CN107506349A - A kind of user's negative emotions Forecasting Methodology and system based on network log - Google Patents
A kind of user's negative emotions Forecasting Methodology and system based on network log Download PDFInfo
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- CN107506349A CN107506349A CN201710661868.XA CN201710661868A CN107506349A CN 107506349 A CN107506349 A CN 107506349A CN 201710661868 A CN201710661868 A CN 201710661868A CN 107506349 A CN107506349 A CN 107506349A
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- 238000000034 method Methods 0.000 title claims abstract description 24
- 230000011218 segmentation Effects 0.000 claims abstract description 20
- 238000000605 extraction Methods 0.000 claims abstract description 11
- 238000005259 measurement Methods 0.000 claims abstract description 11
- 241001269238 Data Species 0.000 claims description 7
- 238000013481 data capture Methods 0.000 claims description 5
- 238000011430 maximum method Methods 0.000 claims description 4
- 230000007935 neutral effect Effects 0.000 claims description 4
- 238000011524 similarity measure Methods 0.000 claims description 4
- 239000000284 extract Substances 0.000 claims description 3
- 238000012545 processing Methods 0.000 abstract description 5
- 238000013135 deep learning Methods 0.000 description 4
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Abstract
The invention discloses a kind of user's negative emotions Forecasting Methodology based on network log and system, method to include：Step 1) obtains the network log data of user；Step 2) is directed to above network log data, obtains Client-initiated and actively searches for data, and word extraction is scanned for it；Step 3) segments to search term, forms the multiple words divided according to property；Step 4) the sensitive word preset by word segmentation result and in advance carries out Semantic Similarity Measurement；Step 5) judges whether sensitive word matching succeeds, and carry out the negative emotions prediction of user accordingly according to the degree of approximation of Semantic Similarity Measurement.The present invention can early have found by the network log data for user, carry out intervention processing to states such as the Dangerous Internet speech of user and negative tendencies.
Description
Technical field
The invention belongs to big data field, belongs to a kind of negative emotions based on deep learning and natural language processing technique
Forecasting system.
Background technology
In recent years in school, students ' negative emotions when school side thinks of, for this reason, it may be necessary to which a kind of user's negative emotions are predicted
System or method.
The content of the invention
The technical problems to be solved by the invention are to provide a kind of user's negative emotions Forecasting Methodology based on network log
And system.
It is as follows that the present invention solves the technical scheme that above-mentioned technical problem is taken：
A kind of user's negative emotions Forecasting Methodology based on network log, including：
Step 1) obtains the network log data of user；
Step 2) is directed to above network log data, obtains Client-initiated and actively searches for data, word is scanned for it
Extraction；
Step 3) segments to search term, forms the multiple words divided according to property；
Step 4) the sensitive word preset by word segmentation result and in advance carries out Semantic Similarity Measurement；
Step 5) judges whether sensitive word matching succeeds according to the degree of approximation of Semantic Similarity Measurement；
Step 6) matches according to above word segmentation result with preset interrogative to judge whether it belongs to doubt statement, and root
The negative emotions of user are judged according to the result of sensitive word matching and interrogative matching.
Preferably, the sensitive word matching of multiple step and interrogative matching result more than, judge that user's is negative
Whether mood aggravates.
Preferably, in step 1), including：
Campus up-downgoing network data is mirrored to collector；
Collector network interface card is monitored, while http protocol datas bag is carried out to solve package package operation；
To up-downgoing data pair, and the data to completing pairing are localized storage.
Preferably, in step 2), including：Data are actively searched for Client-initiated using regular expression to scan for
Word extracts.
Preferably, in step 3), including：
The Chinese short sentence in search term is segmented based on Forward Maximum Method algorithm, formed according to the more of property division
Individual word.
Preferably, Similarity Measure semantic between the word, is specifically included：
Obtain the text data for needing to train；
Using word occurrence number in text and word segmentation result as input data；
Calculating is modeled to the replaceable probability of word with neutral net；Finally give semantic similarity between word.
