CN109446344A - A kind of intellectual analysis report automatic creation system based on big data - Google Patents
A kind of intellectual analysis report automatic creation system based on big data Download PDFInfo
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Abstract
The invention discloses a kind of, and the intellectual analysis based on big data reports automatic creation system, including big data resource pool, knowledge mapping system, modeling engine system and XML expert view library automatic Recommendation System；The big data resource pool, for converging the data resource and knowledge resource in different data source, and according to theme intelligently pushing associated data and association knowledge；Knowledge mapping system, knowledge based logic and relation on attributes building, and according to descriptor auto-associating knowledge relevant to descriptor, realize intelligent retrieval and question and answer；Modeling engine system, the analysis model being related to for being associated with corresponding application field relevant to descriptor, realizes the in-depth analysis to achievement data；XML expert view library automatic Recommendation System, knowledge point that automatic push solve the problems, such as corresponding with descriptor for auto-associating, and automatically generate intelligent report.Compared with traditional intelligence report, the intellectual analysis report automatically generated based on big data is objective, authoritative, can greatly improve the working efficiency of researcher.
Description
Technical field
The invention belongs to the report intellectual analysis researched and developed based on every intelligent information technology means and automatic creation systems
Technical field more particularly to big data mining analysis technology, data exchange and technology of sharing, are known fragment index and index technology
The intellectual analysis for knowing graphical spectrum technology reports automatic creation system.
Background technique
Most common, basic data mart modeling behavior in traditional intelligence data analysis mining BI project.Construct the data warehouse phase
Between, the data of all kinds of operation systems need to enter in data warehouse by stringent ETL process, and then are subsequent
Data exhibiting, analysis provide support.It is inconsistent generally, due to each operation system data bore of enterprise, so that BI project must
It must implement ETL work, it is futile, nonsensical that various data behaviors are otherwise carried out in ambiguous, inaccurate data.
In digital Age of the multimedium across media, traditional data medium is reported during being unable to satisfy Content Organizing and service
Accuse the demands such as the writing of author's remote collaborative, demand personalization customization, intelligent recognition, editor's automation.Therefore, break conventional flow
Based on content object, cooperating, " producing once a, polynary publication " dynamic report is established in the constraint of journey and concept
Accusing generting machanism becomes a crucial technology.
Summary of the invention
In order to solve the above technical problems, the object of the present invention is to provide a kind of, the intellectual analysis report based on big data is automatic
Generation system.
The purpose of the present invention is realized by technical solution below:
A kind of intellectual analysis report automatic creation system based on big data, comprising: big data resource pool, knowledge graph pedigree
System, modeling engine system and XML expert view library automatic Recommendation System；It is described
Big data resource pool, for converging the data resource and knowledge resource in different data source, and according to theme intelligence
Push associated data and association knowledge；
Knowledge mapping system, knowledge based logic and relation on attributes building, and according to descriptor auto-associating and descriptor
Relevant knowledge realizes intelligent retrieval and question and answer；
Modeling engine system, the analysis model being related to for being associated with corresponding application field relevant to descriptor, is realized
In-depth analysis to achievement data；
XML expert view library automatic Recommendation System, corresponding with descriptor for auto-associating, automatic push solve the problems, such as
Knowledge point, and automatically generate intelligent report.
Compared with prior art, one or more embodiments of the invention can have following advantage:
The report generated based on big data is objective from the point of view of content, scientific, and from the point of view of source, data and knowledge mark come
Source can trace, from the point of view of formation speed, automatically generate, and efficiency is accelerated.
Detailed description of the invention
Fig. 1 is the intellectual analysis report automatic creation system structure chart based on big data.
Specific embodiment
To make the object, technical solutions and advantages of the present invention clearer, below in conjunction with examples and drawings to this hair
It is bright to be described in further detail.
As shown in Figure 1, reporting automatic creation system structure for the intellectual analysis based on big data, comprising: big data resource
Pond, knowledge mapping system, modeling engine system and XML expert view library automatic Recommendation System；It is described
Big data resource pool, for converging the data resource and knowledge resource in different data source, and according to theme intelligence
Push associated data and association knowledge；
Knowledge mapping system, knowledge based logic and relation on attributes building, and according to descriptor auto-associating and descriptor
Relevant knowledge realizes intelligent retrieval and question and answer；
Modeling engine system, the analysis model being related to for being associated with corresponding application field relevant to descriptor, is realized
In-depth analysis to achievement data；
XML expert view library automatic Recommendation System, corresponding with descriptor for auto-associating, automatic push solve the problems, such as
Knowledge point, and automatically generate intelligent report.
