on natural language processing and system, this method include：The voice request received is converted into text；Cutting word is carried out to the text, sentence dissects, and obtains and dissects result；It carries out semantic analysis and obtains key message word and qualifier；Matching inquiry processing is carried out in merchandise system according to key message word and qualifier, obtains query processing result；The result of query processing is showed into user.Smart shopper exchange method and system proposed by the present invention based on natural language processing, the voice request received can be converted into text, and semantic analysis is carried out to text, then query processing is carried out according to the result of the semantic analysis, and the result of query processing is exported to client, so that the access of shopping service, using and manipulating very convenient, the inquiry of the particular commodities such as especially preferential order is very natural and hommization, effectively increases the shopping experience of user.
Description
Technical Field
The invention relates to the field of intelligent shopping, in particular to an intelligent shopping interaction method and system based on natural language processing.
Background
Today, with the rapid development of internet technology, online shopping is favored by users, and online shopping has many advantages: can help users save time, reduce shopping cost, enlarge selection and the like, so that the scale of online shopping is increasing rapidly. The online transaction is convenient, and meanwhile, some problems exist, such as various online commodities and numerous quantity, and a user can hardly find a needed commodity quickly; for example, when a user wants to buy a red camel brand jacket which is waterproof and cold-proof, the user usually needs to do screening many times on a shopping website, select the jacket first, and select a brand and a color. In fact, the user converts various choices into calculation to directly identify keywords, and the computer queries according to the keywords, so that the end user can search similar commodities.
With the continuous expansion of the electronic commerce scale, the number and the variety of the commodities are rapidly increased, and customers need to spend a great deal of time to find the commodities which the customers want to buy. This process of browsing through large amounts of unrelated information and products will undoubtedly result in a constant loss of consumers who are overwhelmed by the problem of information overload. Meanwhile, as the electronic commerce system is under continuous expansion, the system structure is continuously complicated, the number of users and commodities is almost linear, however, many recommendation algorithms at the present stage have two problems due to self condition limitation: sparsity and extensibility problems, which severely affect the quality of recommendations. On the other hand, the voice query function has very practical application in various industries. With the popularization of mobile terminals, more and more speech recognition applications are developed.
Such as amazon Shopbot, i.e. i want to buy 42 yards of black breathable nike running shoes, Shopbot will go on to ask which number and list the menu to choose from, and then ask which brand, price range, etc., all require the user to select through the menu, which is tedious and some items cannot be selected, such as whether the running shoes are breathable, etc. The current method has the following disadvantages: the computer cannot understand the human language and accurately recognize information such as all product attributes included in the natural language. Therefore, the voice recognition technology can be used for facilitating the search or operation of the user to a certain extent, and if the voice recognition technology can be supplemented with a system for actively screening and recommending commodities according to the user requirements, products most suitable for the user can be expected to be recommended more quickly and conveniently, so that the purpose that the user can find the required commodities more conveniently is achieved, and the use experience of the user is greatly improved.
Disclosure of Invention
In view of this, embodiments of the present invention provide a method and a system for voice shopping, which can implement whole-course voice shopping, even no-screen shopping, provide a more convenient shopping service for a user, and further solve the problem that shopping cannot be performed through voice in the present stage.
The technical scheme adopted by the invention is as follows:
one aspect of the embodiment of the invention provides an intelligent shopping interaction method based on natural language processing. The method comprises the following steps: s1, converting the received voice request into a text; s2, segmenting words and sentences of the text; s3, according to the parsing result, performing semantic analysis and acquiring key information words and modifiers; s4, performing matching query processing in the commodity system according to the key information words and the modifiers to obtain a query processing result; and S5, displaying the result of the query processing to the user.
In another aspect of the present invention, an intelligent shopping interaction system based on natural language processing is further provided, including: the conversion module is used for converting the received voice request into a text; the sentence analyzing module is used for carrying out word segmentation and sentence analysis on the text; the semantic analysis module is used for performing semantic analysis and acquiring key information words and modifiers according to the parsing result; the matching query module is used for performing matching query processing in the commodity system according to the key information words and the modifiers to obtain a query processing result; and the output module is used for displaying the query processing result to the user.