A kind of user's negative emotions forecasting system based on network log, including：
Data capture unit, for obtaining the network log data of user；
Data extracting unit, for for above network log data, obtaining Client-initiated and actively searching for data, to it
Scan for word extraction；
Data participle unit, for being segmented to search term, form the multiple words divided according to property；
Similarity-rough set unit, for by word segmentation result and sensitive word preset in advance carry out Semantic Similarity Measurement；
Interrogative judging unit, for being matched according to above word segmentation result with preset interrogative to judge whether it belongs to
Doubt statement；
Negative emotions predicting unit, the result for being matched according to the matching of above sensitive word and interrogative judge that user's is negative
Face mood.
Preferably, sensitive word multiple more than matching and interrogative matching result, the negative emotions of user are judged
Whether aggravate.
Preferably, the data capture unit, is further used for：
Campus up-downgoing network data is mirrored to collector；
Collector network interface card is monitored, while http protocol datas bag is carried out to solve package package operation；
To up-downgoing data pair, and the data to completing pairing are localized storage.
Preferably, the data extracting unit, is further used for：Client-initiated is actively searched using regular expression
Rope data scan for word extraction.
After the present invention takes such scheme, monitoring related data can be delivered by student's focus of attention and student's speech
Collection, classification, crawl keyword carry out intelligent semantic comparative analysis, the ideology and politics dynamic of student are understood, so as to aid in establishing
The personalized, Education system of ideology and politics of precision.The states such as the Dangerous Internet speech of student and negative tendency are found early,
Carry out intervention processing.
Other features and advantages of the present invention will be illustrated in the following description, also, partly becomes from specification
Obtain it is clear that or being understood by implementing the present invention.The purpose of the present invention and other advantages can be by the explanations write
Specifically noted structure is realized and obtained in book, claims and accompanying drawing.
Brief description of the drawings
The present invention is described in detail below in conjunction with the accompanying drawings, to cause the above-mentioned advantage of the present invention definitely.Its
In,
Fig. 1 is the schematic flow sheet of user's negative emotions Forecasting Methodology of the invention based on network log；
Fig. 2 is the structural representation of user's negative emotions forecasting system of the invention based on network log.
Embodiment
Embodiments of the present invention are described in detail below with reference to drawings and Examples, and how the present invention is applied whereby
Technological means solves technical problem, and the implementation process for reaching technique effect can fully understand and implement according to this.Need to illustrate
As long as not forming conflict, each embodiment in the present invention and each feature in each embodiment can be combined with each other,
The technical scheme formed is within protection scope of the present invention.
In addition, can be in the department of computer science of such as one group computer executable instructions the flow of accompanying drawing illustrates the step of
Performed in system, although also, show logical order in flow charts, in some cases, can be with different from herein
Order perform shown or described step.
Embodiment one：
As shown in figure 1, a kind of user's negative emotions Forecasting Methodology based on network log, including：
Step 1) obtains the network log data of user；
Step 2) is directed to above network log data, obtains Client-initiated and actively searches for data, word is scanned for it
Extraction；
Step 3) segments to search term, forms the multiple words divided according to property；
Step 4) the sensitive word preset by word segmentation result and in advance carries out Semantic Similarity Measurement；
Step 5) judges whether sensitive word matching succeeds according to the degree of approximation of Semantic Similarity Measurement；
Step 6) matches according to above word segmentation result with preset interrogative to judge whether it belongs to doubt statement, and root
The negative emotions of user are judged according to the result of sensitive word matching and interrogative matching.
The present invention can be by the network log data for user, to the Dangerous Internet speech of user and negative tendency etc.
State is found early, carries out intervention processing.
Embodiment two：
Illustrated for embodiment one, these, it is preferred to, the repeatedly sensitive word matching and query of step more than
Word matching result, judges whether the negative emotions of user aggravate.
Preferably, in step 1), including：
Campus up-downgoing network data is mirrored to collector；
Collector network interface card is monitored, while http protocol datas bag is carried out to solve package package operation；
To up-downgoing data pair, and the data to completing pairing are localized storage.
Preferably, in step 2), including：Data are actively searched for Client-initiated using regular expression to scan for
Word extracts.
Preferably, in step 3), including：
The Chinese short sentence in search term is segmented based on Forward Maximum Method algorithm, formed according to the more of property division
Individual word.
