TWI689843B - Intelligent appraisal system and method therof - Google Patents

Intelligent appraisal system and method therof Download PDF

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TWI689843B
TWI689843B TW107109635A TW107109635A TWI689843B TW I689843 B TWI689843 B TW I689843B TW 107109635 A TW107109635 A TW 107109635A TW 107109635 A TW107109635 A TW 107109635A TW I689843 B TWI689843 B TW I689843B
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reply message
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semantic analysis
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TW201941019A (en
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鍾建屏
何健偉
王逸程
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荔枝智慧股份有限公司
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An intelligent appraisal system and method thereof are provided. The interactive appraisal system includes a user interface, a chatting robot device and a semantic analyzing engine. The chatting robot device receives a question message from an appraisal database to actively present the question message on the user interface. A reply message is sent to the semantic analyzing engine when the user interface receives the reply message. The semantic analysis engine extracts keywords from the reply message by using an algorithm module so as to parse the reply message. A classification module classifies the analyzed reply message into categories according to a field distribution. A score module gives scores according to contents of the classified reply message. A report generating device then compiles the reply message, the categories and the scores to generate a report.

Description

智能檢核系統及其方法 Intelligent inspection system and method

本發明係一種互動式檢核系統及其方法,其係透過使用者與聊天機器人提出答詢並將答詢結果經過解析以作為檢核統計使用。 The invention is an interactive verification system and method, which is to make a query through a user and a chat robot and analyze the result of the query to be used as verification statistics.

檢核是用於收集使用者所回饋的意見,並將回饋意見予以分析以作為後續管理之用。一般來說,檢核係用於教學內容的課程意見、消費行為的後續追蹤、對於服務內容或產品的意見回饋等等。 The audit is used to collect the feedback from users and analyze the feedback for subsequent management. Generally speaking, the inspection department is used for the course content of teaching content, the follow-up of consumer behavior, feedback on service content or products, etc.

既有的檢核在實行上主要是使用紙本施測或線上填答兩種方式,但紙本施測在實際運用時容易受到時間與地點的限制,而使得填答的回覆率普遍較低,而且紙本所耗費的紙張也有環保方面的疑慮,另一方面,紙本施測因為欠缺與受測者之間的互動機制,在相同問卷之下,可能因為不同的問卷講解人的描述而造成偏誤,而問卷題目也沒有辦法提供其他解釋使受測者能夠藉由互動得到不同的題目描述,進而影響填答的準確率。 Existing inspections mainly use paper-based testing or online answering, but paper-based testing is susceptible to time and location constraints in actual use, which makes the response rate for answering questions generally low. In addition, the paper consumed by the paper also has environmental concerns. On the other hand, due to the lack of an interaction mechanism with the testee, the paper test under the same questionnaire may be explained by different questionnaires. It caused errors, and there was no way for the questionnaire questions to provide other explanations so that the testees could get different question descriptions through interaction, which in turn affected the accuracy of answering.

線上填答雖然可以將紙本問卷的內容電子化而有更 多表達效果及方式,且能夠減少受測者在時間與地點上的使用侷限,但仍然無提供紙本填答過程中所欠缺的互動機制,受測者在無法理解問題時,無法即時地藉由互動機制得到對於題目更進一步的解釋,線上填答同樣無法大幅提高問卷的準確程度。此外,在質化性題目的填答上,也無法藉由互動的過程得到更多的資訊。 Although answering online can change the content of the paper questionnaire electronically, Multiple expression effects and methods, and can reduce the use limitations of the testee in time and place, but there is still no interactive mechanism that is lacking in the paper answering process. When the testee cannot understand the question, he cannot borrow it in real time. The interactive mechanism provides a further explanation of the question. Online answering also cannot greatly improve the accuracy of the questionnaire. In addition, when filling and answering qualitative questions, we cannot get more information through the interactive process.

為解決前述問題,本發明提供一種互動式檢核系統,其包括:使用者介面;聊天機器人裝置,其係連接於該使用者介面以及檢核資料庫,該聊天機器人裝置係由該檢核資料庫取得問題訊息以主動呈現該問題訊息於該使用者介面,俾於該使用者介面接收到回覆訊息後,將該回覆訊息傳送至語意解析引擎;該語意解析引擎,其係包括演算法模組、分類模組以及評分模組,其中,該演算法模組將該回覆訊息經過關鍵字提取以解析該回覆訊息,再將經解析的該回覆訊息傳送至該分類模組及該評分模組,以供該分類模組將經解析的該回覆訊息予以分類至依照領域配置的類別,並令該評分模組根據分類後的該回覆訊息中的內容給予分數;以及報表產生裝置,其彙整經該語意解析引擎所解析的該回覆訊息、該分類模組的分類結果及該評分模組所給予的分數以產生報表。 To solve the aforementioned problems, the present invention provides an interactive verification system, which includes: a user interface; a chat robot device connected to the user interface and a verification database; the chat robot device is based on the verification data The library obtains the question message to actively present the question message to the user interface. After the user interface receives the reply message, the reply message is sent to the semantic analysis engine; the semantic analysis engine, which includes an algorithm module , A classification module, and a scoring module, wherein the algorithm module extracts the reply message through keywords to parse the reply message, and then sends the parsed reply message to the classification module and the scoring module, For the classification module to classify the parsed reply message into categories configured according to the field, and cause the scoring module to give a score based on the content of the classified reply message; and a report generation device that aggregates the The reply message parsed by the semantic analysis engine, the classification result of the classification module and the score given by the scoring module to generate a report.