The invention has the beneficial effects that:
the intelligent shopping interaction method and system based on natural language processing can convert the received voice request into the text, perform semantic analysis on the text, perform query processing according to the result of the semantic analysis, and output the result of the query processing to the client. In the whole process, the user query request and the purchase request can be processed and responded, so that whole-course voice and screen-free shopping can be realized, more convenient shopping service is provided for the user, and the problem that the shopping can not be carried out in the whole course at the present stage is solved. And the access, the use and the control of the shopping service are very convenient, particularly, the inquiry of special commodities such as preferential orders and the like is very natural and humanized, and the shopping experience of the user is effectively improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the principles of the invention. In the drawings:
FIG. 1 is an exemplary system architecture diagram of one embodiment of the present invention.
FIG. 2 is a flowchart illustrating an intelligent shopping interaction method based on natural language processing according to an embodiment of the present invention.
FIG. 3 is a schematic structural diagram of an intelligent shopping interaction system based on natural language processing according to an embodiment of the present invention.
In the drawings, the same or corresponding reference numerals indicate the same or corresponding parts.
Detailed Description
The principles and spirit of the present invention will be described with reference to a number of exemplary embodiments. It is understood that these embodiments are given solely for the purpose of enabling those skilled in the art to better understand and to practice the invention, and are not intended to limit the scope of the invention in any way. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
The technical means adopted by the invention to achieve the predetermined object of the invention are further described below with reference to the drawings and the preferred embodiments of the invention.
FIG. 1 illustrates an exemplary system architecture 100 for a natural language processing based intelligent shopping interaction method and system to which embodiments of the present invention may be applied. As shown in fig. 1, the system architecture 100 may include terminal devices 101, 102, 103, a network 104, and a server 105. Wherein,
the network 104 serves as a medium for providing communication links between the terminal devices 101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.
The user may use the terminal devices 101, 102, 103 to interact with the server 105 via the network 104 to receive or send messages or the like. The terminal devices 101, 102, 103 may have installed thereon various communication client applications, such as shopping-like applications, web browser applications, search-like applications, instant messaging tools, mailbox clients, social platform software, etc. (by way of example only).
The terminal devices 101, 102, 103 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like.
The server 105 may be a server providing various services, such as a background management server (for example only) providing support for shopping-like websites browsed by users using the terminal devices 101, 102, 103. The backend management server may analyze and perform other processing on the received data such as the product information query request, and feed back a processing result (for example, target push information, product information — just an example) to the terminal device.
It should be noted that the method for voice shopping provided by the embodiment of the present invention is generally executed by the server 105, and accordingly, a system for voice shopping is generally disposed in the server 105.
It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
FIG. 2 is a flowchart illustrating an intelligent shopping interaction method based on natural language processing according to an embodiment of the present invention. As shown in fig. 2, a method for voice shopping according to an embodiment of the present invention mainly includes:
s1, converting the received voice request into a text;
s2, segmenting words and sentences of the text;
s3, according to the parsing result, performing semantic analysis and acquiring key information words and modifiers;
s4, performing matching query processing in the commodity system according to the key information words and the modifiers to obtain a query processing result;
and S5, displaying the result of the query processing to the user.
Wherein the voice request includes a query request and a purchase request, and wherein performing query purchase processing according to the result of the semantic analysis includes performing query processing and performing purchase processing according to the result of the semantic analysis.
Specifically, step S2 includes: and segmenting the text into words, wherein the segmentation mode comprises nouns, verbs, adjectives, quantitative words, pronouns and auxiliary words, and the sentence is analyzed according to the part of speech in the text.
Step S3 includes: and performing semantic analysis on the words in the analysis result, and acquiring key information words and modified words according to the semantic and part-of-speech combined analysis.
Step S4 includes: determining query logic according to the semantic analysis result, wherein the query logic comprises a query range and a query sequence of the query range, and querying commodity information to be output according to the query logic; when the key information words and the modifiers are matched and inquired in the commodity system, the matching processing result cannot be obtained in the database, and the inquiry processing result is obtained through online deep learning.