Preferably, Similarity Measure semantic between the word, it is based primarily upon deep learning word2vec algorithms,
Specifically include：
Obtain the text data for needing to train；
Using word occurrence number in text and word segmentation result as input data；
Calculating is modeled to the replaceable probability of word with neutral net；Finally give semantic similarity between word.
In a specific embodiment, student (user) negative sense emotional prediction algorithm overall procedure is as follows：
1. network log data acquisition；
2. utilizing regular expression, word extraction is scanned for network data；
3. a pair search term segments；
4. utilizing deep learning algorithm word2vec, the word segmentation result and sensitive word preset in advance to 3 steps carry out semantic
Similarity Measure；
5. the semantic degree of approximation is more than 90%, being defined as sensitive word, the match is successful；
6. carrying out interrogative matching to the word segmentation result of 3 steps simultaneously, then negative sense mood order of severity exacerbation that the match is successful；
Wherein, for network log and placement data acquisition, it includes：
A) network log gatherer process is as follows：
I. campus up-downgoing network data is mirrored to collector；
Ii. capture program monitors to collector network interface card；
Iii. http protocol datas bag is carried out solving package package operation；
Iv. to up-downgoing data pair；
V. the data for completing pairing are localized storage；
Segmentation methods, mainly include：
A) division of word nature is carried out to Chinese short sentence, such as：" today, weather was pretty good ", the result after participle are：It is " modern
My god, weather is pretty good "；
B) algorithm is realized using Forward Maximum Method algorithm；
Deep learning word2vec algorithms, mainly include：
A) using word occurrence number in text and word segmentation result as input；
B) calculating is modeled to the replaceable probability of word with neutral net；
C) semantic similarity between word is finally given.
After the present invention takes such scheme, monitoring related data can be delivered by student's focus of attention and student's speech
Collection, classification, crawl keyword carry out intelligent semantic comparative analysis, the ideology and politics dynamic of student are understood, so as to aid in establishing
The personalized, Education system of ideology and politics of precision.The states such as the Dangerous Internet speech of student and negative tendency are found early,
Carry out intervention processing.
Embodiment three：
Corresponding with above method embodiment, the invention also discloses a kind of user's negative emotions based on network log are pre-
Examining system, including：
Data capture unit, for obtaining the network log data of user；
Data extracting unit, for for above network log data, obtaining Client-initiated and actively searching for data, to it
Scan for word extraction；
Data participle unit, for being segmented to search term, form the multiple words divided according to property；
Similarity-rough set unit, for by word segmentation result and sensitive word preset in advance carry out Semantic Similarity Measurement；
Interrogative judging unit, for being matched according to above word segmentation result with preset interrogative to judge whether it belongs to
Doubt statement；
Negative emotions predicting unit, the result for being matched according to the matching of above sensitive word and interrogative judge that user's is negative
Face mood.
Preferably, sensitive word multiple more than matching and interrogative matching result, the negative emotions of user are judged
Whether aggravate.
Preferably, the data capture unit, is further used for：
Campus up-downgoing network data is mirrored to collector；
Collector network interface card is monitored, while http protocol datas bag is carried out to solve package package operation；
To up-downgoing data pair, and the data to completing pairing are localized storage.
Preferably, the data extracting unit, is further used for：Client-initiated is actively searched using regular expression
Rope data scan for word extraction.
After the present invention takes such scheme, monitoring related data can be delivered by student's focus of attention and student's speech
Collection, classification, crawl keyword carry out intelligent semantic comparative analysis, the ideology and politics dynamic of student are understood, so as to aid in establishing
The personalized, Education system of ideology and politics of precision.The states such as the Dangerous Internet speech of student and negative tendency are found early,
Carry out intervention processing.
It should be noted that for above method embodiment, in order to be briefly described, therefore it is all expressed as a series of
Combination of actions, but those skilled in the art should know, the application is not limited by described sequence of movement because
According to the application, some steps can use other orders or carry out simultaneously.Secondly, those skilled in the art should also know
Know, embodiment described in this description belongs to preferred embodiment, involved action and module not necessarily the application
It is necessary.
It should be understood by those skilled in the art that, embodiments herein can be provided as method, system or computer program
Product.Therefore, the application can use the reality in terms of complete hardware embodiment, complete software embodiment or combination software and hardware
Apply the form of example.