本發明另提供一種互動式檢核方法,其包括:由檢核資料庫取得問題訊息;透過聊天機器人裝置主動呈現該問題訊息於使用者介面;接收回覆訊息以傳送該回覆訊息至 語意解析引擎;透過該語意解析引擎的演算法模組將該回覆訊息經過關鍵字提取以解析該回覆訊息;透過該語意解析引擎的分類模組將經解析的該回覆訊息予以分類至依照領域配置的類別;透過該語意解析引擎的評分模組根據分類後的該回覆訊息中的內容給予分數;以及彙整經該語意解析引擎所解析的該回覆訊息、該分類模組的分類結果及該評分模組所給予的分數以透過報表產生裝置產生報表。 The present invention also provides an interactive verification method, which includes: obtaining a question message from the verification database; actively presenting the question message to a user interface through a chat robot device; receiving a reply message to send the reply message to Semantic analysis engine; extract the reply message through keyword extraction through the semantic analysis engine's algorithm module; parse the reply message through the semantic analysis engine's classification module to classify the parsed reply message according to domain configuration The category of; the score module of the semantic analysis engine gives a score according to the content of the reply message after classification; and summarizes the reply message parsed by the semantic analysis engine, the classification result of the classification module, and the scoring module The scores given by the group to generate reports through the report generating device.

前述的互動式檢核系統及方法,進一步包括答覆資料庫,其係儲存經過該語意解析引擎所處理的該回覆訊息以提供該回覆訊息於報表產生裝置。 The aforementioned interactive verification system and method further include a reply database, which stores the reply message processed by the semantic analysis engine to provide the reply message to the report generation device.

前述的互動式檢核系統及方法,進一步包括學習程序裝置,其係透過模型將該語意解析引擎所解析結果進行機器學習,以將結果傳送至語意解析資料庫。 The foregoing interactive verification system and method further include a learning program device that performs machine learning on the results of the semantic analysis engine through the model to transmit the results to the semantic analysis database.

前述的互動式檢核系統及方法,其中,該聊天機器人裝置係依據該使用者介面所連續收到該回覆訊息的時間間隔,評斷此次檢核的有效性。 In the aforementioned interactive verification system and method, the chat robot device judges the validity of the verification based on the time interval at which the reply message is continuously received by the user interface.

前述的互動式檢核系統及方法,其中,該聊天機器人裝置依據所取得之具有反向意含的問題訊息,評斷此次檢核的有效性。 In the aforementioned interactive verification system and method, the chat robot device judges the validity of the verification based on the obtained question message with reverse meaning.

前述的互動式檢核系統及方法,其中,該聊天機器人裝置所呈現之該問題訊息係以文字按鈕、圖片選答或文字填答的方式呈現,其中,該文字按鈕的問題訊息係透過按鈕給予選項,供該聊天機器人裝置將該經由文字按鈕選擇的回覆訊息轉換為文字;該圖片選答的問題訊息係透過圖 片提供選擇,供該聊天機器人裝置將該經由圖片選答的回覆訊息轉換為文字;以及該文字填答的問題訊息是透過文字形式表達該問題訊息,並接收文字形式的該回覆訊息。 In the foregoing interactive verification system and method, the question message presented by the chat robot device is presented in the form of a text button, a picture selection answer, or a text answer, wherein the question message of the text button is given by a button Option for the chat robot device to convert the reply message selected by the text button into text; The video provides options for the chat robot device to convert the reply message selected by the picture into text; and the question message filled in the text expresses the question message in text form and receives the reply message in text form.

前述的互動式檢核系統及方法,其中,該演算法模組將該回覆訊息透過語意解析資料庫執行關鍵字提取,而產生多維度斷詞的該回覆訊息,以在降低維度後解析該回覆訊息。 The foregoing interactive verification system and method, wherein the algorithm module performs keyword extraction through the semantic analysis database to generate a multi-dimensional word-breaking reply message to parse the reply after reducing the dimension message.

