CN111026804A - Big data analysis intelligent service system based on semantics - Google Patents
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- 238000004458 analytical method Methods 0.000 claims abstract description 37
- 238000013480 data collection Methods 0.000 claims abstract description 33
- 238000012545 processing Methods 0.000 claims abstract description 25
- 238000013079 data visualisation Methods 0.000 claims abstract description 24
- 230000010365 information processing Effects 0.000 claims abstract description 5
- 238000005065 mining Methods 0.000 claims abstract description 4
- 238000007726 management method Methods 0.000 claims description 22
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- 230000008520 organization Effects 0.000 claims description 18
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- 230000000694 effects Effects 0.000 claims description 7
- 230000007246 mechanism Effects 0.000 claims description 6
- 238000012544 monitoring process Methods 0.000 claims description 6
- 230000008569 process Effects 0.000 claims description 6
- 238000013439 planning Methods 0.000 claims description 4
- 230000001154 acute effect Effects 0.000 claims description 3
- 238000012550 audit Methods 0.000 claims description 3
- 238000004140 cleaning Methods 0.000 claims description 3
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- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/26—Visual data mining; Browsing structured data
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
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Abstract
The invention discloses a semantic-based intelligent service system for big data analysis, which comprises a data collection unit, a data analysis unit and a data visualization unit, wherein the data collection unit is used for mining big data and comprises a structured data processing module and an unstructured data processing module, the data analysis unit is used for integrating data, classifying the data and correlating the analyzed data to form an analysis result and provide real-time data required by analysis, the data visualization unit is used for displaying the finally required data analysis result in a graphic language which can be identified and received by a user, the system also comprises a storage unit, a service output unit and a data quality management unit, the storage unit comprises an information processing module, and the information processing module sequentially transmits the data processing results of the data collection unit, the data analysis unit and the data visualization unit, wins opportunities for enterprises in the market economy.
Description
Technical Field
The invention belongs to the technical field of electronic commerce platforms, and particularly relates to a semantic-based big data analysis intelligent service system.
Background
In the new period of the social development of China, the different military of small and medium-sized enterprises is prominent, and therefore the force of the Chinese market is increasingly vigorous. They are eagerly developed and need information services without the strength and energy of capital-intensive large group companies from having constructed information institutions. The information resource is one of the most important resources of an enterprise, and developing the information resource is the starting point of enterprise informatization and is also the 'homing' of the enterprise informatization.
With the continuous deepening of the informatization degree, the desire of enterprises for the analysis service of the big data is increasingly strong. The continuous increase of information resources of the internet contains huge amount of information with commercial value, and becomes an important business intelligent service information source, but the value of the internet is not fully developed and utilized by the industry due to the difficulties of huge data volume, large acquisition difficulty, relatively low unit value, almost all non-structural data such as texts and the like.
For an enterprise, "efficiency is life and time is money". The internet can provide more convenient, rapid and omnibearing reference consultation service for small and medium-sized enterprises only by actively providing information service means and utilizing modern technical equipment to realize resource sharing and organizing, planning and purposefully collecting and processing information, thereby accelerating the decision-making speed of enterprise leadership and gaining opportunity for enterprises in market economy.
Therefore, a semantic-based big data analysis intelligent service system is provided to solve the problems in the prior art, a structured data processing module and an unstructured data processing module are matched to mine big data in a data collection unit to provide more sources for data acquisition, a storage unit is arranged in the system to sequentially transmit data processing results of the data collection unit, the data analysis unit and a data visualization unit, and a business delivery unit is arranged in the system and comprises a marketing data collection module, a data business module, a marketing report generation module and a business information analysis module, so that more convenient, quick and comprehensive reference consultation services are provided for small and medium-sized enterprises, the enterprise leadership decision making speed is accelerated, and opportunities are won for the enterprises in market economy.
Disclosure of Invention
The invention aims to provide a semantic-based big data analysis intelligent service system, which aims to solve the problems that the value of the prior art is not fully developed and utilized by the industry due to the difficulties of huge internet data volume, high acquisition difficulty, relatively low unit value, almost all non-structural data such as texts and the like.
