Interactive response system based on artificial intelligence

Abstract

The invention discloses an interactive response system based on artificial intelligence in the technical field of artificial intelligence, and the system comprises an intelligent analysis center, and input information is firstly processed to extract interaction features, including recognition of key elements inputted by a user and relationships thereof. Based on the characteristics, the system uses an advanced algorithm to carry out data analysis, and aims to find records or model output with the highest matching degree from a database. And generating accurate and related interaction feedback according to the optimal matching result. Interaction results are detected and analyzed in real time through connected sensor data, output content is optimized through environment, position information and the like, information is searched and displayed through intelligent analysis, if the information is internal data, the face and pupils of interaction personnel are analyzed through the sensor data, and the interaction effect is improved. After the analysis is completed, a visual report is generated and displayed after the external environment is confirmed through the sensor data, and if the data is the external data, the visual report is generated and displayed after the external environment is confirmed through the sensor data.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and specifically to an interactive response system based on artificial intelligence. Background Art

[0002] With the development of the Internet, the communication methods between enterprises and organizations and customers have become increasingly diverse. Traditional customer service centers rely on manual operations, which are not only costly but also difficult to ensure 24-hour uninterrupted service. To address these challenges, various automated solutions have emerged in recent years, and among them, AI-based interactive response systems have become a research and application hotspot.

[0003] In the process of realizing interactive response, a common challenge is that it is difficult for the system to make appropriate adjustments according to the specific situation of the individual with whom it interacts, which directly leads to poor interaction effects and reduces the user experience. Specifically, some current interactive response systems, when processing information and making responses, often only rely on the direct input provided by the user and ignore the impact of the actual interaction environment on user needs. Although this method can meet basic information queries or service requests to a certain extent, due to the lack of flexibility and personalized consideration, it cannot fully take into account the specific situation and its changes of the user, thus affecting the quality of the interaction. Therefore, in order to improve the efficiency and user experience of the interactive response system, it is necessary to focus on enhancing the system's perception ability, enabling it to not only understand the user's language content but also keenly capture various environmental clues involved in the interaction process, and accordingly flexibly adjust the response strategy to provide a service experience that is more in line with the actual situation and personal preferences of the user. Based on this, the present invention designs an interactive response system based on artificial intelligence to solve the above problems. Summary of the Invention

[0004] The purpose of the present invention is to provide an interactive response system based on artificial intelligence to solve the problems raised in the above background art.

[0005] To achieve the above purpose, the present invention provides the following technical solutions:

[0006] An interactive response system based on artificial intelligence includes an intelligent analysis center. Input information is first processed to extract interaction features, including identifying key elements of the user input and their relationships. Based on these features, the system uses advanced algorithms for data analysis, aiming to find the record or model output with the highest matching degree in the database. An accurate and relevant interaction feedback is generated according to the best matching result. Then, the interaction results are detected and analyzed in real time through connected sensor data, and the output content is optimized using environmental and location information, etc.;

[0007] Data cleaning and preprocessing, integrating the analyzed information, cleaning noise, missing values, and outliers in the data, and performing standard transformation on the data to achieve convenient display. Through advanced analysis, predictive analysis and prescriptive analysis are carried out using methods such as statistical analysis, machine learning, and deep learning, and unstructured data is processed using technologies such as natural language processing (NLP) and image recognition;

[0008] The intelligent analysis center is used to obtain interaction features from the input information, analyze the data based on the obtained information, generate an interaction result for the matching result with the largest data matching degree value, and then detect and analyze the interaction result through sensor data, and perform classification display after the analysis is completed.

[0009] Preferably, internal data, such as enterprise resource planning (ERP) systems, customer relationship management (CRM) systems, and point of sale (POS) systems.

[0010] Preferably, external data, such as social media data, public datasets, data obtained through third-party API interfaces (such as weather information, financial market data), etc.

[0011] Preferably, it includes sensor data, which is collected through a micro camera and facial recognition set externally, including various sensors (temperature, humidity, GPS positioning, etc.).

[0012] Preferably, it includes integrating heterogeneous data, identifying and correcting or removing data points that do not conform to the expected pattern to ensure data quality.