前述的互動式檢核系統及方法,其中,該分類模組是根據在語意解析資料庫中的分類模型分類該回覆訊息中的內容,且該依照領域配置的類別是設定於該分類模組的類別資料庫中。 The aforementioned interactive verification system and method, wherein the classification module classifies the content of the reply message according to the classification model in the semantic analysis database, and the category configured according to the domain is set in the classification module Category database.

前述的互動式檢核系統及方法,其中,該評分模組是根據該回覆訊息中內容的情緒詞彙的正向或負向的值域給予分數。 In the foregoing interactive verification system and method, wherein the scoring module is based on the positive or negative value range of the emotional vocabulary of the content in the reply message.

本發明之雙向互動的智能檢核系統,在現行網路與智慧型行動裝置的普及下,檢核的受測者可以不受到填答的時間與地點的限制,而能夠以更直覺的互動式對話,在即時通訊平台上與聊天機器人進行互動答詢的檢核,不僅可以增加填答率,也能夠藉由即時的互動機制和檢核過程中判斷問卷有效性的機制來增加問卷的準確率。 With the popularization of the current network and smart mobile devices, the bi-directional interactive intelligent inspection system of the present invention can be inspected without restriction of the time and location of the answer, and can be more intuitively interactive Conversation, the verification of interactive queries with chatbots on the instant messaging platform, not only can increase the answer rate, but also can increase the accuracy of the questionnaire through the real-time interactive mechanism and the mechanism to judge the validity of the questionnaire during the verification process .

11:使用者介面 11: User interface

12:聊天機器人裝置 12: chat robot device

13:檢核資料庫 13: Audit database

14:語意解析引擎 14: Semantic analysis engine

15:答覆資料庫 15: Reply database

16:學習程序裝置 16: learning program device

17:報表產生裝置 17: Report generation device

S1-S14:步驟 S1-S14: Step

第1圖為本發明之互動式檢核系統的系統架構示意圖;第2至3圖為本發明之使用者介面及聊天機器人模組 之使用示意圖;第4圖為本發明經過斷詞的回覆訊息之示意圖;以及第5圖為本發明之互動式檢核系統的操作流程示意圖。 Figure 1 is a schematic diagram of the system architecture of the interactive inspection system of the present invention; Figures 2 to 3 are the user interface and chat robot module of the present invention Fig. 4 is a schematic diagram of the reply message of the present invention after word breaking; and Fig. 5 is a schematic diagram of the operation flow of the interactive verification system of the invention.

本發明提供一種互動式檢核系統以及互動式檢核方法,如第1圖所示,該互動式檢核系統包括:使用者介面11、聊天機器人裝置12、檢核資料庫13、語意解析引擎14、答覆資料庫15、學習程序裝置16以及報表產生裝置17。 The present invention provides an interactive verification system and an interactive verification method. As shown in FIG. 1, the interactive verification system includes: a user interface 11, a chat robot device 12, a verification database 13, and a semantic analysis engine 14. Answer database 15, learning program device 16, and report generating device 17.

使用者介面11是用於接收使用者的語音、文字、圖片、選項等回覆訊息的操作介面,其可以社交軟體、通訊平台、網站、聊天室、或應用程式,使用者可以透過使用者介面11以語音輸入、文字輸入、點選等方式與聊天機器人對話或溝通。 The user interface 11 is an operation interface for receiving user's voice, text, pictures, options and other reply messages. It can be a social software, a communication platform, a website, a chat room, or an application. The user can use the user interface 11 Talk or communicate with chatbots by voice input, text input, and click.