In order to achieve the purpose, the invention adopts the following technical scheme: a big data analysis intelligent service system based on semantics comprises a data collection unit, a data analysis unit and a data visualization unit, wherein the data collection unit is used for mining big data and comprises a structured data processing module and an unstructured data processing module;
the data analysis unit is used for integrating data, classifying the data and analyzing the data in a correlation manner to form an analysis result and provide real-time data required by analysis;
the data visualization unit is used for presenting the finally needed data analysis result in a graphic language which can be recognized and accepted by a user;
the system also comprises a storage unit, a service output unit and a data quality management unit, wherein the storage unit comprises an information processing module which sequentially transmits data processing results of the data collection unit, the data analysis unit and the data visualization unit; the business output unit is used for executing, scheduling and displaying specific business and sequentially comprises a marketing data collection module, a data business module, a marketing report generation module and a business information analysis module.
Preferably, the marketing data collection module is used for providing technical support of data collection, analysis and marketing means for precise marketing; the data service module is used for data collection and semantic analysis which are carried out for meeting the specific data requirements of customers; the marketing report generation module generates a short, summary and image-text combined information summary for the client, and supports automatic generation and report summarization and writing at regular intervals; the business information analysis module is used for business opportunity information analysis, competitor analysis, industry movement and data analysis.
Preferably, the structured data is also called row data, is data logically expressed and realized by a two-dimensional table structure, strictly conforms to data format and length specification, is mainly stored and managed by a relational database, is non-structured data which is not suitable for being expressed by a two-dimensional table of the database, comprises all forms of office documents, XML, HTML, various types of reports, pictures and audio, video information and the like, and is opposite to the structured data, and the database supporting the non-structured data adopts a multi-value field, a field and a variable length field mechanism to create and manage data items.
Preferably, unstructured data is available anywhere, which may be searched for in-company mail messages, chat logs, and collected survey results, comments on personal websites, comments in customer relationship management systems, or text fields from personal applications, and also in social media outside of a company, monitored forums, and comments from topics of interest to some users.
Preferably, the semantic analysis engine unit includes text error correction, emotion tendency analysis, comment viewpoint extraction, conversational emotion recognition, article labels, article classification and news summarization, and can sequentially recognize error segments in a text, perform error prompt and give, perform acute emotion judgment on the text containing supervisor information, automatically analyze user comments, output comment viewpoints and emotion polarities, automatically detect emotional features contained in the daily conversational text of a user, automatically classify the articles according to content types, perform core keyword analysis on the articles, and automatically extract key information in the news text.
Preferably, the data quality management unit is used for performing a series of management activities such as identification, measurement, monitoring, early warning and the like on various data quality problems which may be caused in each stage of a planning, obtaining, storing, sharing, maintaining, applying and extinction life cycle of data, and further improving the data quality by improving and improving the management level of an organization, and mainly comprises data analysis, data evaluation, data cleaning, data monitoring, error early warning and the like aiming at the improvement and management of the data; aiming at the improvement and management of the organization, the method mainly comprises the steps of establishing an organization data quality improvement target, evaluating an organization process, making an organization process improvement plan, making an organization supervision and audit mechanism, implementing improvement, evaluating an improvement effect and the like.
Preferably, the data visualization of the data visualization unit comprises two main components: statistical graphs and thematic maps, data visualization can utilize graphics, image processing, computer vision, and user interfaces to interpret data visually through expression, modeling, and display of stereo, surface, attributes, and animations.
The invention has the technical effects and advantages that: compared with the prior art, the big data analysis intelligent service system based on the semantics has the following advantages:
in the invention, in a data collection unit, a structured data processing module and an unstructured data processing module are matched to mine big data, so that more sources are provided for data acquisition, a storage unit is arranged in the system to sequentially transmit data processing results of the data collection unit, a data analysis unit and a data visualization unit, and a service delivery unit is arranged in the system and comprises a marketing data collection module, a data service module, a marketing report generation module and a business information analysis module, so that more convenient, rapid and omnibearing reference consultation service is provided for small and medium-sized enterprises, the enterprise lead decision speed is accelerated, and opportunities are won for the enterprises in market economy.
