TW201741911A - Processing and interaction method for use in data recommendation, device, and system - Google Patents

Abstract

The invention relates to the field of data processing, and in particular, to a processing and interaction method for use in data recommendation, a device, and a system. The system comprises an interaction device and a data processing device. The interaction device transmits, to the data processing device, acquired data information used by a developer, and state information and corresponding to a determined state of the interaction device, and receives data recommended by the data processing device. The data processing device recommends, according to the data information acquired by the interaction device and the state of the interaction device, and to the interaction device, the data. The method, device, and system are primarily applicable to the field of metadata recommendation.

Description

Method, device and system for processing data recommendation

The invention relates to the field of data processing, in particular to a processing interaction method, device and system for data recommendation.

The relay data, also known as the intermediary data, the relay data, is the information describing the data, mainly the information describing the attribute of the data, and is used to support functions such as indicating storage location, historical data, resource search, and file recording. The traditional relay data management system generally only provides relay data search based on various query criteria, and the recommendation system for relay data is rarely seen in the industry.

In the prior art, due to the lack of a relay data recommendation system, high-quality data cannot be effectively promoted and fully utilized, so that the value of the data is buried; at the same time, the developer generates a large amount of data in the relay data system. The search history is not used effectively, resulting in the inability of the relay data platform to be fully utilized. Developers need to perform repeated and heavy relay data searches every time, especially when developers want to search for similar data. It takes more twists and turns; in addition, the data developer is limited by the known data range, and cannot find other information in the same business domain quickly and easily, which is not conducive to the developer's deep understanding of the data and the data. Innovative applications.

Therefore, in the rapid development of data processing technology, how to efficiently conduct data recommendation and provide users with high-quality information has become an urgent problem in the data management process.

In view of this, the present invention provides a method, device and system for processing data recommendation, and the main purpose is to solve the problem of how to recommend high-quality data to users based on saving user search time.

According to a first aspect of the present invention, the present invention provides a processing interaction system for data recommendation, the system comprising: an interaction device and a data processing device; the interaction device is configured to acquire the information information used by the developer and determine the The status data corresponding to the status is sent to the data processing device, and receives the data recommended by the data processing device to the interactive device; the data processing device is configured to recommend the information according to the information acquired by the interactive device and the state of the interactive device to the interactive device data.

According to a second aspect of the present invention, the present invention provides a data recommendation processing method, which is mainly applied to a data processing device side, and includes: the data processing device extracts basic information for performing data recommendation, and the basic information is used. Performing data matching in the data recommendation process; determining corresponding preset recommendation logic according to the state of the interaction device, the preset recommendation logic using at least one of the basic information Information, recommending data; recommending data to the interactive device based on the determined default recommendation logic and the basic information used.

According to a third aspect of the present invention, the present invention provides an interactive method for data recommendation, which is mainly applied to one side of an interactive device, comprising: an interactive device acquiring information information used by a developer; and transmitting the data information to the data processing And means, wherein the data processing device extracts basic information for performing data recommendation from the material information; and the data recommended by the data processing device is recommended to the developer.

According to a fourth aspect of the present invention, the present invention provides an interactive method for data recommendation, which is mainly applied to one side of an interactive device, and includes: an interactive device determines a current state; and determines a state corresponding to the state The data is sent to the data processing device, so that the data processing device determines the current state of the interactive device according to the status data, and receives the recommended data sent by the data processing device corresponding to the current state of the interactive device.

According to a fifth aspect of the present invention, the present invention provides a processing device for data recommendation, the data processing device comprising: an extracting unit, configured to extract basic information for performing data recommendation, wherein the basic information is used in a data recommendation process. a data matching unit, configured to determine a corresponding preset recommendation logic according to a state of the interaction device, where the preset recommendation logic uses the basic information At least one basic information for performing data recommendation; and a processing unit configured to perform data recommendation to the interactive device according to the determined preset recommendation logic and basic information used therein.

According to a sixth aspect of the present invention, the present invention provides an interactive device for data recommendation, the interaction device comprising: an obtaining unit, configured to acquire material information used by a developer; and a first sending unit, configured to send the data information And the data processing device is configured to: the data processing device extracts basic information for performing data recommendation from the material information; and the first receiving unit is configured to receive the data recommended by the data processing device and perform recommendation to the developer.

According to a seventh aspect of the present invention, the present invention provides an interactive device for data recommendation, the interaction device comprising: a state determining unit, configured to determine a current state according to content displayed by the interactive device; and a second sending unit, And the second receiving unit is configured to receive the status information that is sent by the data processing device, and the data processing device is configured to determine, according to the status data, a current status of the interaction device; Recommended information corresponding to the current state of the interactive device.

With the above technical solution, a method, device and system for processing data recommendation according to an embodiment of the present invention can extract basic information for performing data recommendation in a large amount of data and data related to a developer or a user. The basic information is used to carry out the data in the data recommendation process. Then, according to the state of the developer or the user on the interactive device side, the corresponding preset recommendation logic is determined. Generally, the interactive recommendation device is in different states and uses different recommendation logics for data recommendation, and the preset recommendation logic is used. At least one basic information in the basic information is used for data recommendation; finally, according to the determined preset recommendation logic and the basic information used by the data recommendation, since the data recommendation is avoided, the search is performed from the massive data, but The recommended materials are obtained from the information related to the developer or the user, so that high-quality materials can be recommended to the user more quickly in large-scale and complex data scenarios.

The above description is only an overview of the technical solutions of the present invention, and the above-described and other objects, features and advantages of the present invention can be more clearly understood. Specific embodiments of the invention are set forth below.