聊天機器人裝置12係連接於使用者介面11以及檢核資料庫13,該聊天機器人裝置12由檢核資料庫13取得已經建置於檢核資料庫13中的問題訊息後,使用按鈕、文字、圖片、或其任意組合之形式主動呈現問題訊息於使用者介面11,如第2、3圖所示,俾於該使用者介面11接收到使用者的回覆訊息後,傳送該回覆訊息至語意解析引擎14。其中,當聊天機器人裝置12提供文字按鈕、圖片選答或文字填答的問題訊息時,該文字按鈕的問題訊息係透過按鈕或卡片的形式呈現選項,使用者根據選項選擇答案後,該聊天機器人裝置12將使用者所選擇的文字按鈕之回覆訊 息轉化為文字並儲存於答覆資料庫15;該圖片選答的問題訊息係在圖片設計不同區塊表示不同選項提供選擇,使用者點選區塊以回答回覆訊息,該聊天機器人裝置12將使用者所選擇的圖片區塊之回覆訊息轉換為相對應的文字,並將相對應的文字儲存於答覆資料庫15;該文字填答的問題訊息是由聊天機器人裝置12傳送檢核資料庫13的問題訊息,而使用者以文字形式回答回覆訊息,聊天機器人裝置12將使用者的文字回覆訊息儲存於答覆資料庫15;答覆資料庫15儲存前述經過該語意解析引擎所處理的該回覆訊息以提供該回覆訊息於報表產生裝置17。 The chat robot device 12 is connected to the user interface 11 and the audit database 13. After the chat robot device 12 obtains the question message that has been built in the audit database 13 from the audit database 13, it uses buttons, text, Pictures, or any combination thereof, actively present the question message to the user interface 11, as shown in Figures 2 and 3, after the user interface 11 receives the user's reply message, the reply message is sent to the semantic analysis Engine 14. Wherein, when the chat robot device 12 provides a text button, a picture selection answer, or a text filled question message, the question message of the text button presents an option in the form of a button or a card. After the user selects an answer according to the option, the chat robot The device 12 responds to the text button selected by the user The information is converted into text and stored in the answer database 15; the question message of the picture selection is provided in different blocks of the picture design to indicate different options. The user clicks the block to answer the reply message, and the chat robot device 12 sends the user The reply message of the selected picture block is converted into corresponding text, and the corresponding text is stored in the reply database 15; the question message filled in the text is sent by the chat robot device 12 to the verification database 13 Message, and the user answers the reply message in text form, the chatbot device 12 stores the user's text reply message in the reply database 15; the reply database 15 stores the aforementioned reply message processed by the semantic analysis engine to provide the reply message The reply message is to the report generating device 17.

語意解析引擎14包括演算法模組、分類模組以及評分模組,其中,該演算法模組將使用者的回覆訊息以自然語言處理的演算法分析其語意,主要是透過關鍵字提取,透過大量文本依照詞彙的詞性所組成的語意解析資料庫,將該回覆訊息的文句予以斷詞,以解析該回覆訊息,並以相同方式產生用於模型訓練的詞彙,如第4圖所示,經過斷詞的語句為多維度架構,在經過降低維度後,使得語句更容易解析。 The semantic analysis engine 14 includes an algorithm module, a classification module, and a scoring module, wherein the algorithm module analyzes the semantics of the user's reply message with a natural language processing algorithm, mainly through keyword extraction, through A large amount of text is a semantic analysis database composed of lexical parts of speech, and the sentence of the reply message is segmented to analyze the reply message, and the vocabulary used for model training is generated in the same way, as shown in Figure 4. Word-breaking sentences have a multi-dimensional structure, which makes the sentences easier to parse after lowering the dimensions.

語意解析引擎14的分類模組將經過前述解析的回覆訊息予以指派至依照產業領域配置的多個類別,分類模組包括類別資料庫以及分類機制,其中,類別資料庫配置有預先建置的不同類別以對應於檢核的不同產業領域,分類機制是建構於語意解析資料庫之上的分類模型,其對於各類別的相關連詞彙進行初步的指派與歸類,並藉由大量文 本反覆訓練分類模型的準確度,以教育產業的學習成效檢核為例,其所使用的類別有「授課方式」、「課程內容」、「考試評分方式」等,以第4圖為例,該回覆訊息將被歸類於「授課方式」的分類。 The classification module of the semantic analysis engine 14 assigns the parsed reply messages to multiple categories configured according to the industrial field. The classification module includes a category database and a classification mechanism, where the category database is configured with different pre-built The categories correspond to the different industrial fields under inspection. The classification mechanism is a classification model built on the semantic analysis database. It initially assigns and categorizes the related words of each category and uses a large number of documents. The accuracy of this repeated training classification model is based on the examination of the learning effectiveness of the education industry. The categories used are "teaching method", "course content", "examination scoring method", etc. Taking Figure 4 as an example, The reply message will be categorized in the "Teaching Method" category.

語意解析引擎14的評分模組根據經過分類模組所歸類的回覆訊息中的內容給予分數,例如,根據使用者的文字填答內容中的詞彙,特別是被定義帶有情緒意義的詞彙,判定其值域,值域分為正向與負向,且值域的量級與寬度將根據不同產業領域的檢核需求訂定,例如,以教育產業的學習成效檢核為例,值域可訂定於[-1,1]的區間內,如前述第4圖的範例,若「無趣」此一詞彙在計分的標籤資料庫中為負向的詞彙,則評分模組將第2圖中屬於「授課方式」分類的語句,根據情緒詞彙的負向程度給予評分,例如,「-0.63分」,並將前述的數值彙整於報表產生裝置。 The scoring module of the semantic analysis engine 14 gives a score based on the content of the reply message classified by the classification module, for example, filling in the vocabulary in the content according to the user's text, especially the vocabulary defined with emotional meaning, Judging its value range, the value range is divided into positive and negative directions, and the magnitude and width of the value range will be determined according to the inspection needs of different industrial fields. For example, in the case of the inspection of the learning effectiveness of the education industry, the value range It can be set in the range of [-1,1]. As in the example in Figure 4 above, if the word "uninteresting" is a negative word in the scoring tag database, the scoring module will The sentences belonging to the "teaching method" category in the figure are scored according to the negative degree of the emotional vocabulary, for example, "-0.63 points", and the aforementioned values are aggregated in the report generating device.