[0013] Preferably, it includes data standard transformation. In the data preprocessing stage, the collected data is standard-transformed by ensuring data type consistency, numerical standardization (such as normalization and Z-score normalization), encoding categorical variables, unifying units, handling missing values, and text cleaning and normalization to improve the accuracy and efficiency of subsequent analysis.

[0014] Preferably, the above includes advanced analysis. Advanced analysis uses technologies such as statistical analysis, machine learning, deep learning, natural language processing, and image recognition to deeply mine and identify patterns in the data to achieve predictive analysis and prescriptive analysis.

[0015] Preferably, it includes visual report generation. Through sensor recognition of the user's age, a classification report is generated, providing various visual forms such as charts and dashboards to help users better understand the data and automatically generate a detailed analysis report according to user needs.

[0016] Compared with the prior art, the beneficial effects of the present invention are:

[0017] The present invention intelligently analyzes the information input through the interactive personnel input interface, searches for and displays the information through intelligent analysis. If it is internal data, the appearance and pupils of the interactive personnel are analyzed through sensor data. After the analysis is completed, the external environment is confirmed through sensor data, and a visual report is generated for display. If it is external data, a visual report is generated for display after the external environment is confirmed through (sensor data of social media data, public data sets, data obtained from third-party API interfaces). BRIEF DESCRIPTION OF THE DRAWINGS

[0018] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0019] Figure 1 It is the system principle framework of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0020] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, rather than all, embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the scope of protection of the present invention.

[0021] Please refer to Figure 1 , the present invention provides a technical solution:

[0022] An interactive response system based on artificial intelligence, including an intelligent analysis center. The input information is first processed to extract interaction features, including identifying key elements input by the user and their relationships. Based on these features, the system uses advanced algorithms for data analysis to find the record or model output with the highest matching degree in the database. Accurate and relevant interaction feedback is generated according to the best matching result. Then, these interaction results are detected and analyzed in real time through the connected sensor data, and the output content is optimized using environmental, location information, etc.;

[0023] Data cleaning and preprocessing, integrating the analyzed information, cleaning noise, missing values, and outliers in the data, and performing standard conversion on the data to achieve convenient display. Through advanced analysis, predictive analysis and prescriptive analysis are performed using methods such as statistical analysis, machine learning, and deep learning, and techniques such as natural language processing (NLP) and image recognition are applied to process unstructured data;

[0024] The intelligent analysis center is used to obtain interaction features from the input information, analyze the data based on the obtained information, generate an interaction result for the matching result with the largest data matching degree value, then detect and analyze the interaction result through sensor data, and perform classification display after the analysis is completed;

[0025] Internal data, such as enterprise resource planning (ERP) systems, customer relationship management (CRM) systems, point of sale (POS) systems, external data, such as social media data, public data sets, data obtained through third-party API interfaces (such as weather information, financial market data), etc., including sensor data, are collected through externally set micro cameras and facial recognition, including various sensors (temperature, humidity, GPS positioning, etc.);

[0026] It includes integrating heterogeneous data, identifying and correcting or removing data points that do not conform to the expected pattern to ensure data quality, including data standard conversion. In the data preprocessing stage, the collected data is subjected to standard conversion by ensuring data type consistency, numerical standardization (such as normalization and Z-score normalization), encoding categorical variables, unifying units, handling missing values, and text cleaning and normalization to improve the accuracy and efficiency of subsequent analysis;

[0027] The above includes advanced analysis. Advanced analysis uses technologies such as statistical analysis, machine learning, deep learning, natural language processing, and image recognition to deeply mine data and identify patterns to achieve predictive analysis and prescriptive analysis, including generating visual reports. Through sensors, the user's age is identified and a classification report is generated, providing various visual forms such as charts and dashboards to help users better understand the data, and automatically generating a detailed analysis report according to user needs.