Drawings
FIG. 1 is a block diagram of an intelligent service system for data analysis according to the present invention;
FIG. 2 is a block diagram of a data quality management unit of the data analysis intelligent service of the present invention;
FIG. 3 is a block diagram of a semantic analysis engine unit of the intelligent service for data analysis according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. The specific embodiments described herein are merely illustrative of the invention and do not delimit the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides a semantic-based big data analysis intelligent service system which comprises a data collection unit, a data analysis unit and a data visualization unit, wherein the data collection unit is used for mining big data and comprises a structured data processing module and an unstructured data processing module;
the data analysis unit is used for integrating data, classifying the data and analyzing the data in a correlation manner to form an analysis result and provide real-time data required by analysis;
the data visualization unit is used for presenting the finally needed data analysis result in a graphic language which can be recognized and accepted by a user;
the system also comprises a storage unit, a service output unit and a data quality management unit, wherein the storage unit comprises an information processing module which sequentially transmits data processing results of the data collection unit, the data analysis unit and the data visualization unit; the business output unit is used for executing, scheduling and displaying specific business and sequentially comprises a marketing data collection module, a data business module, a marketing report generation module and a business information analysis module.
The marketing data collection module is used for providing technical support of data collection, analysis and marketing means for accurate marketing; the data service module is used for data collection and semantic analysis which are carried out for meeting the specific data requirements of customers; the marketing report generation module generates a short, summary and image-text combined information summary for the client, and supports automatic generation and report summarization and writing at regular intervals; the business information analysis module is used for business opportunity information analysis, competitor analysis, industry movement and data analysis.
Structured data, also called row data, is data logically expressed and realized by a two-dimensional table structure, strictly follows data format and length specification, is mainly stored and managed by a relational database, is non-structured data which is not suitable for being expressed by a database two-dimensional table and comprises office documents, XML, HTML, various reports, pictures, audio, video information and the like in all formats, and a database supporting the non-structured data adopts a multi-value field, a field and a variable length field mechanism to create and manage data items.
Unstructured data is available anywhere, which can be searched for in-company mail messages, chat logs, and collected survey results, as well as comments on personal websites, comments in customer relationship management systems, or text fields from personal applications, and also in social media outside of a company, monitored forums, and comments from topics of interest to some users.
The semantic analysis engine unit comprises text error correction, emotional tendency analysis, comment viewpoint extraction, conversation emotion identification, article labels, article classification and news summarization, can identify error segments in a text in sequence, carries out error prompt and gives out, carries out emotion acute judgment on the text containing supervisor information, automatically analyzes user comments, outputs comment viewpoints and emotion polarities, automatically detects emotion characteristics contained in daily conversation texts of users, automatically classifies the articles according to content types, carries out core keyword analysis on the articles, and automatically extracts key information in the news texts.
The data quality management unit is used for carrying out a series of management activities such as identification, measurement, monitoring, early warning and the like on various data quality problems possibly caused in each stage of a life cycle of planning, obtaining, storing, sharing, maintaining, applying and eliminating data, further improving the data quality by improving and improving the management level of organization, and mainly comprises the contents of data analysis, data evaluation, data cleaning, data monitoring, error early warning and the like aiming at the improvement and management of the data; aiming at the improvement and management of the organization, the method mainly comprises the steps of establishing an organization data quality improvement target, evaluating an organization process, making an organization process improvement plan, making an organization supervision and audit mechanism, implementing improvement, evaluating an improvement effect and the like.
The data visualization of the data visualization unit comprises two main components: statistical graphs and thematic maps, data visualization can utilize graphics, image processing, computer vision, and user interfaces to interpret data visually through expression, modeling, and display of stereo, surface, attributes, and animations.