The results of the query processing include: information on a commodity, information on whether purchase is confirmed, or information on whether switching is confirmed; wherein,
the information of the commodity comprises state information of the commodity, and the state information at least comprises one of the following items: shipping mode, payment mode, harvest address, availability of goods and preferential policy.
After determining the commodities with output according to the result of semantic analysis, the discount strategies of the commodities can be further determined, and the discount strategies are compared and analyzed, so that the best discount commodity is output for the user firstly. In the process of comparing and analyzing the preference strategies of the commodities, the sequence of the speech output of the commodities can be determined according to the historical data of the user. For example, after querying a mobile phone with a price of 2000 yuan to 3000 yuan, a user determines that the user is a demand through semantic analysis, searches and queries the mobile phone with the price of 2000 yuan to 3000 yuan in a commodity library, determines that partial commodities are in preferential promotion, and gives a discount for one mobile phone in a millet brand 300 yuan, but by querying purchase record data and browsing record data of the user, the user can be known to be concerned with the mobile phone with the Hua brand all the time, and further can preferentially recommend the mobile phone with the Hua brand.
After the commodity is inquired according to the result of semantic analysis, the information of the inquired commodity is converted into voice to be output. The output commodity information comprises detailed information of the commodity and state information of the commodity, the detailed information of the commodity comprises the brand, the model, the price and the like of the commodity, and the state information comprises a delivery mode, a payment mode, a harvest address, whether the commodity is available or not, a preference strategy and the like. After the information of the commodity is output, it is output.
Although the operations of the method of the present invention are depicted in the drawings in a particular order, this does not require or imply that these operations must be performed in this particular order, or that all of the illustrated operations must be performed, to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions.
Having described the method of the exemplary embodiment of the present invention, the intelligent shopping interaction system based on natural language processing of the exemplary embodiment of the present invention will be described with reference to fig. 3.
The implementation of the intelligent shopping interaction system based on natural language processing can be referred to the implementation of the method, and repeated details are not repeated. The term "unit" or "module" used hereinafter may be a combination of software and/or hardware that implements a predetermined function. Although the means described in the embodiments below are preferably implemented in software, an implementation in hardware, or a combination of software and hardware is also possible and contemplated.
FIG. 3 is a schematic structural diagram of an intelligent shopping interaction system based on natural language processing according to an embodiment of the present invention. As shown in fig. 3, the system mainly includes:
the conversion module 1 is used for converting the received voice request into a text;
the sentence analyzing module 2 is used for carrying out word segmentation and sentence analysis on the text;
the semantic analysis module 3 is used for performing semantic analysis according to the parsing result and acquiring key information words and modifiers;
the matching query module 4 is used for performing matching query processing in the commodity system according to the key information words and the modifiers to obtain a query processing result;
and the output module 5 is used for displaying the query processing result to the user.
It should be noted that the computer readable medium shown in the present invention can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present invention, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present invention, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The modules described in the embodiments of the present invention may be implemented by software or hardware. The described modules may also be provided in a processor, which may be described as: a processor includes a conversion module, a speech analysis module, a processing module, and an output module. Where the names of the units do not in some cases constitute a limitation on the units themselves, for example, the translation module may also be described as "translating received voice requests into text".
The intelligent shopping interaction method and system based on natural language processing can convert the received voice request into the text, perform semantic analysis on the text, perform query processing according to the result of the semantic analysis, and output the result of the query processing to the client. In the whole process, the user query request and the purchase request can be processed and responded, so that whole-course voice and screen-free shopping can be realized, more convenient shopping service is provided for the user, and the problem that the shopping can not be carried out in the whole course at the present stage is solved. And the access, the use and the control of the shopping service are very convenient, particularly, the inquiry of special commodities such as preferential orders and the like is very natural and humanized, and the shopping experience of the user is effectively improved.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (8)
1. An intelligent shopping interaction method based on natural language processing is characterized by comprising the following steps:
s1, converting the received voice request into a text;
s2, segmenting words and sentences of the text to obtain an analysis result;
s3, according to the parsing result, performing semantic analysis and acquiring key information words and modifiers;
s4, performing matching query processing in the commodity system according to the key information words and the modifiers to obtain a query processing result;
and S5, displaying the result of the query processing to the user.