11‧‧‧Interactive devices

12‧‧‧Data processing device

61‧‧‧Extraction unit

62‧‧‧Logic determination unit

63‧‧‧Processing unit

611‧‧‧First extraction subunit

612‧‧‧Second extraction subunit

613‧‧‧ third extraction subunit

6111‧‧‧First acquisition module

6112‧‧‧First Statistical Module

6113‧‧‧First Computing Module

6114‧‧‧First extraction module

6115‧‧‧Second acquisition module

6116‧‧‧Second statistical module

6117‧‧‧Second extraction module

6118‧‧‧ Third acquisition module

6119‧‧‧ third statistical module

6120‧‧‧ Third extraction module

6121‧‧‧ Fourth acquisition module

6122‧‧‧Fourth statistical module

6123‧‧‧Fourth extraction module

81‧‧‧Acquisition unit

82‧‧‧First sending unit

83‧‧‧First receiving unit

91‧‧‧State determination unit

92‧‧‧Second sending unit

93‧‧‧second receiving unit

Various other advantages and benefits will become apparent to those skilled in the art from a The drawings are only for the purpose of illustrating the preferred embodiments and are not intended to limit the invention. Throughout the drawings, the same elements are denoted by the same reference numerals. In the drawings: FIG. 1 is a block diagram of a processing interaction system for data recommendation according to an embodiment of the present invention; FIG. 2 is a flowchart of a method for processing data recommendation according to an embodiment of the present invention; FIG. 3 is a flowchart of an interaction method for data recommendation according to an embodiment of the present invention; FIG. 4 is a flowchart of an interaction method for data recommendation according to an embodiment of the present invention; FIG. A schematic diagram of a complete data recommendation logic provided by the example; FIG. 6 is a block diagram showing the composition of a data processing apparatus according to an embodiment of the present invention; and FIG. 7 is a block diagram of a data processing apparatus according to an embodiment of the present invention. FIG. 8 is a block diagram showing the composition of an interactive device for data recommendation according to an embodiment of the present invention; FIG. 9 is a block diagram showing the composition of an interactive device for data recommendation according to an embodiment of the present invention.

Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While the invention has been shown and described with reference to the embodiments Rather, these embodiments are provided so that this disclosure will be more fully understood and the scope of the disclosure will be fully disclosed.

In today's lack of recommendation systems in the field of relay data, high-quality information can't be displayed in front of developers in the first time, while developers are deploying funds. When data search is performed in the material system, a large amount of search history cannot be effectively utilized, and the ability of the relay data platform cannot be fully utilized. Developers need to perform repeated and heavy relay data search every time, especially developers want Searching for similar information on a profile requires more twists and turns.

In order to solve the above problem, an embodiment of the present invention provides a processing interaction system for data recommendation. As shown in FIG. 1 , the system includes: an interaction device 11 and a data processing device 12; and the interaction device 11 is configured to acquire the data used by the developer. The information and the determined status data corresponding to the state in which it is located are sent to the data processing device 12, and the data recommended by the data processing device 12 to the interactive device 11 is received; the data processing device 12 is configured to use the information and interactions acquired by the interactive device 11 The current state of the device 11 is recommended to the interactive device 11.

Further, the interactive device 11 in the system has the function of the device shown in FIG. 8 for acquiring the material information used by the developer; and transmitting the material information to the data processing device 12, so that the data processing device 12 is The basic information for performing data recommendation is extracted from the data information; the data recommended by the data processing device 12 is received, and the recommendation is made to the developer.

In addition to the functions of the device shown in FIG. 8, the interactive device 11 in the system has the function of the device shown in FIG. 9 for determining the current state of the interactive device 11; The status data is sent to the data processing device 12, so that the data processing device 12 determines the current state of the interactive device 11 based on the status data; The recommendation information sent by the processing device 12 corresponding to the state in which the interactive device 11 is currently located.

Further, the data processing device 12 in the system has the functions of the devices shown in FIG. 6 and FIG. 7 for extracting basic information for performing data recommendation, and the basic information is used for data matching in the data recommendation process; The state of the interaction device 11 determines a corresponding preset recommendation logic, and the preset recommendation logic uses at least one basic information in the basic information to perform data recommendation; according to the determined preset recommendation logic and basic information used thereof The interactive device 11 performs data recommendation.

The data interaction recommendation processing system provided by the embodiment of the present invention can extract basic information for performing data recommendation in a large amount of materials and materials related to a developer or a user, and the basic information is used in the data recommendation process. Perform data matching; then determine corresponding preset recommendation logic according to the state of the developer or user on the interactive device side, and generally use different recommendation logic for data recommendation for the interactive device in different states, the preset recommendation The logic uses at least one basic information of the basic information to perform data recommendation; finally, the data recommendation is performed according to the determined preset recommendation logic and the basic information used thereof, because the search for massive data is avoided when performing data recommendation, It is to obtain recommended materials in the materials related to developers or users, so it is possible to recommend high-quality materials to users more quickly in large-scale and complex data scenarios.

The processing interaction system for data recommendation provided by the embodiment of the present invention not only relates to an interactive method of data recommendation on the side of the interactive device, but also relates to a method for processing data recommendation on the side of the data processing device, and thus The method of the data processing device in the system and the method on the side of the interactive device are respectively described in the embodiment of the present invention.

The embodiment of the invention provides a method for processing data recommendation, which can promptly recommend high quality materials to users in a large-scale and complex data scene. The method is applied to a data processing device, as shown in FIG. 2, the method includes:

201. The data processing device extracts basic information for performing data recommendation, and the basic information is used for data matching in the data recommendation process.

With the advent of the era of big data, users need to find the information they need in a large amount of data, but in traditional data systems such as relay data management systems, developers or users need to conduct based on various query criteria. Following the data search. However, in the existing data systems, data developers are limited by the scope of their own known data, especially the limitations of their own input query criteria, such as their own input keywords, search scope and other restrictions, usually make data developers unable to Quickly and easily discover other materials in the same business area. Therefore, in the embodiment of the present invention, when performing data recommendation, step 201 is first performed: extracting basic information for performing data recommendation, where the basic information includes information information generated by the developer itself and information information related to the developer. And the basic information is used for data matching in the data recommendation process.

202. Determine, according to a state in which the interaction device is located, a corresponding preset recommendation logic, where the preset recommendation logic uses at least one basic information in the basic information to perform data recommendation.

