KR20220050007A - Big data analysis system for advertise marketing and method thereof - Google Patents

Abstract

The present invention relates to a big data analysis system for marketing, which enables small and medium-sized businesses, having difficulty in collecting sufficient information only with internal information, to effectively collect information that can provide desired marketing information through a model optimized for marketing, and to analyze the collected information in a systematic way, and a method thereof. The big data analysis system for marketing searches for internal customer information and information from sources (websites) on a network selected based on keywords, collects the results in an information collection unit, distributes and stores the information collected by the information collection unit in consideration of characteristics, analyzes the distributed and stored information by an analysis method including value analysis through item association analysis, provides the results, and effectively analyzes time-sequentially changing information dissemination status of customers through a repetitive process of storing the analysis results and the provided results again as data and analyzing the correlation between the stored data and newly accumulated and analyzed data, thereby effectively providing marketing support information or management support information even if the analysis information possessed by itself is limited, and enables specialized analysis companies to construct these components rather than individual companies and use the collected information universally, thereby providing marketing support information desired by individual customers through analysis methods required by the individual customers. In this case, the individual customers can secure the marketing support information or the management support information through big data analysis at a low cost.

Description

Big data analysis system for advertise marketing and method thereof

The present invention relates to a big data analysis system and method for marketing, and in particular, information sufficient only with internal information

A big data analysis system and method for marketing that allows small and medium-sized businesses that are difficult to collect effectively collect information that can provide desired marketing information through a marketing-optimized model and systematically analyze the collected information. it's about

As interest in the collection and analysis of big data increases, many members such as portals, large distributors or manufacturers

Companies that possess and can collect vast amount of member usage log information analyze members’ usage logs.

The use of big data, such as calculating one trend information or classifying a target group, is being considered.

Basically, the processing of big data is about distributed storage and distributed processing to effectively process vast amounts of information.

technology, technology to collect and correlate various structured and unstructured data, and meaningfulness from information obtained without purpose

Technology that calculates one piece of information is being applied in a complex way, and the effect of such big data analysis is still not visible.

Because it has not been proven as

Research and attempts have been made to utilize big data analysis in marketing mainly for large companies that can secure data.

is currently being lost.

Among them, distributed storage and distributed processing of large-capacity data to respond to the rapid increase in web content or the increase in member usage logs.

Although considerable technological advances and utilization have been made in relation to data management, there are still

Much research is needed in this regard.

In particular, for such big data analysis, various analysis methods are being studied for practical use.

When big data analysis is used for business activities, it is mainly used to analyze internal data provided by customers

Some of them are being used for trend analysis, etc.

It has not been lost. However, the vast use of various mobile devices, the use of various social networks, and the

Various user usage log information that can be tracked and collected by the expansion of the network infrastructure is being accumulated exponentially.

In the future, big data analysis using this is essential for marketing support or management support information throughout the industry.

No one can deny that it will be.

In the end, the company does not have enough information about its customers, which is standardized and easy to collect and utilize, or it is difficult to analyze big data.

Small and medium-sized enterprises (SMEs) that cannot afford the system cost for

There is a high possibility that it will develop into a situation of being shunned or subordinated in competition with companies accessing the market.

Generally, companies succeed in commercialization through product or service development, but later go bankrupt due to lack of funds.

Passing through the so-called 'Death valley' is quite difficult, usually in hundreds or thousands.

talk about probabilities. Even if a product or service is launched on the market after passing through this valley of death, the initial market and mainstream

Before entering the market, demand temporarily stagnates or goes through a disconnection phenomenon that retreats.

It is called chasm, and it is only after this stage is exceeded that the technology goes through generalization, spreads to the general public, and has a ripple effect on the entire market.

appears. These valleys of death or chasms are divided into two major crisis situations for small and medium-sized enterprises (SMEs), and

To effectively verify the effectiveness of marketing for the spread of market trends, products or services, the marketing direction

Appropriate management support information to establish this is essential.

As mentioned above, large portals and large corporations use the capital or accumulated information of their customers for Big Day.

Such management information can or will be used soon through market analysis, but SMEs and venture companies

It is inevitably difficult to utilize management information through such big data analysis.

On the other hand, large portals provide free big data analysis tools that can utilize the vast amount of information they have.

There are cases where you want to preempt the platform market, so you can analyze various information you have.