The working principle is as follows: in the invention, in a data collection unit, a structured data processing module and an unstructured data processing module are matched to mine big data, so that more sources are provided for data acquisition, a storage unit is arranged in the system to sequentially transmit data processing results of the data collection unit, a data analysis unit and a data visualization unit, and a service delivery unit is arranged in the system and comprises a marketing data collection module, a data service module, a marketing report generation module and a business information analysis module, so that more convenient, rapid and omnibearing reference consultation service is provided for small and medium-sized enterprises, the enterprise lead decision speed is accelerated, and opportunities are won for the enterprises in market economy.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that modifications may be made to the embodiments or portions thereof without departing from the spirit and scope of the invention.
Claims (7)
1. The utility model provides a big data analysis intelligence service system based on semanteme, includes data collection unit, data analysis unit and data visualization unit, its characterized in that: the data collection unit is used for mining big data and comprises a structured data processing module and an unstructured data processing module;
the data analysis unit is used for integrating data, classifying the data and analyzing the data in a correlation manner to form an analysis result and provide real-time data required by analysis;
the data visualization unit is used for presenting the finally needed data analysis result in a graphic language which can be recognized and accepted by a user;
the system also comprises a storage unit, a service output unit and a data quality management unit, wherein the storage unit comprises an information processing module which sequentially transmits data processing results of the data collection unit, the data analysis unit and the data visualization unit; the business output unit is used for executing, scheduling and displaying specific business and sequentially comprises a marketing data collection module, a data business module, a marketing report generation module and a business information analysis module.
2. The big data analysis intelligent service system based on semantics as claimed in claim 1, wherein: the marketing data collection module is used for providing technical support of data collection, analysis and marketing means for accurate marketing; the data service module is used for data collection and semantic analysis which are carried out for meeting the specific data requirements of customers; the marketing report generation module generates a short, summary and image-text combined information summary for the client, and supports automatic generation and report summarization and writing at regular intervals; the business information analysis module is used for business opportunity information analysis, competitor analysis, industry movement and data analysis.
3. The big data analysis intelligent service system based on semantics as claimed in claim 1, wherein: structured data, also called row data, is data logically expressed and realized by a two-dimensional table structure, strictly follows data format and length specification, is mainly stored and managed by a relational database, is non-structured data which is not suitable for being expressed by a database two-dimensional table and comprises office documents, XML, HTML, various reports, pictures, audio, video information and the like in all formats, and a database supporting the non-structured data adopts a multi-value field, a field and a variable length field mechanism to create and manage data items.
4. The big data analysis intelligent service system based on semantics as claimed in claim 1, wherein: unstructured data is available anywhere, which can be searched for in-company mail messages, chat logs, and collected survey results, as well as comments on personal websites, comments in customer relationship management systems, or text fields from personal applications, and also in social media outside of a company, monitored forums, and comments from topics of interest to some users.
5. The big data analysis intelligent service system based on semantics as claimed in claim 1, wherein: the semantic analysis engine unit comprises text error correction, emotional tendency analysis, comment viewpoint extraction, conversation emotion identification, article labels, article classification and news summarization, can identify error segments in a text in sequence, carries out error prompt and gives out, carries out emotion acute judgment on the text containing supervisor information, automatically analyzes user comments, outputs comment viewpoints and emotion polarities, automatically detects emotion characteristics contained in daily conversation texts of users, automatically classifies the articles according to content types, carries out core keyword analysis on the articles, and automatically extracts key information in the news texts.
6. The big data analysis intelligent service system based on semantics as claimed in claim 1, wherein: the data quality management unit is used for carrying out a series of management activities such as identification, measurement, monitoring, early warning and the like on various data quality problems possibly caused in each stage of a life cycle of planning, obtaining, storing, sharing, maintaining, applying and eliminating data, further improving the data quality by improving and improving the management level of organization, and mainly comprises the contents of data analysis, data evaluation, data cleaning, data monitoring, error early warning and the like aiming at the improvement and management of the data; aiming at the improvement and management of the organization, the method mainly comprises the steps of establishing an organization data quality improvement target, evaluating an organization process, making an organization process improvement plan, making an organization supervision and audit mechanism, implementing improvement, evaluating an improvement effect and the like.