[0028] The user selects through the input interface, voice (text) input or image input. During the user input process, externally set sensors (facial sensors) scan the user and upload facial data. After the user input is completed, the information input by the user is analyzed based on the user's historical input data and database data. If it is internal information, the face irradiated by the sensor needs to be recognized. After successful recognition, a report is generated for the searched data according to the external information detected by the sensor. If it is external data, such as social media data, public data sets, data obtained through third-party API interfaces (such as weather information, financial market data), etc., a report is generated;

[0029] The input environment of the user is recognized according to the sensor. If the input environment is a public place, the volume of the voice output module is adjusted to an appropriate decibel to avoid the user having difficulty in listening. If it is a private space, the user is prompted to pay attention to the sound volume of the voice module. After the prompt is completed, the output method is selected through voice output, text output, and image output displayed on the screen. The voice output module can be connected according to Bluetooth or wired headphones to avoid data being overheard, and can also be displayed through the text output displayed on the screen;

[0030] When the user needs image output, the data analyzed is recognized and the data points that do not conform to the expected pattern are corrected or removed by integrating heterogeneous data in data cleaning and preprocessing. After the processing is completed, through data standard conversion, the data values are standardized (such as normalization and Z-score standardization), categorical variables are encoded, units are unified, missing values are processed, and text cleaning and normalization are performed to perform standard conversion on the collected data. After the conversion is completed, through advanced analysis using statistical analysis, machine learning, deep learning, and natural language processing, it is converted into a conforming image for subsequent display.

[0031] In the description of this specification, the description with reference to terms such as "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0032] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the present invention to only the specific implementation manners. Obviously, according to the content of this specification, many modifications and changes can be made. These embodiments are selected and specifically described in this specification to better explain the principles and practical applications of the present invention, so that those skilled in the art in the relevant technical field can understand and utilize the present invention well. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. An artificial intelligence-based interactive response system, characterized in that: including an intelligent analysis center, where the input information is first processed to extract interaction features, including identifying the key elements of the user input and their relationships; Based on these features, the system uses advanced algorithms for data analysis, aiming to find the record or model output with the highest matching degree in the database; generating accurate and relevant interaction feedback according to the best matching result; then, the interaction results are detected and analyzed in real time through the connected sensor data, and the output content is optimized using environmental, location information, etc.; data cleaning and preprocessing, integrating the analyzed information, cleaning the noise, missing values and outliers in the data, and performing standard conversion on the data to achieve convenient display. Through advanced analysis, predictive analysis and prescriptive analysis are carried out using methods such as statistical analysis, machine learning, and deep learning, and technologies such as natural language processing (NLP) and image recognition are applied to process unstructured data; an intelligent analysis center, used to obtain interaction features from the input information, analyze the data based on the obtained information, generate an interaction result for the matching result with the largest data matching degree value, and then detect and analyze the interaction result through sensor data, and perform classification display after the analysis is completed.

2. The interactive response system based on artificial intelligence according to claim 1, wherein: including internal data, such as enterprise resource planning (ERP) systems, customer relationship management (CRM) systems, and point of sale (POS) systems.

3. The interactive response system based on artificial intelligence according to claim 1, wherein: including external data, such as social media data, public data sets, data obtained through third-party API interfaces (such as weather information, financial market data), etc.

4. An interactive response system based on artificial intelligence according to claim 1, characterized in that: including sensor data, collected through externally installed micro cameras and facial recognition, including various sensors (temperature, humidity, GPS positioning, etc.).

5. An interactive response system based on artificial intelligence according to claim 1, characterized in that: including integrating heterogeneous data, identifying and correcting or removing data points that do not conform to the expected pattern to ensure data quality.

6. The interactive response system based on artificial intelligence according to claim 1, wherein: including data standard conversion. In the data preprocessing stage, the collected data is standard-converted by ensuring data type consistency, numerical standardization (such as normalization and Z-score normalization), encoding categorical variables, unifying units, handling missing values, and text cleaning and normalization to improve the accuracy and efficiency of subsequent analysis.

7. An interactive response system based on artificial intelligence according to claim 1, characterized in that: including advanced analysis, which uses technologies such as statistical analysis, machine learning, deep learning, natural language processing, and image recognition to deeply mine and identify patterns in the data to achieve predictive analysis and prescriptive analysis.

8. An interactive response system based on artificial intelligence according to claim 1, characterized in that: including visual report generation, generating a classification report for the user's age identified by the sensor, providing various visual forms such as charts and dashboards to help users better understand the data, and automatically generating a detailed analysis report according to the user's needs.

Images