Above-mentioned big data resource pool: will be distribution, data such as relation data in heterogeneous data source, flat using ETL tool
Face data file etc. is taken out by natural language processing technique, artificial intelligence, data mining, data processing, knowledge fragmentation technology
It gets and is cleaned after interim middle layer, convert, integrate, be finally loaded into data warehouse or Data Mart, become online point
The basis of analysis processing, data mining.By classification, estimation, prediction, correlation grouping or correlation rule, cluster, description and visually
Change, complex data type (Text, Web, graph image, video, audio etc.) excavate, by data storage enter relational database,
NOSQL, SQL etc..
Knowledge mapping system: knowledge mapping and index main body system are called, that sets up based on natural language knows
Know the knowledge mapping of network system building, shows the incidence relation between data relevant to Knowledge Element and disclose multi-dimensional semantic and close
System.By the way that the data of scattered distribution are formed Knowledge Grid, the resources such as fusion creation data, scientific data, marketing data are goed deep into
Excavate the globality and relevance of data.Knowledge mapping includes basic resource layer, blocks of knowledge layer, knowledge organization layer and knowledge table
Up to layer.By the way that the data of separate sources are carried out Knowledge Extraction, blocks of knowledge entity is formed, then the entity extracted is known
Know fusion, excavate the incidence relation between entity, the tissue of knowledge can be realized from semantic level, is implied between discovered knowledge
Relationship forms knowledge network.
Above-mentioned knowledge mapping system is from structuring, semi-structured and unstructured data, using automatically or semi-automatically
Technology extracts knowledge true from raw data base and third party database, and the knowledge fact of extraction is stored in knowledge base
Data Layer and mode layer.
It includes: Knowledge Extraction, knowledge that the above-mentioned knowledge fact by extraction, which is stored in knowledge base data Layer and the process of mode layer,
Expression, knowledge fusion, knowledge reasoning Four processes, and updating iteration each time includes this four-stage.
Modeling engine system: calling model engine, using statistical analysis technique, such as hypothesis testing, significance test, difference
Analysis, correlation analysis, T inspection, variance analysis, chi-square analysis, partial Correlation Analysis, distance analysis, regression analysis, simple regression point
Analysis, multiple regression analysis, successive Regression, regression forecasting and residual analysis, logistic regression analysis, curve estimation, Factor minute
It is analysis, clustering, principal component analysis, factorial analysis, quick clustering method and clustering procedure, discriminant analysis, correspondence analysis, polynary corresponding
Analyze the building utility model such as (Optimal Scaling Technique), bootstrap technology.
Above-mentioned modeling engine system is based on CNKI agriculture field authority paper resource, according to research purpose, content, data class
The difference of type constructs all kinds of analysis models using artificial intelligence technology, forms modeling engine.
XML expert view library automatic Recommendation System: using fragment index and index technology in addition to whole or whole contents
It is outer to carry out metadata mark, also the knowledge to each chapters and sections of digital publishing resource individually to index and index in more detail.
Fragment knowledge after index and index is easier to be obtained and utilized by reader, life cycle than whole book it is longer,
More effectively.Digital content fragmentation tissue main flow include: maintain traditional publication content, save author's contribution, last instance contribution,
Eventually row file, and convert eventually row file according to kind, copy, part, a piece, chapter and section mode carry out tissue；By the piece, chapter, section of formation
Content is classified by modes such as subject, the classification of middle figure, themes, by the classification of formation according to a certain subject, a direction, certain industry
Construct knowledge hierarchy；Knowledge hierarchy is split into the blocks of knowledge of different directions again, blocks of knowledge splits into knowledge point, finally tears open
It is divided into descriptor, keyword；Knowledge point is dynamically associated by semantic relation between keyword, forms netted interconnecting relation；
Content is recombinated on demand, realizes that dynamic is published using polymorphic synchronous generation technique.