Although there is an opportunity, it is still a static analysis through distributed storage of large data and known analysis methods.

The degree is general, but small and medium-sized enterprises or venture companies can customize these systems for themselves or

It is still difficult to directly develop and apply methodologies and analysis processes to effectively analyze changing market conditions.

difficult situation. Therefore, we give up on securing business information through big data analysis and follow traditional marketing methodologies.

Even if big data analysis is performed, it is used only as a simple auxiliary data that is not reliable.

1 is a conceptual diagram illustrating a conventional general big data analysis process.

As shown, the member use log acquisition unit 1 that collects the standardized use log of its own members, which is internal information, and the member

A distributed storage unit (2) that distributes and stores vast usage logs of

It consists of an analysis unit 3 and a result providing unit 4 that organizes the analyzed information and provides the results to the user.

Using this configuration to analyze usage log information generated by numerous members by age of users

It analyzes information on fragrance, time of use, location of use, preferred interest, etc. to identify trends or set marketing targets.

It is used for marketing or management information such as

However, if the number of members is small or the information that can be collected from the usage log is limited, the reliability of the analysis is low and the analysis

The possible objects themselves are bound to be limited. In particular, set macro management directions to set trends or marketing targets

In addition to information on how to provide advertisements right away and through which channels to conduct marketing,

What is the effect of chatting and what is the spread of viral marketing, which has a great influence in online marketing?

More direct short-term management support information or short-term marketing support information is effective for SMEs through the configuration of the existing system.

It is difficult to secure as an enemy.

As a result, small and medium-sized enterprises (SMEs) that have a small number of members or cannot obtain the desired analysis results from the usage information provided by members.

In the case of a venture company, if it is possible to effectively obtain information on management or marketing support optimized for the situation of the company,

Therefore, it is suitable for cases such as viral marketing where it is difficult to collect information because it is distributed and time-series correlation analysis is required.

A new type of big data analysis system and method that can collect data and provide desired analysis results is required.

there is a situation.

An object of the embodiments of the present invention for improving the above-described problems is to provide a network selected based on internal customer information and keywords.

Search for information from sources (websites) on the website and collect the results in an information collection unit, and a plurality of information collection units

In consideration of the characteristics, the collected information is distributed and stored, and the distributed and stored information includes value analysis through item association analysis.

analyzes in an analysis method and provides the results, but saves the analysis results and the provided results as data again

Through an iterative process of analyzing the correlation with the data that is stored and analyzed, it is possible to confirm customer information that changes in time series.

By effectively analyzing the living conditions, marketing support information or management support even if the analysis information possessed is limited

It is to provide a big data analysis system and method for marketing that can effectively provide information.

Another object of the embodiments of the present invention is to actively provide necessary information, not limited information of its customers, on the web.

In order to effectively analyze various atypical information according to the collection target, various atypical information according to the collection target

It can be done in various ways by configuring the information collection unit that formalizes the collected information collected by items to a processable level.

It enables the value analysis of the collected information on the web based on the items, and uses the analyzed information to create new analysis information and items.

By repeating the process of reanalysis based on

A big data analysis system for marketing that enables time series analysis and analysis of viral marketing

to provide a way

Another object of the embodiments of the present invention is to provide a user's request or result after storing the analyzed information in a utilization database

The contents of the utilization database are processed by the application and provided to the user as a result, and the provision of these results is

Analyze the events generated during the analysis process for

By storing it in the database, the information generated according to the experience of the actual work processor to provide results is divided.

A big data analysis system and method for marketing that is additionally reflected in the table and can be recycled by other users

will provide

In order to achieve the above object, the big data analysis system for marketing according to an embodiment of the present invention is

After searching for information from a set type of website according to the set search criteria, the searched information is parsed and prepared in advance.

an information collecting unit provided for each type of website that converts the hierarchical common code and the format based on the item; remind

a distributed storage unit for distributing and storing the information converted by the information collection unit with reference to a common code and size; The distributed storage unit

Distributed and stored information is accessed in a distributed processing method and divided according to analysis processes including item-based value analysis.

After analysis, the results are stored in the utilization database, and the previous value analysis results stored in the utilization database and the new

an analysis unit for re-analyzing the analyzed value analysis result based on the item and further storing the result in the utilization database;

Reanalyze the analysis results of the utilization database as a desired process or search according to the requested query and output the results.