Since the existing data system needs to recommend data according to the query criteria input by the developer or the user, the recommendation logic used in the data recommendation is relatively simple, and the query is based on the query criteria of the developer or the user, which results in the effect of the data recommendation. The pros and cons of the query criteria. For the above reasons, in order to obtain a higher quality recommendation result when performing data recommendation, the embodiment of the present invention needs to determine specific recommendation logic according to the state of the user or the developer on the side of the interactive device, and different recommendation logics. Different basic information is used, but each recommendation logic uses at least one of the basic information in the basic information for material recommendation.

203. Perform data recommendation to the interactive device according to the determined preset recommendation logic and basic information used therein.

After the basic information for performing the data recommendation is extracted by step 201, and the preset recommendation logic corresponding to the state of the interactive device is determined by step 202, step 203 may be performed: according to the determined preset recommendation logic and The basic information used is recommended for information. Because the basic information extracted in step 201 is the material information generated by the developer itself and the material information related to the developer, and the recommendation logic determined in step 202 is the recommendation logic related to the state of the developer on the side of the interactive device. Therefore, when the recommendation is combined with the recommendation logic and the basic information used, the recommendation of the data can be more accurately performed to the developer or the user.

Corresponding to the method shown in FIG. 2 above, an embodiment of the present invention provides an interaction method for data recommendation, which is applied to one side of an interactive device, as shown in FIG. 3, the method includes:

301. The interactive device obtains information information used by the developer.

Usually when a developer or user operates on the interactive device side, it will involve a large amount of data information, which can reflect the relationship between the developer and the data from the side, especially for the historical data of the developer operation. Research can be used to infer the developer's preferences and needs for the data, so you can refer to the developer's information to recommend the information to the developer. Since the developer or the user usually performs a series of operations involving the information information on the side of the interactive device, such as browsing the data table, searching for the keyword, creating the data table, etc., the embodiment of the present invention needs to perform step 301 to acquire the developer. Information information.

302. Send the data information to the data processing device, so that the data processing device extracts basic information for performing data recommendation from the data information.

After the interactive device obtains the information information used by the developer, the information information needs to be sent to the data processing device. Because the developer has a large amount of information involved in the operation of the interactive device side, and for historical data information, there is often a large amount of invalid data, such as the developer inputting the wrong material information, and the developer creating the wrong material information. Or browsing the wrong information, etc., so if you blindly select a specific data from a large amount of information to recommend to the developer on the side of the interactive device, the effective recommendation effect will not be achieved. Therefore, the information needs to be extracted by the data processing device to obtain representative basic information, which can be used to recommend data to the interactive device.

303. Receiving data recommended by the data processing device and pushing the developer recommend.

When the interactive device sends the data information used by the developer to the data processing device, the data processing device extracts representative basic information from a large amount of data information, and combines the basic information with the state of the interactive device. , recommend information to the interactive device. The state in which the interactive device is located is the state when the developer operates on the interactive device side, such as the developer searching for keywords on the interactive device or browsing the data table on the interactive device; and the data processing device will be the developer. The information searched on the interactive device or the information of the browsed data table is matched with the extracted basic information. Since the basic information is related to the developer and is representative information about the developer, the interactive device receives To the successful matching data recommended by the data processing device, the data can largely meet the needs or preferences of the developer, thereby achieving the purpose of recommending data to the developer according to the state of the interactive device.

Corresponding to the method shown in FIG. 2 and the method shown in FIG. 3, the embodiment of the present invention further provides an interaction method for data recommendation, which is applied to one side of the interactive device, as shown in FIG. Methods include:

401. The interactive device determines the current state.

Developers or users typically perform multiple types of operations on interactive devices, such as developers searching for information on interactive devices or browsing data on interactive devices. These different operations display different content on interactive devices. Put the interactive device in a different state. Therefore, as an optional implementation manner, the interaction device in the embodiment of the present invention may determine the current state according to the content displayed by the embodiment, and the determining process may be The developer or the user selects the state according to the content displayed by the interactive device, and of course, the interactive device can determine the current state according to the content displayed by the interactive device. For example, when a developer searches for information on an interactive device, the interactive device typically displays the search interface, searched keyword information, and even other keyword information associated with the keyword information; or, when the developer When browsing data information on an interactive device, text information such as data sheets and documents are usually displayed on the interactive device. Since the developer performs different operations on the interactive device, the content displayed on the interactive device is also different, so the interactive device can determine the current state according to the content displayed by the interactive device. When the interactive device displays the keyword information input by the developer, it can be determined that the current state of the interactive device is the state of the search keyword; when the interactive device displays text information such as a data sheet or a document, the current device can be determined. The status is the status of browsing data. When the interactive device is in different states, the information recommended to the interactive device is often different. When the interactive device is in the state of searching for a keyword, it is required to recommend to the interactive device the information associated with the searched keyword and the matching device; When browsing the status of the data sheet, it is necessary to recommend the data associated with the browsed data sheet to the interactive device. Therefore, when recommending information to the interactive device, it is first necessary to determine the current state by the interactive device. Therefore, step 401 needs to be performed to determine the current state.

402. Send the determined status data corresponding to the status to the data processing device, so that the data processing device determines, according to the status data, a current state of the interaction device.

When the interactive device determines the current state, it needs to determine The status data corresponding to the status is sent to the data processing device, so that the data processing device determines the current state of the interactive device based on the status data. The state data in the embodiment of the present invention is used to describe the state, and the different states correspond to different state materials. Specifically, the status information may be represented by a status identifier. For example, when the interactive device is in the state of the search keyword, the corresponding status identifier in the embodiment of the present invention may be “state-search”; when the interactive device is in the browsing data table. In the state of the embodiment, the corresponding state identifier in the embodiment of the present invention may be “state-scan”, and the data processing device can determine the current state of the interaction device according to the received state identifier.

403. Receive recommended information sent by the data processing device corresponding to the current state of the interaction device.