Moreover, the application can use the computer for wherein including computer usable program code in one or more can use
The computer program product that storage medium is implemented on (including but is not limited to magnetic disk storage, CD-ROM, optical memory etc.)
Form.
Finally it should be noted that：The preferred embodiments of the present invention are the foregoing is only, are not intended to limit the invention,
Although the present invention is described in detail with reference to the foregoing embodiments, for those skilled in the art, it still may be used
To be modified to the technical scheme described in foregoing embodiments, or equivalent substitution is carried out to which part technical characteristic.
Within the spirit and principles of the invention, any modification, equivalent substitution and improvements made etc., it should be included in the present invention's
Within protection domain.
Claims (10)
1. a kind of user's negative emotions Forecasting Methodology based on network log, including：
Step 1) obtains the network log data of user；
Step 2) is directed to above network log data, obtains Client-initiated and actively searches for data, and word extraction is scanned for it；
Step 3) segments to search term, forms the multiple words divided according to property；
Step 4) the sensitive word preset by word segmentation result and in advance carries out Semantic Similarity Measurement；
Step 5) judges whether sensitive word matching succeeds according to the degree of approximation of Semantic Similarity Measurement；
Step 6) matches to judge whether it belongs to doubt statement, and according to quick according to above word segmentation result with preset interrogative
The result of the matching of sense word and interrogative matching judges the negative emotions of user.
2. user's negative emotions Forecasting Methodology according to claim 1 based on network log, it is characterised in that by with
The sensitive word matching of upper multiple step and interrogative matching result, judge whether the negative emotions of user aggravate.
3. user's negative emotions Forecasting Methodology according to claim 1 based on network log, it is characterised in that step 1)
In, including：
Campus up-downgoing network data is mirrored to collector；
Collector network interface card is monitored, while http protocol datas bag is carried out to solve package package operation；
To up-downgoing data pair, and the data to completing pairing are localized storage.
4. user's negative emotions Forecasting Methodology according to claim 1 based on network log, it is characterised in that step 2)
In, including：Data are actively searched for Client-initiated using regular expression and scan for word extraction.
5. user's negative emotions Forecasting Methodology according to claim 1 based on network log, it is characterised in that step 3)
In, including：
The Chinese short sentence in search term is segmented based on Forward Maximum Method algorithm, forms the multiple words divided according to property
Language.
6. user's negative emotions Forecasting Methodology according to claim 1 based on network log, it is characterised in that institute's predicate
Semantic Similarity Measure, is specifically included between language：
Obtain the text data for needing to train；
Using word occurrence number in text and word segmentation result as input data；
Calculating is modeled to the replaceable probability of word with neutral net；Finally give semantic similarity between word.
7. a kind of user's negative emotions forecasting system based on network log, including：
Data capture unit, for obtaining the network log data of user；
Data extracting unit, for for above network log data, obtaining Client-initiated and actively searching for data, carried out to it
Search term extracts；
Data participle unit, for being segmented to search term, form the multiple words divided according to property；
Similarity-rough set unit, for by word segmentation result and sensitive word preset in advance carry out Semantic Similarity Measurement；
Interrogative judging unit, for being matched according to above word segmentation result with preset interrogative to judge whether it belongs to query
Sentence；
Negative emotions predicting unit, the result for being matched according to the matching of above sensitive word and interrogative judge the negative feelings of user
Thread.
8. user's negative emotions forecasting system according to claim 7 based on network log, it is characterised in that by with
Upper multiple sensitive word matching and interrogative matching result, judge whether the negative emotions of user aggravate.
9. user's negative emotions forecasting system according to claim 7 based on network log, it is characterised in that the number
According to acquiring unit, it is further used for：
Campus up-downgoing network data is mirrored to collector；
Collector network interface card is monitored, while http protocol datas bag is carried out to solve package package operation；
To up-downgoing data pair, and the data to completing pairing are localized storage.
10. user's negative emotions forecasting system according to claim 1 based on network log, it is characterised in that described
Data extracting unit, it is further used for：Data are actively searched for Client-initiated using regular expression and scan for word extraction.
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