CN110134955A - A kind of semantic processes method - Google Patents
A kind of semantic processes method Download PDFInfo
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- CN110134955A CN110134955A CN201910395991.0A CN201910395991A CN110134955A CN 110134955 A CN110134955 A CN 110134955A CN 201910395991 A CN201910395991 A CN 201910395991A CN 110134955 A CN110134955 A CN 110134955A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/30—Semantic analysis
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Abstract
The present invention provides a kind of semantic processes method, which comprises is analyzed and processed to media, the analysis processing includes that sentence conversion meaning randomization processing is carried out to each category feature such as temporal aspect, protensive features, frequecy characteristic, environmental characteristic, the process object includes but is not limited to word and word, word and word, word and word, word and word, word and sentence, sentence and word, sentence and sentence, paragraph and paragraph, sentence and paragraph, paragraph and sentence.This method can be used for being promoted the effect of semantic processes, increase the semantic degree of association in front and back.
Description
Technical field
The present invention relates to natural semantic domain, especially a kind of semantic processes method.
Background technique
In artificial intelligence technology, semantic understanding and processing are piths naturally.With the hair of artificial intelligence technology
Exhibition, semantic processes on consumer electronics using more and more extensive.There are many have semantic processes function on the market now
Product, such as the small ice of Microsoft.These products can carry out corresponding feedback by understanding the semantic information of user.Existing tool
The product of standby semantic processes function is fed back just for previous information.When the special statuss such as information against errors or ambiguity
When, if product can not correctly recognize the situation, error feedback can be carried out according to the information judging result of mistake.
Common solution is by context understanding optimum results.However, the prior art is logical when handling context
The methods of weighted average feature vector is commonly used to realize that frequecy characteristic is handled, and this can still result in a large amount of front and back timing in media
The omission of feature, protensive features.
Summary of the invention
The present invention proposes a kind of semantic processes method, in the process can be by error message judging result for solving semantic processes
The problem of interference.Technical solution of the present invention is as follows:
Media input；
Media are analyzed and processed, the analysis processing includes to temporal aspect, protensive features, frequecy characteristic, environmental characteristic
Carry out sentence conversion meaning randomization processing etc. each category feature, the process object includes but is not limited to word and word, word and word, word with
Word, word and word, word and sentence, sentence and word, sentence and sentence, paragraph and paragraph, sentence and paragraph, paragraph and sentence；
Processing result output；
Optionally, described that media are handled, comprising: it is accumulative to handle, at the information for the input of Screening Treatment continuous-stable
Reason, is analyzed and processed protensive features, frequecy characteristic;Timing sequence process, for handling the letter that having time is successive, and the period crosses over
Breath, guarantees the semantic coherence of context;Mixing semantic processes, the media information of the different dimensions for that will input, before
Received information, and processed information etc. carry out mixing and analysis result are calculated.
The present invention can at least bring following the utility model has the advantages that increasing the semantic degree of association in front and back, promote artificial intelligence product
To the fault-tolerant ability and understandability of special circumstances semanteme.
Detailed description of the invention
In attached drawing: Fig. 1 is a kind of flow chart of semantic processes method of the present invention.
In attached drawing: Fig. 2 is the flow chart that the present invention handles media.
Specific embodiment
A specific embodiment of the invention is described in further details with reference to the accompanying drawing.
As shown in Figure 1, the present invention discloses a kind of semantic processes method, content includes:
Media input；
Media are handled, which includes but is not limited to word and word, word and word, word and word, word and word, word and sentence, sentence
With word, sentence and sentence, paragraph and paragraph, sentence and paragraph, temporal aspect, protensive features, the frequecy characteristic of paragraph and sentence, and
The processing of the sentence of environment and all kinds of characteristic probabilities conversion meaning；
Specific steps include: accumulative processing, for the information processing of Screening Treatment continuous-stable input, to protensive features, frequency
Feature is analyzed and processed;Timing sequence process guarantees the language of context for handling the information that having time is successive, and the period crosses over
Adopted continuity;Mix semantic processes, the media information of the different dimensions for that will input, received information before, and
Processed information etc. carries out mixing and analysis result is calculated；
Processing result output.
As shown in Fig. 2, the flow chart that the present invention handles media, content include:
Accumulative processing carries out at analysis protensive features, frequecy characteristic for the information processing of Screening Treatment continuous-stable input
Reason;
Timing sequence process guarantees the semantic coherence of context for handling the information that having time is successive, and the period crosses over;
Mix semantic processes, the media information of the different dimensions for that will input, received information before, and located
Information managed etc. carries out mixing and analysis result is calculated.