It analyzes the output contents and provides it as data to the distributed storage unit according to the data format or utilizes it for reuse.

It includes a result providing unit to be stored in the database.

In addition, it provides the search criteria of the information collection unit, updates the analysis process in the analysis unit, and re-analysis process in the result provision unit.

It may include a user support unit that provides scans or queries and provides the results to users.

The information collection unit includes member information set as a search criterion, and may search for information related to the member.

On the other hand, the information collection unit includes keywords as a search criterion, and as basic information for general-purpose users, from a plurality of websites

It is divided into hierarchical common keywords prepared to search for information according to the above keywords and classify the search results.

By parsing the beam, it can be converted into a format including items for which relevance information is set.

The information collection unit can anonymize collected personal information and encrypt or delete identification information.

In addition, the information collection unit converts the format based on the item, but may include unstructured data.

The information collection unit is each open website, including search portal sites, social network sites, and cloud sites.

You can access the website and collect information according to the search criteria through a search or open API. here, information

The collection unit is divided by type of website, and each information collection unit collects search results according to the type of website in a common code.

It is preferable that the criteria for classifying the plots and the criteria for parsing the search results based on the items are different.

The analysis unit may provide the analysis result back to the distributed storage unit as data.

The analysis unit stores the value analysis results performed based on items in the utilization database for 1:N correlation analysis.

It is desirable to collect data repeatedly.

The result providing unit is an interface for linking with an external analysis solution or an external analysis solution, or an external user site

may include customizable analysis configurations.

The big data analysis method for marketing according to another embodiment of the present invention is classified according to a preset type of website.

Searches for information according to the search criteria set by the information collection unit, and compares the search contents with the hierarchical common code prepared in advance.

an information collection step of converting an item-based format; The converted information collected in the information collection step can be

a distributed storage step in which a Shinhan distributed storage unit distributes and stores received information based on a common code and size; the dispersion low

An analysis unit that performs a required analysis using the distributed and stored information in the chapter stage is distributed to the distributed and stored information

Approach as a processing method, conduct analysis according to analysis processes including item-based value analysis, and then analyze the results

It is stored in the utilization database, and the results of the previous value analysis and the newly analyzed value analysis pre-stored in the utilization database

an analysis step of re-analyzing the results based on the items and storing the results back in the utilization database; to the user

The result providing unit that provides results re-analyzes the analysis results of the utilization database into a desired process, or responds to the requested query.

It searches and outputs the results, analyzes the output contents, and submits them as data to the distributed storage unit according to the data format.

It includes a step of providing the results, which is shared or stored in a utilization database for reuse.

Provides search criteria to the information collection unit, updates the analysis process in the analysis unit, and provides re-analysis processes or

A unit that receives and processes user requests through the user support department, which provides queries and provides the results to users.

may include a system.

In the information collection step, the information collection unit includes member information set as a search criterion, and information related to the member

can be explored.

In the information collection step, the information collection unit includes keywords as search criteria, and includes a plurality of basic information for general-purpose users.

It is a hierarchical common keyword prepared to search information according to the keyword from the website and classify the search result.

It can be classified and converted into a format including items for which relevance information is set by parsing the information.

In the information collection step, the information collection unit includes a search portal site, a social network site, and a cloud site.

by accessing each open website and searching for information according to the search criteria through a search or public open API

can be collected In addition, these information collection units are divided by type of website, and each information collection unit is a website.

Criteria for classifying search results into common codes according to the type of site, or for parsing search results based on items

Criteria may be different.

In the analysis step, the analysis unit may provide the analysis result back as data to the distributed storage unit. In the analysis step, the analysis unit stores the value analysis result performed based on the item in the utilization database for 1:N correlation analysis. Data can be collected repeatedly.

Big data analysis system and method for marketing according to an embodiment of the present invention is selected based on internal customer information and keywords

Search for information from sources (websites) on the selected network and collect the results in the information collection unit,

In consideration of the characteristics of the information collection unit, the collected information is distributed and stored, and the distributed and stored information is valued through item association analysis.