After the interactive device sends the status data corresponding to the current state to the data processing device, the data processing device determines the current state of the interactive device according to the specific status data, and uses the status and the information for recommending the data. The basic information is combined, and the recommended information matching the state is selected from the basic information and sent to the interactive device. Since the basic information is representative information information related to the developer or the user extracted from the large amount of data information used by the data processing device from the interactive device side, the interactive device receives the recommended information sent by the data processing device. To the extent that the developer's needs or preferences are met, the purpose of recommending information to the developer based on the state of the interactive device is achieved.

The method for processing data recommendation in the embodiment of the present invention can extract basic information for performing data recommendation in a large amount of data and data related to a developer or a user, and the basic information is used in the data. Data matching is performed during the recommendation process; then the corresponding preset recommendation logic is determined according to the state of the developer or user on the interactive device side, and the recommended recommendation logic is generally used for the interaction of the interactive device in different states. The preset recommendation logic uses at least one basic information of the basic information to perform data recommendation; finally, the data recommendation is performed according to the determined preset recommendation logic and the basic information used thereof, because the data recommendation is avoided from the massive data. Searching, but obtaining recommended materials in materials related to developers or users, it is possible to recommend high-quality materials to users more quickly in large-scale and complex data scenarios.

In order to better understand the methods shown in FIG. 2, FIG. 3 and FIG. 4, as a refinement and expansion of the above embodiments, the embodiments of the present invention will be performed for the steps in FIG. 2, FIG. 3 and FIG. Detailed description.

Since in the embodiment of the present invention, the developer usually operates on the interactive device, and the operation involves a large amount of material information, which is often related to the developer's preferences or needs. Therefore, the data processing device not only needs to refer to the data generated or used by the developer when referring to the interactive device, but also needs to refer to data generated by other developers having a relationship with the developer, that is, extracting data for recommendation. The basic information needs to be extracted from the interactive device to return a large amount of data information to the data processing device, extract developer behavior history information for recommending the data, preset the relay data label within the recommended range, and/or reduce the recommendation. Scope of relationship data. What needs to be explained here is the developer behavior history information extracted from the large amount of data information returned by the interactive device to the data processing device, the relay data tag or the relationship resource within the preset recommendation range. It is expected that any of the three types of information can be used in the process of recommending data to the interactive device. Even if one of the types of information is used alone, the accuracy of the data recommendation can be improved in one aspect or to some extent. As a preferred embodiment, when the data recommendation is performed to the interactive device, the data processing device can simultaneously use the developer behavior history information, the relay data label in the preset recommendation range, and the relationship data, thereby achieving more accurate data recommendation. effect.

The material information acquired by the interaction device and sent to the data processing device generally includes: a keyword searched by the developer, a browsed data table, a created data table, and/or a data table on which the data table is created, and the interactive device sends the data table. The more comprehensive the type of material information for the data processing device, the more representative the basic information extracted by the data processing device for data recommendation, and the more accurate the subsequent recommended information to the interactive device. The developer behavior history information extracted by the data processing device from the data information is the material information that the developer has used or generated or relied on, and is the most critical part for accurate data recommendation; the relay data label in the preset recommendation range Need to be combined with developer behavior history information, you can match the approximate data, which is characterized by a wide range of matching; and the relationship data is used to narrow the matching breadth, so as to accurately and quickly search and recommend data. In the embodiment of the present invention, the relay data label in the preset recommended range generally refers to a table that removes the temporary table, the table size is less than 10 MB, the developer's own table, the table used by the developer in the last week, and no downstream dependency. The relay data label of the data table other than the table (if a data table does not directly generate other data tables, the data table is a table without downstream dependencies). Setting the preset recommendation It is to avoid repeated search and recommendation of data when recommending data. The following is an explanation of the extraction of the basic information of these three parts.

For the data processing device to extract developer behavior history information, the main three kinds of information information are extracted:

(1) extracting the search keyword of the developer within the preset time;

In the specific execution process, the main process is to obtain the history of the search keywords of the developer within a preset time, wherein the preset time can be set according to requirements, if the demand is for the information that is desired to be searched for the last half year. , you can set the preset time to 6 months. In the embodiment of the present invention, one month may be taken as the preset time, that is, the search keyword history of the developer within one month is acquired; and then the invalid keyword is removed from the history of the search keyword and is valid. Search for keywords; the invalid keywords include: stop words and special characters.

When a valid search keyword is obtained within 1 month, the weighted algorithm can be used to count the weight of the effective search keyword. The embodiment of the present invention does not limit the specific weighting algorithm. As an optional implementation manner, the TF-IDF algorithm can be used to calculate the weight of the effective search keyword. According to the calculation formula of the TF-IDF algorithm, it needs to be borrowed. The word frequency of the valid search keyword and the frequency of the reverse file are calculated, wherein the frequency of the word of a valid search keyword is equal to the frequency of the effective search keyword in the effective search keyword within 1 month; the reverse file frequency is equal to the data The total number of tables is divided by the number of files containing the valid search keywords, and the resulting quotient is obtained in logarithm. Of course, as a simple way of processing, you can also participate in the subsequent words by using the word frequency of the effective search keyword as its weight. In the middle.

After the weights of the valid search keywords are counted, in order to more accurately perform the sorting of the valid search keywords, the embodiment of the present invention also needs to consider the influence of the time, and the specific value may be based on the weights corresponding to the valid search keywords. And the search time calculates the time weighted value of the valid search keyword. Wherein, the search time corresponding to the valid search keyword needs to be converted into the digit of yyyyMMdd, and the time weighted value of the effective search keyword is calculated according to the formula yyyyMMdd/time factor + (weight value * weight factor), and finally the calculated time weight value In the order of large to small, the first predetermined number of search keywords are extracted from the effective search keywords as the search keywords of the developer within a preset time of one month, and the first preset number may be For 10, which is the 10 most representative (most frequently used or most concerned) keywords that developers have in a one-month default period. It should be noted here that if the weight of the effective search keyword is counted by the weighted algorithm, it is simple to use the word frequency of the effective search keyword as the statistical result of the weighted algorithm, and then calculate the time weighted value of the effective search keyword. It is calculated by the formula yyyyMMdd/time factor + (word frequency * word frequency factor). Among them, the time weighting value is 100 is the best, and the word frequency factor in the formula can be adjusted according to different situations. The adjustment is mainly based on the following aspects: if the word frequency is to be reduced, the influence of the word frequency on the representativeness of the effective search keyword is The word frequency factor can be set to a value less than one, and if the influence of the word frequency on the representativeness of the effective search key is to be enhanced, the word frequency factor can be set to a value greater than one.