7. The big data analysis intelligent service system based on semantics as claimed in claim 1, wherein: the data visualization of the data visualization unit comprises two main components: statistical graphs and thematic maps, data visualization can utilize graphics, image processing, computer vision, and user interfaces to interpret data visually through expression, modeling, and display of stereo, surface, attributes, and animations.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111679814A (en) * | 2020-05-24 | 2020-09-18 | 杭州云徙科技有限公司 | Data-driven data center system |
| CN112015962A (en) * | 2020-07-24 | 2020-12-01 | 北京艾巴斯智能科技发展有限公司 | Government affair intelligent big data center system architecture |
| CN113343711A (en) * | 2021-06-29 | 2021-09-03 | 南方电网数字电网研究院有限公司 | Work order generation method, device, equipment and storage medium |
| CN115577646A (en) * | 2022-12-08 | 2023-01-06 | 北京领雁科技股份有限公司 | Data modeling method, device, equipment and medium based on multi-source heterogeneous data |
| CN116189193A (en) * | 2023-04-25 | 2023-05-30 | 杭州镭湖科技有限公司 | Data storage visualization method and device based on sample information |
| CN113343711B (en) * | 2021-06-29 | 2024-05-10 | 南方电网数字电网研究院有限公司 | Work order generation method, device, equipment and storage medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070021992A1 (en) * | 2005-07-19 | 2007-01-25 | Srinivas Konakalla | Method and system for generating a business intelligence system based on individual life cycles within a business process |
| CN103389998A (en) * | 2012-05-11 | 2013-11-13 | 安徽华贞信息科技有限公司 | Novel Internet commercial intelligence information semantic analysis technology based on cloud service |
| CN104182389A (en) * | 2014-07-21 | 2014-12-03 | 安徽华贞信息科技有限公司 | Semantic-based big data analysis business intelligence service system |
| CN107918818A (en) * | 2016-10-10 | 2018-04-17 | 香港纺织及成衣研发中心有限公司 | Supply chain management DSS based on big data technology |
| CN107958049A (en) * | 2017-11-28 | 2018-04-24 | 航天科工智慧产业发展有限公司 | A kind of quality of data checking and administration system |
-
2019
- 2019-12-04 CN CN201911230571.3A patent/CN111026804A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070021992A1 (en) * | 2005-07-19 | 2007-01-25 | Srinivas Konakalla | Method and system for generating a business intelligence system based on individual life cycles within a business process |
| CN103389998A (en) * | 2012-05-11 | 2013-11-13 | 安徽华贞信息科技有限公司 | Novel Internet commercial intelligence information semantic analysis technology based on cloud service |
| CN104182389A (en) * | 2014-07-21 | 2014-12-03 | 安徽华贞信息科技有限公司 | Semantic-based big data analysis business intelligence service system |
| CN107918818A (en) * | 2016-10-10 | 2018-04-17 | 香港纺织及成衣研发中心有限公司 | Supply chain management DSS based on big data technology |
| CN107958049A (en) * | 2017-11-28 | 2018-04-24 | 航天科工智慧产业发展有限公司 | A kind of quality of data checking and administration system |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111679814A (en) * | 2020-05-24 | 2020-09-18 | 杭州云徙科技有限公司 | Data-driven data center system |
| CN112015962A (en) * | 2020-07-24 | 2020-12-01 | 北京艾巴斯智能科技发展有限公司 | Government affair intelligent big data center system architecture |
| CN113343711A (en) * | 2021-06-29 | 2021-09-03 | 南方电网数字电网研究院有限公司 | Work order generation method, device, equipment and storage medium |
| CN113343711B (en) * | 2021-06-29 | 2024-05-10 | 南方电网数字电网研究院有限公司 | Work order generation method, device, equipment and storage medium |
| CN115577646A (en) * | 2022-12-08 | 2023-01-06 | 北京领雁科技股份有限公司 | Data modeling method, device, equipment and medium based on multi-source heterogeneous data |
| CN116189193A (en) * | 2023-04-25 | 2023-05-30 | 杭州镭湖科技有限公司 | Data storage visualization method and device based on sample information |
| CN116189193B (en) * | 2023-04-25 | 2023-11-10 | 杭州镭湖科技有限公司 | Data storage visualization method and device based on sample information |
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Application publication date: 20200417 |