Above-mentioned XML expert view library automatic Recommendation System by knowledge base management system, independent knowledge base, database, push away
Reason machine, interpreter, knowledge acquisition module and user interface composition；It is described
Knowledge base management system, for the knowledge in knowledge base to be checked and retrieved；
Database, for storing initial data and the inference machine average information obtained in reasoning；
Interpreter, for explaining to solution procedure and providing the countermeasure solved the problems, such as；
Knowledge acquisition module, the relevant knowledge for will acquire are transferred to knowledge base；
User interface is responsible for receiving the information of user's input and is converted into internal system representation, and is submitted to corresponding
Module is handled, and is then converted user's acceptable form of expression for the internal information that system exports and is returned to user.
In the automatic Recommendation System of above-mentioned XML expert view library, the knowledge point of solved problem includes As-Is analysis, reason spy
Rope, countermeasure and suggestion and prediction knowledge resource etc..
After fragmentation solves, multiplexing and one of the key technology that recombination is that dynamic digital is published.Traditional Content Management
The content of fragmentation can be managed, but multiplexing and the reformulation rule of fragmentation content can not be managed, especially dynamic recombination,
Need to realize the dynamic restructuring of the series of standards such as application request, combination, output.
The file of content and integration, formatting for fragmentation, it is necessary to after having an inspection mass file storage
Then the method whether damaged is backed up and is repaired for the part of damage, mass file Features Management is established, in order to examine
It looks into, manage, repair, this is the key that in current digital content inspection and multiplexing technology.
Based on the Research foundation of collection and fragmentation and recombination to content, a content dynamic reorganization is devised herein
With print on demand platform.Platform general technological system route presses operation flow, function and feature, is divided into three relatively independent layers
It is secondary: data service layer, data management layer and data acquisition layer.
Data service layer mainly includes digital publishing service system, mobile reading system by all kinds of means.Data management layer is main
Including modules such as digital asset management system, data verification management, mass data characteristic processings.Data acquisition layer is mainly included in
Line is published system of compiling, author, editor, expert's index tool, scientific and technological symbol Internet-based and the complicated of figure and is edited
Tool etc..
Wherein, data management layer is mainly realized for publishing house's digital content resource, including books and periodicals, chapter section, knowledge
Concentrated processing processing, resource management and the digital content output service of the multimedia resources such as point, audio-video, animation and picture,
It is divided into content storage management, general purpose module management, content arrangement management, logic content depositary management reason and content and shows management etc. mainly
Function.
1. content storage management: all kinds of digital contents deposit unified content being managed platform, then passes through content fragmentation
Processing, is split content by chapters and sections, picture etc., and carries out semantization mark after singulation, and by treated, result is stored in
Fragment content storage platform.2. general purpose module management: the description information (attribute tags) to content is managed collectively by system,
And the related information between all kinds of contents is managed, meanwhile, system will provide full-text search engine for the content of management, to full content
Carry out unified retrieval.3. content arranges management.Semantic engine is provided, processing staff is helped to be labeled digital content；Together
When provide content annotation tool, which helps PDF document to be divided into chapters and sections and picture, and in the fragmentation after cutting
Hold addition semantic label；Content retrieval system provides the retrieval capability to different levels content, and by the content retrieved by
Weight sequencing.Editor's personal space provides editor and author's accumulation and the tool for managing personal content.4. content shows management.
Digital content will form various logic content library, such as raw data library, picture library, article library, audio-video library after arranging
Deng.
Although disclosed herein embodiment it is as above, the content is only to facilitate understanding the present invention and adopting
Embodiment is not intended to limit the invention.Any those skilled in the art to which this invention pertains are not departing from this
Under the premise of the disclosed spirit and scope of invention, any modification and change can be made in the implementing form and in details,
But scope of patent protection of the invention, still should be subject to the scope of the claims as defined in the appended claims.