(2) extracting the relay data extraction keyword of the table created by the developer;

In the specific execution process, the main step is to obtain the relay data label of the table created by the developer, and the relay data label is derived from the table name of the data table, the table comment, and the field comment. After obtaining the relay data label of the table created by the developer, it is required to collect the weight of the obtained relay data label in the full amount of the relay data label (global label), that is, the weighted algorithm is used to collect the statistics created by the developer. The weight of the table's relay data label in the label of all data sheets. Of course, as a simple processing method, it is also possible to directly count the word frequency of the relay data label of the table created by the developer in the label of all the data tables. The specific statistical method is similar to the weight of the search key of the above-mentioned statistical developer in the preset time, and will not be described here.

After the weight of the relay data label of the table created by the developer is counted, the weight of the relayed data label of the statistics may be extracted in the order of the obtained relay data label. The second preset number of relay data labels is used as a relay data extraction key for the table created by the developer. The second preset number may be 10, that is, the most representative 10 relay data labels in the global label are selected as the table created by the developer in the relay data label of the table created by the developer. Relay data extraction keywords.

(3) Extract the relay data extraction keyword of the table that the developer depends on.

First of all, the table that the developer depends on means that when the developer develops the table A, the table A is directly developed on the basis of the table B, and the table B is a table that the developer depends on. In the specific execution process, this step is mainly to obtain the relay data label of the table that the developer depends on, and to relay the data label. From the table name of the data table, the table comment (comment), the field comment (field comment), after obtaining the relay data tag of the table that the developer depends on, the relay data tag that needs to be obtained by statistics is in full. The weight in the relay data tag (global tag), that is, the weighting algorithm is used to count the weight of the relay data tag of the table that the developer depends on in the tag of all data tables. Of course, as a simple processing method, it is also possible to directly count the word frequency of the relay data label of the table that the developer depends on in the label of all the data tables. The specific statistical method is similar to the weight of the search key of the above-mentioned statistical developer in the preset time, and will not be described here.

After the weight of the relay data label of the table that the developer depends on is counted, the weight of the relayed data label may be extracted in the order of the obtained relay data label. The three preset number of relay data tags serve as relay data extraction keywords for the tables that the developer relies on. The third preset number may be 10, that is, the most representative 10 relay data labels in the global label are selected as the developer dependent table in the relay data label of the table that the developer depends on. Relay data extraction keywords.

For the extraction of the relay data label within the preset recommendation range, in order to avoid repeated search and recommendation of data when performing data recommendation, the main purpose is to remove the temporary table, the table whose table size is less than 10 MB, the developer's own table, After the developer uses the table for the last week and the table without the downstream dependency, the keywords that are the relay data tags are extracted from the table information of the other data tables: (1) extracting the table name as the keyword of the relay data tag; (2) ) extract the table comment as the keyword of the relay data tag; (3) extract the field Comment is the keyword for the relay data tag. After obtaining these keywords as relay data tags, it is also necessary to use a weighted algorithm to count the weights of the keywords of these relay data tags in the data table, and the specific statistical methods are compared with the above-mentioned statistical developers at preset times. The key weights of the search within are similar and will not be described here. Finally, in accordance with the weights of the keywords as the relay data labels, the keywords of the fourth preset number of relay data labels are extracted in each data table as the preset recommended range. Relay data label. The fourth preset number may be 10, that is, the most representative 10 relay data labels in the global label are selected as the full quantity in the relay data label of the data table in the preset recommended range. Set the relay data label within the recommended range. It should be noted that when the weight of the keyword of the extracted relay data label is statistically counted, since the table name and the table comment are more able to summarize the role of the data table than the field comment, the final determination is derived from the table name and When the weight of the keyword of the relay data tag of the comment is added, the calculated weight is added to the preset value, and the value can be set. The larger the value, the key of the relay data tag from the table name and the form comment. The more representative the word, the weight of the keyword of the relay data tag derived from the table name and the table comment can be added to 0.05 in the embodiment of the present invention.

For the extraction of relational data, since in a six-dimensional space theory, up to five people can make contact between any two people, the depth of the developer relationship should not be too deep when narrowing the data search range by relational data. Otherwise, it will not achieve the purpose of narrowing the search. In the embodiment of the present invention, according to the depth of the developer relationship, the developer may select Developers with preset hierarchical relationships form relationship data for narrowing the scope of recommendations. According to the actual test, the three-layer depth relationship data can be selected for data recommendation. For example, if developer A develops data sheet A, developer B develops data sheet B on the basis of data sheet A, and developer C develops data sheet C on the basis of data sheet B, then the developer A, B, and The three-layer depth developer relationship, the data sheets A, B, and C developed by each are three-layer depth relationship data.

After extracting the basic information for performing material recommendation by the above embodiment, it is also necessary to use the recommendation logic for data recommendation. The embodiment of the present invention is different from the prior art in that the data search query is performed based on the query criteria input by the user, but the corresponding preset recommendation logic needs to be determined according to the current state of the interaction device. Generally, the recommendation logic needs to be combined with different Basic information for information recommendation. The recommendation logic preset in the embodiment of the present invention can be divided into three types according to the state of the interaction device: (1) no context, recommendation based on the developer behavior history; (2) recommendation based on the search keyword; (3) Recommend based on a specific data sheet.