The above description of this invention is only example, is not restricted to particular embodiments described above.For this field
For technical staff, any equivalent modifications and substitutions to the present invention are also within the scope of the present invention.Therefore, not
It is detached from made equal transformation and modification under the spirit and scope of the present invention, should all be covered within the protection scope of the present invention.
Claims (11)
1. the present invention discloses a kind of semantic processes method, which is characterized in that the described method includes:
Obtain media；
Signature analysis processing is carried out to media, the signature analysis processing includes but is not limited to accumulative processing, timing sequence process, mixing
Semantic processes, the accumulative processing is for being analyzed and processed protensive features, frequecy characteristic, and the timing sequence process is for handling
The information that having time is successive, the period crosses over, to guarantee the semantic coherence of context, the mixing semantic processes are used for will be defeated
The media information of the different dimensions entered, before received information, processed information etc. carry out mixing be calculated
Analyze result；
Wherein, the object of signature analysis processing includes but is not limited to word and word, word and word, word and word, word and word, word with
Sentence, sentence and word, sentence and sentence, paragraph and paragraph, sentence and paragraph, the feature between paragraph and sentence；
It is fed back according to analysis and processing result.
2. according to the method described in claim 1, the acquisition media include but is not limited to: actively or passively being carried out to media
It obtains, it is characterised in that the input of media information contained in the method.
3. according to the method described in claim 1, described be analyzed and processed media, content further include:
Media are cut, Cutting Length type includes but is not limited to: equal, close or different；It is characterized by: every section
Media fragment includes complete information.
4. according to the method described in claim 1, the temporal aspect including but not limited to: the time of the information segment of media is suitable
Sequence characteristics；It is characterized by: temporal aspect is believed including but not limited in media information segment with the part of time correlation and all
Breath.
5. according to the method described in claim 1, the protensive features are including but not limited to each, every kind of media information piece
The lasting or continuous feature of section；It is characterized by: protensive features sort including but not limited to each, every kind of media information segment
Rule Information.
6. according to the method described in claim 5, the type of the protensive features including but not limited to: lasting occur, be separated out
Existing, unordered appearance etc..
7. according to the method described in claim 1, the frequecy characteristic including but not limited to: in fixation, be not fixed in the period,
The frequecy characteristic that the information segment of media occurs.
8. according to the method described in claim 1, the environmental characteristic including but not limited to: media information segment is in different rings
Feature under border.
9. according to the method described in claim 8, the environment includes but is not limited to: scene, interference information etc.；Its feature exists
In: objective influence is caused on information.
10. according to the method described in claim 1, the semantic conversion is handled, including but not limited to: carrying out randomization to feature
Processing.
11. according to the method described in claim 1, the accumulated process, including but not limited to:
The information of Screening Treatment continuous-stable input；
Record the input frequency of various information.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN201910395991.0A CN110134955A (en) | 2019-05-14 | 2019-05-14 | A kind of semantic processes method |
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| CN201910395991.0A CN110134955A (en) | 2019-05-14 | 2019-05-14 | A kind of semantic processes method |
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101510221A (en) * | 2009-02-17 | 2009-08-19 | 北京大学 | Enquiry statement analytical method and system for information retrieval |
| CN104317846A (en) * | 2014-10-13 | 2015-01-28 | 安徽华贞信息科技有限公司 | Semantic analysis and marking method and system |
| US20170109786A1 (en) * | 2015-10-20 | 2017-04-20 | Korea Electronics Technology Institute | System for producing promotional media content and method thereof |
| WO2019085640A1 (en) * | 2017-10-31 | 2019-05-09 | 株式会社Ntt都科摩 | Word meaning disambiguation method and device, word meaning expansion method, apparatus and device, and computer-readable storage medium |
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2019
- 2019-05-14 CN CN201910395991.0A patent/CN110134955A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101510221A (en) * | 2009-02-17 | 2009-08-19 | 北京大学 | Enquiry statement analytical method and system for information retrieval |
| CN104317846A (en) * | 2014-10-13 | 2015-01-28 | 安徽华贞信息科技有限公司 | Semantic analysis and marking method and system |
| US20170109786A1 (en) * | 2015-10-20 | 2017-04-20 | Korea Electronics Technology Institute | System for producing promotional media content and method thereof |
| WO2019085640A1 (en) * | 2017-10-31 | 2019-05-09 | 株式会社Ntt都科摩 | Word meaning disambiguation method and device, word meaning expansion method, apparatus and device, and computer-readable storage medium |
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Application publication date: 20190816 |