Claims (7)
1. a kind of intellectual analysis based on big data reports automatic creation system, which is characterized in that the system comprises: big data
Resource pool, knowledge mapping system, modeling engine system and XML expert view library automatic Recommendation System；It is described
Big data resource pool, for converging the data resource and knowledge resource in different data source, and according to theme intelligently pushing
Associated data and association knowledge；
Knowledge mapping system, knowledge based logic and relation on attributes building, and it is related to descriptor according to descriptor auto-associating
Knowledge, realize intelligent retrieval and question and answer；
Modeling engine system, the analysis model being related to for being associated with corresponding application field relevant to descriptor, is realized to finger
Mark the in-depth analysis of data；
XML expert view library automatic Recommendation System, corresponding with descriptor for auto-associating, what automatic push solved the problems, such as knows
Know point, and automatically generates intelligent report.
2. the intellectual analysis based on big data reports automatic creation system as described in claim 1, which is characterized in that described big
It is realized by natural language processing technique, artificial intelligence, data mining, data processing, knowledge fragmentation technology in data resource pond
To the cleaning of data, conversion and integrate.
3. the intellectual analysis based on big data reports automatic creation system as described in claim 1, which is characterized in that described to know
Chart system is known from structuring, semi-structured and unstructured data, using automatically or semi-automatically technology, from initial data
The knowledge fact is extracted in library and third party database, and the knowledge fact of extraction is stored in the data Layer and mode layer of knowledge base.
4. the intellectual analysis based on big data reports automatic creation system as described in claim 1, which is characterized in that the mould
Type automotive engine system is based on CNKI agriculture field authority paper resource, according to research purpose, content, the difference of data type, and benefit
Manually intellectual technology constructs all kinds of analysis models, forms modeling engine.
5. the intellectual analysis based on big data reports automatic creation system as described in claim 1, which is characterized in that described
XML expert view library automatic Recommendation System by knowledge base management system, independent knowledge base, database, inference machine, interpreter,
Knowledge acquisition module and user interface composition；It is described
Knowledge base management system, for the knowledge in knowledge base to be checked and retrieved；
Database, for storing initial data and the inference machine average information obtained in reasoning；
Interpreter, for explaining to solution procedure and providing the countermeasure solved the problems, such as；
Knowledge acquisition module, the relevant knowledge for will acquire are transferred to knowledge base；
User interface is responsible for receiving the information of user's input and is converted into internal system representation, and is submitted to corresponding module
It is handled, then converts user's acceptable form of expression for the internal information that system exports and return to user.
6. the intellectual analysis based on big data reports automatic creation system as described in claim 1, which is characterized in that described
In the automatic Recommendation System of XML expert view library, the knowledge point of solved problem includes As-Is analysis, reason exploration, countermeasure and suggestion
With prediction knowledge resource.
7. the intellectual analysis based on big data reports automatic creation system as claimed in claim 3, which is characterized in that will extract
Knowledge fact deposit knowledge base data Layer and the process of mode layer include: Knowledge Extraction, the representation of knowledge, knowledge fusion, knowledge
Reasoning Four processes.
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| CN111507758B (en) * | 2020-04-09 | 2023-10-31 | 深圳传世智慧科技有限公司 | Investigation method, device, system and server based on semantic analysis |
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| CN112199515A (en) * | 2020-11-17 | 2021-01-08 | 西安交通大学 | Polymorphic knowledge map driven knowledge service innovation method |
| CN112199515B (en) * | 2020-11-17 | 2023-08-15 | 西安交通大学 | Knowledge service innovation method driven by polymorphic knowledge graph |
| CN113962210A (en) * | 2021-11-24 | 2022-01-21 | 黄河勘测规划设计研究院有限公司 | Intelligent report compiling method based on NLP technology |
| CN115062165A (en) * | 2022-08-18 | 2022-09-16 | 合肥综合性国家科学中心人工智能研究院(安徽省人工智能实验室) | Medical image diagnosis method and device based on film reading knowledge graph |
| CN115713085B (en) * | 2022-10-31 | 2023-11-07 | 北京市农林科学院 | Method and device for analyzing literature topic content |
| CN115713085A (en) * | 2022-10-31 | 2023-02-24 | 北京市农林科学院 | Document theme content analysis method and device |
| CN116719926B (en) * | 2023-08-10 | 2023-10-20 | 四川大学 | Congenital heart disease report data screening method and system based on intelligent medical treatment |
| CN116719926A (en) * | 2023-08-10 | 2023-09-08 | 四川大学 | Congenital heart disease report data screening method and system based on intelligent medical treatment |
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