Analyze with an analysis method that includes analysis and provide the results, but save the analysis results and the provided results again as data

Then, through an iterative process that analyzes the correlation with the newly accumulated and analyzed data,

By effectively analyzing the spread of customer information, even if the analysis information possessed by the company is limited,

Not only does it have the effect of effectively providing information on management support and management, but also individual companies do not

Through the analysis method required by individual customers, by using the information that is organized and collected by a specialized analysis company

It is also possible to provide marketing support information that individual customers want. In this case, individual customers can analyze big data

It has the effect of securing marketing support information or management support information at a low cost.

The big data analysis system and method for marketing according to the embodiment of the present invention requires not limited information of its customers.

In order to actively collect information on the web, but to effectively analyze various atypical information according to the collection target,

Distributed storage by standardizing the collected information collected in various atypical items according to the collection target to a processable level

It constitutes the information collection unit, and it is possible to analyze the value of various collected information on the web based on the items.

by repeating the process of re-analyzing the analyzed information based on new analysis information and items.

By enabling correlation analysis of 1:N relationships based on items, it is possible to quickly analyze time series analysis and viral marketing.

It has the effect of economically providing reliable analysis results.

A big data analysis system and method for marketing according to an embodiment of the present invention stores the analyzed information in a utilization database

After processing the contents of the utilization database by the user's request or the result providing application, the result is provided to the user.

It is provided as a result, and some of them are redistributed by analyzing the events produced in the analysis process to provide these results.

By storing it in the utilization database so that it can be stored or recycled,

It has the effect of increasing the quality of provided marketing information by additionally reflecting the information generated according to experience in the analysis and allowing other users to recycle it, and increases reliability and satisfaction according to its use.

1 is a block diagram of a conventional big data analysis system.
2 is a conceptual diagram of a big data analysis system according to an embodiment of the present invention.
3 is a block diagram of a big data analysis system according to an embodiment of the present invention;

The present invention as described above will be described in detail with reference to the accompanying drawings and embodiments.

The technical terms used in the present invention are only used to describe specific embodiments, and are not intended to limit the present invention.

Note that this is not the intention. In addition, the technical terms used in the present invention have a different meaning in particular in the present invention.

Unless defined, it has a meaning commonly understood by one of ordinary skill in the art to which the present invention pertains.

should not be construed in an overly inclusive sense or in an overly narrow sense. In addition,

When the technical term used in the present invention is an incorrect technical term that does not accurately express the idea of the present invention

should be understood by being replaced with technical terms that can be correctly understood by those skilled in the art. Also used in the present invention

The general terms used should be interpreted according to the definition in the dictionary or according to the context, and excessively

It should not be construed in a reduced sense.

Also, the singular expression used in the present invention includes the plural expression unless the context clearly dictates otherwise.

In the present invention, terms such as “consisting of” or “comprising” refer to several elements or several steps described in the invention.

It should not be construed as all-inclusive, and some components or some steps thereof may not be included.

It should be construed that it may further include additional components or steps.

In addition, terms including ordinal numbers such as 1st, 2nd, etc. used in the present invention will be used to describe the components.

However, the components should not be limited by terms. The terms refer to one component as another

It is used only for the purpose of distinguishing from For example, without departing from the scope of the present invention, the first component may be

The second component may be named, and similarly, the second component may also be referred to as the first component.

Hereinafter, a preferred embodiment according to the present invention will be described in detail with reference to the accompanying drawings, but regardless of the reference numerals, the same

Elements that work or are similar are given the same reference numerals, and overlapping descriptions thereof will be omitted.

In addition, in describing the present invention, detailed descriptions of related known technologies may obscure the gist of the present invention.

If it is determined, a detailed description thereof will be omitted. In addition, the accompanying drawings are to make it easier to understand the spirit of the present invention

It should be noted that the spirit of the present invention is not to be construed as being limited only for the purpose of the accompanying drawings.

2 is a conceptual diagram of a big data analysis system according to an embodiment of the present invention, and the internal

Information search and collection that not only uses information, but actively collects numerous user information generated on the web

The system 10, the distributed storage system 20 for distributing and storing the vast amount of information collected in this way, and distributing to the distributed and stored information

A person who conducts analysis by approaching the processing method and distributes and stores recyclable information among the analysis results

The analysis system 30 and the analysis system 30 receive and provide the analysis result, or the analysis system 30 analyzes the result

to re-perform the necessary analysis based on the results, or to search the analysis results according to the query and provide the results;

Search result information that can be recycled is provided as data to the distributed storage system 20 according to the type and analyzed as it is.