以下的表1為經過前述分類模組與評分模組所分類與評分的範例:

Figure 107109635-A0305-02-0010-1
Table 1 below is an example of classification and scoring by the aforementioned classification module and scoring module:
Figure 107109635-A0305-02-0010-1

以下示例為語意解析引擎14的訓練階段以及預測階段的範例,在訓練階段中,使用者所輸入的語句經過斷詞、詞性分析後得出下列表2的矩陣O,而根據詞性不同,有可能得出多個矩陣(例如:O1,O2,...,On);在將前述斷詞後所得到的高維度矩陣進行降低維度而得到下列表3的矩陣S(根據詞性的不同,有可能得出矩陣S1,S2,...,Sn);將矩陣S與類別值C放入分類模組以建立分類模型而得出模型A;再依據每個類別值的使用者輸入的矩陣S與分數V,使用評分模組建立模型而得出模型B(根據類別的不同,有可能得出矩陣B1,B2,...,Bn)。 The following example is an example of the training phase and prediction phase of the semantic analysis engine 14. In the training phase, the sentence input by the user is subjected to word segmentation and part-of-speech analysis to obtain the matrix O in Table 2 below. Depending on part of speech, it is possible Obtain multiple matrices (for example: O 1 , O 2 ,..., On n ); reduce the dimensions of the high-dimensional matrix obtained after the aforementioned word-breaking to obtain the matrix S of the following Table 3 (according to the difference of parts of speech , It is possible to get the matrix S 1 ,S 2 ,...,S n ); put the matrix S and the category value C into the classification module to create a classification model to get the model A; then according to the use of each category value The matrix S and the score V input by the user are modeled using the scoring module to obtain the model B (depending on the category, it is possible to obtain the matrix B 1 , B 2 , ..., B n ).

在預測階段中,使用者所輸入的語句經過斷詞、詞性分析後得出前述的矩陣O(根據詞性不同,有可能得出多個矩陣O1,O2,...,On);在將前述斷詞後所得到的高維度矩陣進行降低維度而得到矩陣S(根據詞性的不同,有可能得出矩陣S1,S2,...,Sn);將前述的矩陣S放入模型A中,以取得類別值C;根據前述的類別值C選擇對應的模型B,在透過矩陣S取得預測的分數。 In the prediction stage, the sentence input by the user is subjected to word segmentation and part-of-speech analysis to obtain the aforementioned matrix O (according to different parts of speech, it is possible to obtain multiple matrices O 1 , O 2 , ..., On n ); Reduce the dimensions of the high-dimensional matrix obtained after the aforementioned word breaking to obtain the matrix S (depending on the part of speech, it is possible to obtain the matrix S 1 , S 2 ,..., S n ); put the aforementioned matrix S Enter model A to obtain the category value C; select the corresponding model B according to the aforementioned category value C and obtain the predicted score through the matrix S.

例如:使用者輸入:這堂課教的內容實在太有趣了 For example: User input: The content of this lesson is too interesting

預測類別為:課程內容 The predicted category is: Course content

預測分數為:4 The predicted score is: 4

Figure 107109635-A0305-02-0012-3
Figure 107109635-A0305-02-0012-3

Figure 107109635-A0305-02-0012-4
Figure 107109635-A0305-02-0012-4

本發明的報表產生裝置17從答覆資料庫15中彙整前述經解析、斷詞的該回覆訊息、該分類模組的分類結果及該評分模組所給予的分數,經過統計後以文字或圖表形式產生報表,並藉由演算法模組歸納出利於決策的關鍵指標。 The report generating device 17 of the present invention aggregates the parsed and word-breaking reply message, the classification result of the classification module and the score given by the scoring module from the answer database 15, after statistics, in the form of text or chart Generate reports, and use the algorithm module to summarize key indicators that facilitate decision-making.

本發明更包括學習程序裝置16,其係透過模型將該語意解析引擎所解析結果進行機器學習,以將結果傳送至語意解析資料庫。 The present invention further includes a learning program device 16, which performs machine learning on the analysis results of the semantic analysis engine through the model to transmit the results to the semantic analysis database.