2. The intelligent shopping interaction method based on natural language processing as claimed in claim 1, wherein the voice request includes a query request and a purchase request, and wherein the query purchase processing according to the result of the semantic analysis includes query processing and purchase processing according to the result of the semantic analysis.
3. The intelligent shopping interaction method based on natural language processing as claimed in claim 1, wherein S2, performing word segmentation and sentence parsing on the text, comprises:
and segmenting the text into words, wherein the segmentation mode comprises nouns, verbs, adjectives, quantitative words, pronouns and auxiliary words, and the sentence is analyzed according to the part of speech in the text.
4. The intelligent shopping interaction method based on natural language processing as claimed in claim 1, wherein S3, according to the parsing result, performing semantic analysis and obtaining key information words and modifiers, comprises:
and performing semantic analysis on the words in the analysis result, and acquiring key information words and modified words according to the semantic and part-of-speech combined analysis.
5. The intelligent shopping interaction method based on natural language processing as claimed in claim 2, wherein S4, performing matching query processing in the merchandise system according to the key information words and modifiers, and obtaining the query processing result, comprises:
and determining query logic according to the semantic analysis result, wherein the query logic comprises a query range and a query sequence of the query range, and querying commodity information to be output according to the query logic.
6. The intelligent shopping interaction method based on natural language processing as claimed in claim 2, wherein S4, performing matching query processing in the merchandise system according to the key information words and modifiers, and obtaining the query processing result, comprises:
when the key information words and the modifiers are matched and inquired in the commodity system, the matching processing result cannot be obtained in the database, and the inquiry processing result is obtained through online deep learning.
7. The intelligent shopping interaction method based on natural language processing as claimed in claim 1, wherein the result of said query processing includes: information on a commodity, information on whether purchase is confirmed, or information on whether switching is confirmed; wherein,
the information of the commodity comprises state information of the commodity, and the state information at least comprises one of the following items: shipping mode, payment mode, harvest address, availability of goods and preferential policy.
8. An intelligent shopping interaction system based on natural language processing, comprising:
the conversion module is used for converting the received voice request into a text;
the sentence analyzing module is used for carrying out word segmentation and sentence analysis on the text;
the semantic analysis module is used for performing semantic analysis and acquiring key information words and modifiers according to the parsing result;
the matching query module is used for performing matching query processing in the commodity system according to the key information words and the modifiers to obtain a query processing result;
and the output module is used for displaying the query processing result to the user.
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| CN109271502A (en) * | 2018-09-25 | 2019-01-25 | 武汉大学 | A kind of classifying method and device of the space querying theme based on natural language processing |
| CN109617783A (en) * | 2018-11-08 | 2019-04-12 | 成都颠峰科创信息技术有限公司 | Single service system under a kind of user based on semantic analysis |
| CN109840323A (en) * | 2018-12-14 | 2019-06-04 | 深圳壹账通智能科技有限公司 | The voice recognition processing method and server of insurance products |
| CN112148751A (en) * | 2019-06-28 | 2020-12-29 | 北京百度网讯科技有限公司 | Method and device for querying data |
| CN112423119A (en) * | 2020-11-20 | 2021-02-26 | 广州欢网科技有限责任公司 | Real-time image modeling design method, device and equipment for smart television terminal |
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| CN112148751A (en) * | 2019-06-28 | 2020-12-29 | 北京百度网讯科技有限公司 | Method and device for querying data |
| CN112148751B (en) * | 2019-06-28 | 2024-05-07 | 北京百度网讯科技有限公司 | Method and device for querying data |
| CN112423119A (en) * | 2020-11-20 | 2021-02-26 | 广州欢网科技有限责任公司 | Real-time image modeling design method, device and equipment for smart television terminal |
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Application publication date: 20180622 |