If it can be utilized in the analysis system 30, the result providing system 40 that provides it for recycling, and information search and collection

The system 10 provides search criteria for the information to be collected, and the content to be analyzed (scripts, analysis, and the analysis system 30) is provided to the analysis system 30.

process, etc.) or update the content to be analyzed, and the content for re-analysis in the result providing system 40

(a process such as a script, analysis algorithm, setup, etc.) or a user who provides a query and provides the results to the user

support system 50 . Here, the user support system 50 allows a user to access each of the systems.

It may be an interface, but it may be a system with some functions of each system, so the specific configuration may vary.

there is.

In the end, the configuration shown is not the traditional method of collecting and analyzing standardized internal information, but rather the mobile service, portal,

Diversity arising from websites that provide various services including social network services and cloud services

Among the information, information suitable for the desired analysis target is collected and the desired marketing or management support is provided.

It is a method of performing information analysis.

If you have some information about the member, as well as internal information about the member, the various websites

Various related information may be collected by collecting more information related to the member on the website.

Websites collecting information may be, for example, various portals such as Google, Naver, Daum, Bing, Nate, Yahoo, Baidu, etc.

In addition, information using specific search results or member identifiers can be collected from this, and information provided by each portal

may target web pages, news, blogs, documents, etc. for information collection. In these portals, not only

An open API (Application) that enables search and information collection for various services provided by the portal.

Program Interface) is also provided. Websites that collect this information include, for example, Facebook, Twitter, YouTube

Various social networks such as V, Pinterest, Cyworld, Line, Instagram, Me2day, Tumblr, Listen Me, and Last FM

It can be a network. Most of these social networks are externally searchable for inside information or

They often provide an open API that allows you to do this.

In addition, it is possible to collect information from various websites such as various cloud service sites and mobile service sites.

In many cases, these sites also provide open APIs.

Therefore, it is possible to collect information using a robot, so it is possible to collect information according to the desired

It can collect vast amounts of information.

However, just because such a variety of information on the web is simply collected, it can be directly used for big data analysis.

It is not, and it is suitable for marketing because the collected data is analyzed with an analysis script through a distributed processing method.

It is not possible to generate information.

Accordingly, the embodiment of the present invention basically introduces two new methods. First, to a certain extent, the collected information

The method of composing information collection units corresponding to the types of websites to form

For viral marketing analysis, which increases in importance, value analysis is performed based on items, and then stored

Association analysis of 1:N relationships based on items through an iterative process of analyzing associations with collected and analyzed data

By making this possible, we introduce a method that enables potential value analysis for marketing support.

In addition, analysis requests from real marketing experts (scripts, algorithms, settings, etc. for the desired analysis) or search queries

Result information is generated and provided to users according to

By applying a method that allows the analysis of historical information to be reused, it is practically meaningful rather than simply analyzing large amounts of data.

Make it possible to provide analysis information for marketing support or management support. In addition, the practice of this invention

The system according to the example is not a subordinate system for a specific company, but a specialized service for general-purpose users.

In the case of a generalization, the generally collected information is analyzed according to the analysis needs of each service user, and then the result is analyzed.

can provide In this case, the system utilization increases, so the burden on service users can be reduced, and each service

As the analysis results of the marketing managers of the companies are collected in a recyclable way, these various service users

You will be able to obtain the desired results quickly and in a variety of ways. In addition, by integrating the analysis results with newly collected information,

By analyzing, it is possible to increase the efficiency of time series analysis or correlation analysis based on items.

A more specific example to which such a configuration is applied will be described with reference to FIG. 3 .

3 is a block diagram of a big data analysis system according to an embodiment of the present invention. As shown, a preset type of web

After searching for information according to the search criteria set from the site, the searched information is parsed to provide a hierarchical common code

An information collection unit 100 and an information collection unit provided for each type of website, converting it into a format based on the data and items

A distributed storage unit 200 for distributing and storing the information converted by (100) in the distributed storage 300 with reference to a common code and size;

An analysis program that includes item-based value analysis by accessing the distributed storage unit 200 in a distributed processing method

After analyzing according to the processes, the result is stored in the database unit 400 , and previously stored in the database unit 400 .

The value analysis result and the newly analyzed value analysis result are reanalyzed based on the item, and the result is stored in the database unit 400

The analysis unit 500 that stores further and the analysis result of the database unit 400 are reanalyzed into a desired process or a requested query

search according to the data format and output the results, and analyze the output contents and convert the data to the distributed storage unit according to the data format.