為了確保檢核過程的有效以及確認使用者是否確實答覆問題,可以透過該聊天機器人裝置12係藉由該使用者介面所連續收到該回覆訊息的時間間隔長短,確認使用者 填寫答覆的時間,以評斷此次檢核的有效性,該聊天機器人裝置12也可在傳送多個問題訊息之間,隨機傳送具有反向意含的問題訊息,以評斷此次檢核的有效性(例如,在第一個問題中詢問是否喜歡該項活動,並在第5題中反向訊問使用者是否不喜歡該項活動)。 In order to ensure the validity of the verification process and to confirm whether the user actually answers the question, the chat robot device 12 can continuously receive the reply message through the user interface through the user interface to confirm the user Fill in the time of the reply to judge the validity of the audit. The chat robot device 12 can also randomly send question messages with reverse meaning between multiple question messages to judge the effectiveness of the audit Sex (for example, ask if you like the activity in the first question, and ask the user if you don’t like the activity in question 5).

請參考第5圖的互動式檢核系統的操作流程示意圖,使用者啟用本發明之互動式檢核系統時,互動式檢核系統系統判斷使用者進入系統之途徑S1,由聊天機器人裝置會詢問使用者意圖S2,以進行身分之確認(若此次的檢核需要確認使用者身份則需提供同意身份綁定,若無此要求則不進行身分綁定)以判斷使用者進入的檢核系統,詢問意圖以進入檢核系統可為三種:提供代碼進入檢核、直述進入檢核(例如跟聊天機器人裝置說:我想填答OO講座的問卷),以及點選按鈕進入檢核(使用者與聊天機器人裝置進行互動時,在聊天機器人裝置詢問使用者之意圖時,會提供使用者快速回覆之按鈕供使用者進行點按),則讓使用者進入檢核S4,聊天機器人裝置詢問檢核的類別S4,判斷是否有暫存S5,並根據該檢核是否具有可暫存之特性來檢視該檢核於該身分是否存在歷史填答紀錄,而詢問是否接續上次的填答S7,若繼續則接續上次的檢核S8;或判斷無暫存內容後,由聊天機器人裝置說明檢核內容S9,並與聊天機器人裝置互動檢核過程S10,在結束互動檢核過程後,檢核互動系統確認是否提交回覆訊息S11,若為是,則匯入資料庫S12,若否,則由聊天機器人裝置詢問意圖 S2;接著在S12後,詢問是否繼續填答其他問題S13,若是,回到步驟S4,若為否,則結束本次檢核S14;若在詢問是否接續上次的填答S7或是否提交回覆訊息S11中選擇為否,則回到聊天機器人裝置會詢問使用者意圖S2。 Please refer to the operation flow diagram of the interactive verification system in FIG. 5. When the user activates the interactive verification system of the present invention, the interactive verification system system determines the user's way of entering the system S1, and the chat robot device will ask The user intends S2 to confirm the identity (if the verification needs to confirm the user's identity, it is necessary to provide consent identity binding, and if there is no such requirement, the identity binding will not be performed) to determine the verification system the user enters There are three types of inquiries about intention to enter the verification system: providing code to enter the verification, direct statement to enter the verification (for example, talking to the chat robot device: I want to fill in the questionnaire for the OO lecture), and click the button to enter the verification (use When the user interacts with the chat robot device, when the chat robot device queries the user's intention, the user will be provided with a quick reply button for the user to click), then the user is allowed to enter the verification S4, and the chat robot device Check the category of S4, determine whether there is a temporary storage S5, and check whether there is a historical answer record in the identity according to whether the review has temporary characteristics, and ask whether to continue the previous answer S7, If it continues, continue with the previous verification S8; or after judging that there is no temporary storage content, the chat robot device will explain the verification content S9, and interact with the chat robot device verification process S10, after the interactive verification process is completed, the verification The interactive system confirms whether to submit the reply message S11, if it is, it is imported into the database S12, if not, the chat robot device asks the intention S2; then after S12, ask whether to continue to answer other questions S13, if yes, go back to step S4, if not, then end the audit S14; if asking whether to continue the previous answer S7 or whether to submit a reply If No is selected in the message S11, returning to the chat robot device will ask the user's intention S2.

上列詳細說明乃針對本發明之一可行實施例進行具體說明,惟該實施例並非用以限制本發明之專利範圍,凡未脫離本發明技藝精神所為之等效實施或變更,均應包含於本案之專利範圍中。 The above detailed description is a specific description of a feasible embodiment of the present invention, but this embodiment is not intended to limit the patent scope of the present invention, and any equivalent implementation or change without departing from the technical spirit of the present invention should be included in The patent scope of this case.

綜上所述,本案不僅於技術思想上確屬創新,並具備習用之傳統方法所不及之上述多項功效,已充分符合新穎性及進步性之法定發明專利要件,爰依法提出申請,懇請貴局核准本件發明專利申請案,以勵發明,至感德便。 To sum up, this case is not only innovative in terms of technical ideas, but also possesses the above-mentioned multiple functions that traditional methods do not match, which has fully met the requirements of novelty and progressive legal invention patents. Approve this application for a patent for invention to encourage invention and achieve good results.