In the embodiment of the present invention, when recommending data to the interactive device, it is not only necessary to use the representative basic information related to the developer or the user extracted from the large amount of data information acquired from the interactive device side, but also needs to be combined with different states. The recommendation logic is recommended. Therefore, the data processing apparatus of the embodiment of the present invention further needs to perform data recommendation to the interactive device correctly after determining the current state of the interactive device. Specifically, the data processing device needs to receive the status data sent by the interactive device corresponding to the state in which the interactive device is located. In the embodiment of the present invention, the preset recommendation logic There are usually three types of interaction devices corresponding to the series: 1. The interactive device is in the current state without context; 2. The interactive device is in the state of searching for keywords; 3. The interactive device is in the state of browsing the data table. When the interactive device determines that it is currently in a state without context, the state data corresponding to the state without context (which may be state-null) is sent to the data processing device; when the interactive device determines that the current search keyword is in the state, The status data corresponding to the status of the search keyword (which may be state-search) is sent to the data processing device; when the interactive device determines that the status of the browsing data table is currently being viewed, the status data corresponding to the status of the browsing data table is Can be sent to the data processing device for state-scan). The data processing device can determine the current state of the interactive device according to the received status data, thereby selecting recommendation logic corresponding to the status to perform data recommendation. The status data corresponding to the status may be represented by other forms except for the status identifiers exemplified in the embodiment of the present invention. For example, the status data may be represented by “state-IDX”, and the X may be an Arabic numeral number or an English letter. Number, etc.

After the data processing device extracts the basic information for performing the data recommendation and determines the corresponding recommendation logic by the state of the interactive device, the specific information can be selected from the basic information and recommended to the interactive device. Specifically: when the state of the interactive device is the current state without context, in general, when the developer or user is in the home page of a website, that is, in the state without the current context, at this time, the recommendation system will perform the most Complete recommendation logic processing, as shown in Figure 5, that is, combined with the extracted user behavior calendar The history information is matched in the relay data tag in the extracted preset recommendation range, and the extracted relationship data is used to narrow the search range, and the search data is narrowed and the data corresponding to the successfully relayed relay data tag is matched to the interactive device. The developer on the side makes recommendations.

When the state of the interactive device is the developer search keyword, that is, when the developer or the user searches for the keyword, the searched keyword is the current context, which can reflect the developer's intention. At this time, the recommendation system performs matching according to the keyword searched by the user in the extracted relay data tag in the preset recommended range, and uses the extracted relationship data to narrow the search range, and narrows the search range to match the successful one. Follow the data corresponding to the data tag to the developer of the interactive device. What needs to be explained here is that the current data recommendation similar to the whole society has not yet been formed. The general data usage is limited to the internal use of the enterprise. Therefore, by default, all the data within the preset recommended range will participate in the recommendation. In order to avoid duplicate data in the search results, it is necessary to exclude the search result data of the current page. When the data recommendation for the whole society is formed in the future, the information that can be recommended must be carefully selected or determined by the advertiser.

When the state of the interactive device is the developer browsing the data table, that is, when the developer or the user browses a specific data table, the data table is the current context, and at this time, the recommendation system will extract the data. The relay data label of the table is matched in the extracted relay data label in the preset recommended range, and the data corresponding to the successfully matched relay data label is recommended to the developer of the interactive device.

For interactive devices, when the developer is on the interactive device When the webpage is not operated, the interactive device receives the information recommended by the data processing device and displays the data to the developer, and the data is processed by the data processing device by using the developer behavior history information and the preset recommendation range. The relay data tag is matched and obtained by using the relationship data to narrow the search range; when the developer searches for the keyword on the interactive device, the interactive device receives the data recommended by the data processing device, and the data is borrowed by the data processing device. By matching the searched keyword with the relay data tag in the preset recommended range, and using the relationship data to narrow the search range; when the developer browses the data table on the interactive device, the interactive device receives the data. The data recommended by the processing device is obtained by the data processing device by matching the label of the data table browsed by the interactive device with the relay data label in the preset recommended range.

In the embodiment of the present invention, the recommendation system can adopt different recommendation logics according to different states of the interaction device, and combine the corresponding basic information to perform data recommendation, and the basic information is information information closely related to the developer, thereby being able to be more Accurately recommend to developers what information developers may need.

Further, as an implementation of the method shown in FIG. 2, an embodiment of the present invention provides a processing device for data recommendation, which is referred to as a data processing device. As shown in FIG. 6, the data processing device includes: an extracting unit 61. The logic determining unit 62 is configured to extract basic information for performing material recommendation, the basic information is used for data matching in the data recommendation process, and the logic determining unit 62 is configured to perform interaction according to the interaction. The status of the device is determined Corresponding preset recommendation logic, the preset recommendation logic uses at least one basic information in the basic information to perform data recommendation; and the processing unit 63 is configured to use, according to the determined preset recommendation logic and basic information used by the The interactive device performs data recommendation.

Further, as shown in FIG. 7, the extracting unit 61 includes: a first extracting subunit 611 for extracting developer behavior history information for performing material recommendation; and a second extracting subunit 612 for extracting a preset recommended range. The relay data tag in the third extraction sub-unit 613 is configured to extract relationship data for narrowing the recommendation range.

Further, the first extraction subunit 611 is configured to extract a relay data extraction keyword of a table created by the developer, a relay data extraction keyword of a table that the developer depends on, and/or a search key of the developer within a preset time. The words together constitute the developer's behavior history information.

Further, as shown in FIG. 7, the first extraction subunit 611 includes: a first acquisition module 6111, configured to acquire a history record of a search keyword of the developer within a preset time, from the history of the search keyword. Obtaining a valid search keyword after culling the invalid keyword; the invalid keyword includes: a stop word and a special character; the first statistic module 6112 is configured to use a weighted algorithm to count the weight of the valid search keyword; The calculation module 6113 is configured to calculate a time weighted value of the valid search keyword according to the weight corresponding to the effective search keyword and the search time; The first extraction module 6114 is configured to extract, according to the calculated time weighting value, the first preset number of search keywords in the effective search keyword as the search keyword of the developer within the preset time.