Search criteria of the result providing unit 600 and the information collection unit 100 to provide or store in the database unit 400 for reuse

to provide, update the analysis process of the analysis unit 500, and provide a reanalysis process or query to the result providing unit 600

and a user support unit 700 that provides the result to the user.

Here, the user support unit 700 refers to an integrated user interface as well as a simple interface.

It is also possible to provide an extension function for each related functional unit (information collecting unit 100, analysis unit 500, result providing unit 600).

and, in some cases, may be included in the corresponding functional unit as a partial function of each functional unit. Therefore, user support

The unit 700 may be configured in various ways or may have various functions, so it is not limited to the configuration according to the embodiment of the present invention.

does not

On the other hand, the illustrated distributed storage unit 200 and distributed storage 300 divide the data according to the size and store the data in several storage places.

Various distributed storage methods for storing data can be used. In this embodiment, a well-known Hadoop file

The system (HDFS) is the basis for distributed storage. In this case, the analysis unit 500 performs map reduce using the Hadoop file system.

It can be used as a basis for distributed processing.

The illustrated database unit 400 stores information on files that are distributed and stored or a search criterion for searching the information collection unit 100 .

Code having information on the metadata database 410 and the hierarchical integration code for classification

The database 420, the analysis unit 500, and the result providing unit 600 store the analysis results for analysis, and item-based value division

It includes a utilization database 420 that accumulates the results and stores the results for recycling among the search results.

That is, the database unit 400 substantially described in the description of FIG. 3 described above means the utilization database 420 .

all. Other databases 410 and 430 will be further described later.

Meanwhile, in the illustrated configuration, the information collection unit 100 includes a member information acquisition unit 110 and an information search collection unit 120 , which

Among them, the member information obtaining unit 110 may be selectively applied. The illustrated member information acquisition unit 110 is within the information collection

It collects sub-member information or internal member usage information, and as necessary, the information search and collection unit 120 to various websites

You can provide information that enables you to collect information related to member information when collecting information from the company.

Of course, the information collection unit 100 is a website set based on the keyword set by the user through the user support unit 700 .

It is also possible to configure only the information search and collection unit 120 that collects information from the fields.

As described above, in an embodiment of the present invention, while searching for and collecting desired information from various websites,

The information collection unit that parses them and converts them into a format with appropriate classification codes and items is constructed for each type of website.

make up

This will be described in more detail with reference to FIG. 4 .

4 is a configuration of the information search and collection unit 120 according to an embodiment of the present invention, and the information search of the information search and collection unit 120

The metadata database 410 in which the search criteria for

The configuration of the user support unit 700 provided to 0) is shown.

In an embodiment of the present invention, the illustrated information search and collection unit 120 collects various information to enable big data analysis.

method, which we will look at in more detail.

First of all, it is not a standardized internal information, but various result provision formats or provided results (web pages, documents, bulletin boards, comments, etc.)

Standardized based on items for integrated analysis, and classification criteria to classify searched content by type

to be classified as a hierarchical integration code. The search results provided above for each type of website are different.

The information retrieval unit that analyzes the data in a parsing method and converts it into an integrated code and item-based format

It should be configured according to the type of site. This may change the rules of the website itself or change the status of the search results.

Even if a new website is added, only the relevant information retrieval unit needs to be updated.

In addition to making it easy to manage for information search by adding

Even if there are various types of data, the collected information can be converted into data that can be analyzed in an integrated way. Of course, format like this

Separating the search results to the extent of determining the item by selecting one of the items with similarity even if

is possible, but it is very difficult to match even the data type of the item. Therefore, it is collected as a related item

Even if it is data, the data can be structured or unstructured data.

Select one of several known methods for interworking data and process it.

For this purpose, the illustrated information search and collection unit 120 is a search criterion set in the metadata 410 (keyword, generation of search target information).

Collection management module to search information according to sex time, target website, browsing cycle, browsing degree, member information, etc.)

122 and an information search mode for accessing the website 800 set according to the request of the collection management module 122 to search for information

After parsing the module 121 and the information searched for by the information search module 121 in consideration of the characteristics of the website, the relationship

The data generation module 123 that converts the format based on the defined items, and the information generated by the data generation module 123

and a data providing module 124 provided to the distributed storage 200 .