11:使用者介面 11: User interface

12:聊天機器人裝置 12: chat robot device

13:檢核資料庫 13: Audit database

14:語意解析引擎 14: Semantic analysis engine

15:答覆資料庫 15: Reply database

16:學習程序裝置 16: learning program device

17:報表產生裝置 17: Report generation device

Claims (10)

一種智能檢核系統,其包括:使用者介面;聊天機器人裝置,其係連接於該使用者介面,該聊天機器人裝置係用以取得問題訊息以主動呈現該問題訊息於該使用者介面,俾於該使用者介面接收到回覆訊息後,傳送該回覆訊息;語意解析引擎,其係包括演算法模組、分類模組以及評分模組,其中,在接收該回覆訊息後,該演算法模組將該回覆訊息經過關鍵字提取以解析該回覆訊息,再將經解析的該回覆訊息傳送至該分類模組及該評分模組,以供該分類模組將該經解析的回覆訊息予以分類至依照領域配置的類別,並令該評分模組根據分類後的該回覆訊息中的內容給予分數;以及報表產生裝置,其彙整經該語意解析引擎所解析的該回覆訊息、該分類模組的分類結果及該評分模組所給予的分數以產生報表;其中,該聊天機器人裝置係依據該使用者介面所連續收到該回覆訊息的時間間隔及依據所取得之具有反向意含的問題訊息,評斷此次檢核的有效性,該評分模組是根據該回覆訊息中內容的情緒詞彙的正向或負向的值域給予分數。 An intelligent inspection system includes: a user interface; a chat robot device connected to the user interface, the chat robot device is used to obtain a problem message to actively present the problem message to the user interface, so as to After receiving the reply message, the user interface sends the reply message; the semantic analysis engine includes an algorithm module, a classification module, and a scoring module. After receiving the reply message, the algorithm module will The reply message is extracted by keywords to parse the reply message, and then the parsed reply message is sent to the classification module and the scoring module for the classification module to classify the parsed reply message to The category configured by the domain, and the scoring module is given a score according to the content of the categorized reply message; and a report generation device that aggregates the reply message parsed by the semantic analysis engine and the classification result of the classification module And the score given by the scoring module to generate a report; wherein, the chat robot device is judged according to the time interval of continuously receiving the reply message by the user interface and according to the obtained question message with reverse meaning For the validity of this check, the scoring module is based on the positive or negative value range of the emotional vocabulary in the reply message. 根據申請專利範圍第1項所述的智能檢核系統,進一步包括答覆資料庫,其係用以儲存經過該語意解析引擎 所處理的該回覆訊息以提供該回覆訊息於報表產生裝置,或者,進一步包括學習程序裝置,其係透過模型將該語意解析引擎所解析結果進行機器學習,以將結果傳送至語意解析資料庫。 The intelligent verification system according to item 1 of the patent application scope further includes a reply database, which is used to store the semantic analysis engine The processed reply message is used to provide the reply message to the report generation device, or further includes a learning program device, which performs machine learning on the analysis result of the semantic analysis engine through the model to send the result to the semantic analysis database. 根據申請專利範圍第1項所述的智能檢核系統,其中,該聊天機器人裝置所呈現之該問題訊息係以文字按鈕、圖片選答或文字填答的方式呈現,其中,該文字按鈕的問題訊息係透過按鈕給予選項,供該聊天機器人裝置將該經由文字按鈕選擇的回覆訊息轉換為文字;該圖片選答的問題訊息係透過圖片提供選擇,供該聊天機器人裝置將該經由圖片選答的回覆訊息轉換為文字;以及該文字填答的問題訊息是透過文字形式表達該問題訊息,並接收文字形式的該回覆訊息。 According to the intelligent verification system described in item 1 of the patent application scope, wherein the question message presented by the chat robot device is presented in the form of a text button, a picture selection answer, or a text answer, in which the question of the text button The message is given an option via a button for the chat robot device to convert the reply message selected by the text button into text; the question message selected by the picture is selected by the picture for the chat robot device to select the answer message by the picture The reply message is converted into text; and the question message filled in the text is to express the question message in text form and receive the reply message in text form. 根據申請專利範圍第1項所述的智能檢核系統,其中,該演算法模組將該回覆訊息透過語意解析資料庫執行關鍵字提取,而產生多維度斷詞的該回覆訊息,以在降低維度後,解析該回覆訊息。 According to the intelligent verification system described in item 1 of the patent application scope, the algorithm module executes keyword extraction through the semantic analysis database to generate the multi-dimensional word-breaking reply message in order to reduce After the dimension, parse the reply message. 根據申請專利範圍第1項所述的智能檢核系統,其中,該分類模組是根據在語意解析資料庫中的分類模型分類該回覆訊息中的內容,且該依照領域配置的類別是設定於該分類模組的類別資料庫中。 