Further, as shown in FIG. 7, the first extraction subunit 611 further includes: a second acquisition module 6115, configured to acquire a relay data label of a table created by the developer; and a second statistics module 6116, configured to obtain statistics The weight of the relay data label in the full amount of the relay data label; the second extraction module 6117 is configured to extract, according to the weight of the statistical relay data label, the obtained relay data label The second preset number of relay data tags are used as relay data extraction keywords of the table created by the developer.

Further, as shown in FIG. 7, the first extraction subunit 611 further includes: a third acquisition module 6118, configured to acquire a relay data label of a table that the developer depends on; and a third statistics module 6119, which is used for statistical acquisition. The weight of the relay data label in the full amount of the relay data label; the third extraction module 6120 is configured to extract, according to the weight of the statistical relay data label, the obtained relay data label The third predetermined number of relay data tags serve as relay data extraction keywords for the tables that the developer relies on.

Further, as shown in FIG. 7, the second extraction subunit 612 includes: The fourth obtaining module 6121 is configured to extract a keyword as a relay data label in the table information of the data table, and the fourth statistical module 6122 is configured to use the weighting algorithm to collect the keyword as a relay data label. The fourth extraction module 6123 is configured to extract, according to the weight of the keyword as the relay data label, a keyword of the fourth preset number of relay data labels in each data table as The relay data label within the preset recommended range.

Further, the fourth statistic module 6122 is configured to add the weight of the keyword as the relay data label when the keyword used as the relay data label is derived from the table name or the table annotation in the table information. The preset value.

Further, the third extraction sub-unit 613 is configured to select, in the developer according to the depth of the developer relationship, a developer having a preset hierarchical relationship to form relationship data for narrowing the recommendation range.

Further, the processing unit 63 is configured to match the developer behavior history information with the relay data label in the preset recommendation range when the interaction device is in the current state without context, and use the extracted relationship data to narrow the search scope, and After the search range is narrowed, the data corresponding to the successfully matched relay data label is recommended to the interactive device; the processing unit 63 is further configured to: when the interactive device is in the state of the search keyword, the keyword searched by the interactive device and the preset recommended range The relay data tag in the match is matched, and the extracted relationship data is used to narrow the search range, and the search range is narrowed down to match the successfully matched relay data tag. The data is recommended to the interactive device. The processing unit 63 is further configured to match the label of the data table browsed by the interactive device with the relay data label in the preset recommended range when the interactive device is in the state of browsing the data table, and the matching is successful. The data corresponding to the relay data label is recommended to the interactive device.

Further, as an implementation of the method shown in FIG. 3, an embodiment of the present invention provides an interactive device for data recommendation. As shown in FIG. 8, the interaction device includes: an obtaining unit 81, a first sending unit 82, and a first The receiving unit 83 is configured to acquire the material information used by the developer, and the first sending unit 82 is configured to send the material information to the data processing device, so that the data processing device extracts the data information. The basic information for performing data recommendation; the first receiving unit 83 is configured to receive the recommended data of the data processing device and make recommendations to the developer.

Further, the basic information for performing data recommendation extracted by the data processing device from the data information sent by the first sending unit 82 includes: developer behavior history information, a relay data label within a preset recommended range, and/or used to narrow the recommendation. Scope of relationship data.

Further, the first receiving unit 83 is configured to: when the interactive device is in the current state without context, the receiving data processing device matches the developer behavior history information with the relay data label in the preset recommended range, and uses the relationship. The data corresponds to the data corresponding to the successfully matched relay data label obtained after narrowing the search range.

Further, the first receiving unit 83 is configured to: when the interactive device is in the state of the search keyword, the receiving data processing device matches and uses the keyword searched by the interactive device with the relay data tag in the preset recommended range. The relationship data is obtained by narrowing the search range and obtaining the matching data of the relay data label.

Further, the first receiving unit 83 is configured to: when the interactive device is in the state of browsing the data table, the receiving data processing device matches the tag of the data table browsed by the interactive device with the relay data tag in the preset recommended range. The obtained data corresponding to the successfully matched relay data label.

Further, as an implementation of the method shown in FIG. 4, an embodiment of the present invention provides an interactive device for data recommendation. As shown in FIG. 9, the interaction device includes: a state determining unit 91, a second sending unit 92, and a a receiving unit 93, wherein the state determining unit 91 is configured to determine a state in which the interactive device is currently located; and the second sending unit 92 is configured to send the determined state data corresponding to the state to the data processing device for data The processing device determines the current state of the interactive device according to the status data; and the second receiving unit 93 is configured to receive the recommended information of the current state of the corresponding interactive device sent by the data processing device.

Further, the state determined by the state determining unit 91 includes the state in which the interactive device is in the current state without context, the state in which the interactive device is in the search keyword, and/or the state in which the interactive device is in the browsing data table.

Further, the second receiving unit 93 is configured to when the interactive device is in the When there is no context before, the recommendation data corresponding to the state without context sent by the data processing device is received.

Further, the second receiving unit 93 is configured to receive the recommended information of the status of the corresponding search keyword sent by the data processing device when the interactive device is in the state of the search keyword.

Further, the second receiving unit 93 is configured to receive the recommended information of the status of the corresponding browsing data table sent by the data processing device when the interactive device is in the state of browsing the data table.

The device for processing information recommendation provided by the embodiment of the present invention can extract basic information for performing data recommendation in a large amount of materials and materials related to a developer or a user, and the basic information is used in the data recommendation process. Perform data matching; then determine corresponding preset recommendation logic according to the state of the developer or user on the interactive device side, and generally use different recommendation logic for data recommendation for the interactive device in different states, the preset recommendation The logic uses at least one basic information of the basic information to perform data recommendation; finally, the data recommendation is performed according to the determined preset recommendation logic and the basic information used thereof, because the search for massive data is avoided when performing data recommendation, It is to obtain recommended materials in the materials related to developers or users, so it is possible to recommend high-quality materials to users more quickly in large-scale and complex data scenarios.