Here, the data generation module 123 parses the searched information and converts it into a standardized format while the information belongs to

Classification can be added as hierarchical common code information. For example, if the information is about the lipstick you used recently.

It may be common code information corresponding to cotton women's products - cosmetics - lipsticks.

In addition, if necessary, the data generation module 123 anonymizes the collected personal information and encrypts or deletes the identification information.

Security-related processing may also be performed.

On the other hand, since the searched information is information obtained from an arbitrary website, items provided on a specific website are different from other information.

It may not be provided on the website, and items that are verified on a specific web page may not be verified on other web pages.

This may not be the case, so for big data analysis, prepare items that have relationship settings and apply them to the website from there.

Select the combined items so that you can organize them in a prepared format. For example, the user's gender, age, location,

For the items, information corresponding to the related items may or may not be collected. Therefore, in these cases the collection

As basic target information, gender, age, location, etc. are prepared as relevant items, and among them,

The obtained information can be set as a corresponding item. As another example, the user's location information on a certain website

As user IP information, it is collected as information that can confirm the approximate user location, and is used as address information on other websites.

collected, and may be collected as GPS information on another website, all of which may have a relationship as a location item.

there is. However, they each have a different data structure. Therefore, by converting them into specific information (address or GPS location),

It can fit the format or can configure the format by classifying it into appropriate sub-items among location items having a relationship.

all.

In the subsequent analysis of this item information, value analysis according to the relationship between items or 1:N information creation based on items

Since it can be utilized in the analysis of association according to

In the example, this format setting is optimal for the characteristics of the collection target by allowing parsing by reflecting the characteristics of the website.

Transformation is possible.

5 is a configuration example of the distributed storage unit 200 according to an embodiment of the present invention, as shown in the diagram, the distributed storage unit

200 includes a plurality of unit distributed storage units 210 corresponding to a plurality of information collection units separately provided for each type of website.

This unit distributed storage unit 210 searches for the format provided by the information collection unit according to its own conversion rule.

Collect information and check the integrated code for it in the code database 430 to add a classification identifier and the size

is divided and stored in the distributed storage 300 .

Each unit distributed storage unit 210 distributes and stores the collected information in the distributed storage 300 while distributed storage location, file name, and

A collection agent module 211 that provides information about the group code, input date, etc. to the metadata database 410, and

and a data flow control module 212 for dividing and storing the collected data according to the size of the collected data.

FIG. 6 shows the configuration of the analysis unit 500 according to an embodiment of the present invention, and as shown in FIG.

Query distributed data stored in the distributed storage 300 or distributed processing using a MapReduce method, etc. and, if necessary,

Distributed processing to store data in the same format as data in the analysis result back to the distributed storage 300 for recycling

It manages the module 510 and various analysis processes (analysis scripts, algorithms, settings, etc.) including item-based value analysis.

The analysis process module 530 and the analysis process module 530 automatically perform the analysis according to each analysis process.

The individual analysis processes of the data analysis module 520 and the data processing module 530 for performing and calculating the result, etc.

data analysis module by locking, updating, removing, and, if necessary, checking the integrated code information from the code database 430

Analysis of providing to 520, collecting the results analyzed by the data analysis module 520 and recording it in the utilization database 420

a control module 540 . The user support unit 700 provides an analysis process for the desired analysis to the analysis unit 500 .

Alternatively, information on updating an existing process or deleting an existing process can be provided.

The analysis control module 540 performs value analysis by item-based correlation analysis for effective viral marketing analysis.

Analysis processes including (inquiry, structured and unstructured linkage analysis, statistical analysis, text analysis, machine learning, batch analysis, data

Using correlation analysis, pattern extraction, ranking, issue analysis, timing analysis, related word analysis, correlation analysis, regression analysis, etc.)

After analyzing the collected data, the result is stored in the utilization database 420, and the data previously stored in the utilization database is stored.

Re-analyze the previous value analysis result and the newly analyzed value analysis result based on the items and use the results database

Save more to 420. If this process is repeated, 1:N analysis information can be accumulated for items, and through this

Since analysis becomes possible, various information about changes in analysis results can be confirmed. For example, certain lips

How does usage information about tics spread over time or in what direction (by age, region, specific affiliation, website)?

direction), and by analyzing this in relation to the execution of advertisements, the effect of viral marketing can be

can be checked

On the other hand, the data analysis module 520 or the analysis control module 540 stores the analyzed result as data again in the distributed storage 300 .

can be saved.