The intelligent verification system according to item 1 of the patent application scope, wherein the classification module classifies the content of the reply message according to the classification model in the semantic analysis database, and the category configured according to the domain is set at The category database of the classification module. 一種智能檢核方法,其包括: 取得問題訊息;透過聊天機器人裝置主動呈現該問題訊息於使用者介面;接收回覆訊息以傳送該回覆訊息至語意解析引擎;透過該語意解析引擎的演算法模組將該回覆訊息經過關鍵字提取以解析該回覆訊息;透過該語意解析引擎的分類模組將該經解析的回覆訊息予以分類至依照領域配置的類別;透過該語意解析引擎的評分模組根據分類後的該回覆訊息中的內容給予分數;以及彙整經該語意解析引擎所解析的該回覆訊息、該分類模組的分類結果及該評分模組所給予的分數以透過報表產生裝置產生報表;其中,該聊天機器人裝置係依據所連續收到的該回覆訊息的時間間隔及依據所取得之具有反向意含的問題訊息,評斷此次檢核的有效性,該評分模組是根據該回覆訊息中內容的情緒詞彙的正向或負向的值域給予分數。 An intelligent inspection method, including: Obtain the question message; actively present the question message to the user interface through the chat robot device; receive the reply message to send the reply message to the semantic analysis engine; extract the reply message through keyword extraction through the algorithm module of the semantic analysis engine Parse the reply message; classify the parsed reply message to the category configured by the domain through the classification module of the semantic parsing engine; give the scoring module of the semantic parsing engine based on the content of the reply message after classification A score; and a summary of the reply message parsed by the semantic analysis engine, the classification result of the classification module and the score given by the scoring module to generate a report through a report generation device; wherein the chat robot device is based on the continuous The time interval of the received reply message and the question message obtained with the reverse meaning are used to judge the validity of the review. The scoring module is based on the positive or negative emotion words in the reply message. Scores are given in the negative range. 根據申請專利範圍第6項所述的智能檢核方法,進一步包括:儲存經過該語意解析引擎所處理的該回覆訊息於答覆資料庫,或者,進一步包括:透過模型將該語意解析引擎所解析結果進行機器學習,以將結果傳送至語意解析資料庫。 The intelligent verification method according to item 6 of the patent application scope further includes: storing the reply message processed by the semantic analysis engine in the reply database, or, further comprising: analyzing the result of the semantic analysis engine through the model Perform machine learning to send the results to the semantic analysis database. 根據申請專利範圍第6項所述的智能檢核方法,其中, 該聊天機器人裝置係提供:透過按鈕給予選項,供該聊天機器人裝置將該經由文字按鈕選擇的回覆訊息轉化為文字;透過圖片提供選擇,供該聊天機器人裝置將該經由圖片選答的回覆訊息轉化為文字;以及透過文字形式表達該問題訊息,並接收文字形式的該回覆訊息。 According to the intelligent verification method described in item 6 of the patent application scope, wherein, The chat robot device provides: an option given by a button for the chat robot device to convert the reply message selected by the text button into text; a choice provided by a picture for the chat robot device to convert the reply message selected by the picture As text; and express the question message in text form and receive the reply message in text form. 根據申請專利範圍第6項所述的智能檢核方法,其中,該演算法模組將該回覆訊息透過語意解析資料庫執行關鍵字提取,而產生多維度斷詞的該回覆訊息,以在降低維度後,解析該回覆訊息。 According to the intelligent verification method described in Item 6 of the patent application scope, the algorithm module performs keyword extraction through the semantic analysis database on the reply message, and generates a multi-dimensional word-breaking reply message to reduce After the dimension, parse the reply message. 根據申請專利範圍第6項所述的智能檢核方法,其中,該分類模組是根據在語意解析資料庫中的分類模型分類該回覆訊息中的內容,且該依照領域配置的類別是設定於該分類模組的類別資料庫中。 The intelligent verification method according to item 6 of the patent application scope, wherein the classification module classifies the content of the reply message according to the classification model in the semantic analysis database, and the category configured according to the domain is set at The category database of the classification module.
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US20140324541A1 (en) * 2013-04-30 2014-10-30 International Business Machines Corporation Using real-time online analytics to automatically generate an appropriate measurement scale

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TWM468100U (en) * 2013-04-25 2013-12-11 Univ Chien Hsin Sci & Tech Peer assessment system
US20140324541A1 (en) * 2013-04-30 2014-10-30 International Business Machines Corporation Using real-time online analytics to automatically generate an appropriate measurement scale

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