Here, the utilization database 420 supports high-speed database analysis to effectively perform Hadoop distributed processing.

NoSQL-based database for distributed processing of big data with a length of trillions of rows

You can use HBase. It is configured on an in-memory basis to speed up big data analysis, and the analysis unit

(500) to store the analyzed result so that the stored content can be quickly utilized for various services. of course use

The database 420 has a memory in order to provide compatibility with various other types of databases in addition to the HBase.

It may have the form of a store and an interface. Therefore, it can operate as various types of memory-based databases.

there is.

7 shows the configuration of the result providing unit 600 according to an embodiment of the present invention, and as shown in the figure, the utilization database

To reanalyze the analysis result of 420 as a desired process or search according to the requested query and output the result

A service application module that provides a process or query to utilize the information distribution module 610 and the utilization database 420

By analyzing the module 620 and the result output, the log and the event that can be analyzed according to the data format are transmitted through the distributed storage unit.

Delivered as data to distributed storage and immediately available and serviceable, resulting events are available for reuse in the Leverage Database

It may include an event analysis module 630 that is stored in the switch 420 .

Here, the service application module 620 is a system that interworks with the user and is substantially connected to the user support unit 700 .

It may be a linked interface, and the actual analysis process or query may be provided through the user support unit 700 .

can

On the other hand, some functions of the user support unit 700 may be integrated with the result providing unit 600, in this case the information distribution module

In addition to the function of utilizing the analysis results stored in the utilization database 420, the 610 indicates a new function in the analysis unit 500 if necessary.

A kind of dispatcher that provides a new analysis process to collect the analysis results and output them to the user

It can also provide functions. In this case, the result providing unit 600 is for linking with an external analysis solution or an external analysis solution.

It can be an interface or it can contain an analytics configuration that can be customized to an external user site,

The application module is an analysis engine for distributed processing (for example, Ars, a tool for analysis of distributed processing databases).

It may be an analysis engine configured through R-studio).

On the other hand, users, such as marketers, managers, and advertisers, provide search criteria such as keywords for the analysis they need.

When information is collected, the big data analysis system according to an embodiment of the present invention provides information according to the corresponding search criteria.

Collectively The collected information is distributed and stored, and the analysis information is analyzed by accessing it in a distributed processing method.

Information is accumulated by repeating analysis to enable correlation analysis. This accumulated analysis information

You can query based on the desired criteria to produce results, or propose a new analysis process to utilize the analysis results.

It is based on practical know-how, and it is a part that analysis system designers cannot all support. these threads

By storing the results according to the invincible analysis process or query in the utilization database,

If you request one analysis result, it can be recycled immediately, and the continuous user usage records according to this analysis are

It is learned by the machine learning method in the analysis unit, so that the reliability of the related analysis can be increased.

In the above, preferred embodiments according to the present invention have been shown and described. However, the present invention

It is not limited to the embodiment, and without departing from the gist of the present invention appended in the claims, any person skilled in the art to which the invention pertains will be able to implement various modifications.

10: information search and collection system 20: distributed storage system
30: analysis system 40: result providing system
50: user support system 100: information collection unit
200: distributed storage 300: distributed storage
400: database unit 500: analysis unit
600: result providing unit 700: user support unit

Claims (1)

After searching for information from a preset type of website according to the set search criteria, the searched information is parsed and
an information collection unit provided for each type of website, converting into a format based on related hierarchical common codes and items;
a distributed storage unit for distributing and storing the information converted by the information collection unit with reference to a common code and size;
An analysis program that includes item-based value analysis by accessing the distributed and stored information by the distributed storage unit in a distributed processing method
After analyzing according to the processes, the results are stored in the utilization database, and the data previously stored in the utilization database are stored.
Re-analyze the previous value analysis results and the newly analyzed value analysis results based on the items, and use the results in the above utilization database
an analysis unit to further store it in Ys;
Reanalyze the analysis result of the utilization database as a desired process or search according to the requested query.
output and analyze the output contents and provide it as data to the distributed storage unit according to the data format or for reuse
Big data analysis for marketing, characterized in that it comprises a result providing unit for storing in the utilization database
system.

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