In the above embodiments, the descriptions of the various embodiments are different, and the details that are not detailed in a certain embodiment can be referred to the related descriptions of other embodiments.

It can be understood that the related features in the above method and device can be Cross-reference. In addition, "first", "second", and the like in the above embodiments are used to distinguish the embodiments, and do not represent the advantages and disadvantages of the embodiments.

A person skilled in the art can clearly understand that for the convenience and brevity of the description, the specific working process of the system, the device and the unit described above can refer to the corresponding process in the foregoing method embodiment, and details are not described herein again.

The algorithms and displays provided herein are not inherently related to any particular computer, virtual system, or other device. Various general purpose systems can also be used with the teaching based on the teachings herein. The structure required to construct such a system is apparent from the above description. Moreover, the invention is not directed to any particular programming language. It is to be understood that the present invention may be embodied in a variety of programming language, and the description of the specific language has been described above in order to disclose the preferred embodiments of the invention.

In the description provided herein, numerous specific details are set forth. However, it is understood that the embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques are not shown in detail so as not to obscure the understanding of the description.

Similarly, the various features of the present invention are sometimes grouped together into a single embodiment in the above description of the exemplary embodiments of the invention in order to the , diagram, or description of it. However, the method of the disclosure should not be construed as reflecting the intention that the claimed invention requires more features than those explicitly recited in the scope of each application. More precisely, as reflected in the scope of the patent application below, the inventor It is less than all of the features of the single embodiment disclosed above. Therefore, the scope of the patent application, which is in accordance with the specific embodiments, is hereby expressly incorporated in

Those skilled in the art will appreciate that the modules in the devices of the embodiments can be self-adjustingly altered and placed in one or more devices different than the embodiment. The modules or units or elements of the embodiments may be combined into a single module or unit or component, and further they may be divided into a plurality of sub-modules or sub-units or sub-elements. In addition to the fact that at least some of such features and/or processes or units are mutually exclusive, any combination of features disclosed in the specification, including the accompanying claims, abstract and drawings, and any methods so disclosed may be employed in any combination. Or combine all the processes or units of the device. Each feature disclosed in the specification (including the accompanying claims, the abstract, and the drawings) may be replaced by alternative features that provide the same, equivalent or similar purpose.

In addition, those skilled in the art will appreciate that, although some embodiments described herein include certain features that are included in other embodiments and not in other features, combinations of features of different embodiments are intended to be within the scope of the present invention. Different embodiments are formed and formed. For example, in the scope of the following claims, any one of the claimed embodiments can be used in any combination.

Individual component embodiments of the present invention may be implemented in hardware or as software modules running on one or more processors, or The combination is implemented. Those skilled in the art will appreciate that a microprocessor or digital signal processor (DSP) may be used in practice to implement some or all of the elements of the inventive name (e.g., means for determining the level of link within a website) in accordance with embodiments of the present invention. Some or all of the features. The invention can also be implemented as a device or device program (e.g., a computer program and a computer program product) for performing some or all of the methods described herein. Such a program implementing the present invention may be stored on a computer readable medium or may be in the form of one or more signals. Such signals may be downloaded from an internet website, provided on a carrier signal, or provided in any other form.

It is to be noted that the above-described embodiments are illustrative of the present invention and are not to be construed as limiting the scope of the invention, and those skilled in the art can devise alternative embodiments without departing from the scope of the appended claims. In the scope of the patent application, any reference symbols located between parentheses shall not be construed as limiting the scope of the patent application. The word "comprising" does not exclude the presence of elements or steps that are not listed in the claims. The word "a" or "an" The invention can be implemented by means of a hardware comprising several distinct elements and by means of a suitably programmed computer. In the scope of the patent application for a number of devices, several of these devices may be embodied by the same hardware item. The use of the words first, second, and third does not indicate any order. These words can be interpreted as names.

Claims (37)

A data recommendation processing interaction system, characterized in that the system comprises: an interaction device and a data processing device; the interaction device is configured to acquire the acquired material information of the developer and the determined status data corresponding to the state in which it is located. Sending to the data processing device and receiving the data recommended by the data processing device to the interactive device; the data processing device is configured to recommend the data to the interactive device according to the information information acquired by the interactive device and the state of the interactive device. The system of claim 1, wherein the interactive device acquires material information used by a developer; and transmits the material information to a data processing device, so that the data processing device extracts from the material information Basic information for data recommendation; information recommended by the receiving data processing device is recommended to the developer. The system of claim 1, wherein the interactive device determines a current state; and transmits the determined state data corresponding to the state to the data processing device, so that the data processing device is in accordance with the state The data determines the current state of the interactive device; and receives the recommended information sent by the data processing device corresponding to the current state of the interactive device. The system of claim 1, wherein the data processing device extracts a base resource for performing data recommendation The basic information is used to perform data matching in the data recommendation process; the corresponding preset recommendation logic is determined according to the state of the interaction device, and the preset recommendation logic uses at least one basic information in the basic information to perform Data recommendation; data recommendation to the interactive device based on the determined default recommendation logic and the basic information used. A processing method for data recommendation, the processing method being applied to a data processing device, wherein the processing method comprises: the data processing device extracting basic information for performing data recommendation, wherein the basic information is used in the data recommendation process Performing data matching; determining corresponding preset recommendation logic according to the state of the interaction device, wherein the preset recommendation logic uses at least one basic information in the basic information to perform data recommendation; according to the determined preset recommendation logic and its use Basic information to recommend information to interactive devices. According to the method of claim 5, the extracting basic information for performing data recommendation includes: extracting developer behavior history information for performing data recommendation, and relaying a data label in a predetermined recommended range and/or Or relationship data used to narrow the recommended range. The method of claim 6, wherein extracting developer behavior history information comprises: extracting a relay data extraction keyword of a table created by the developer, a relay data extraction keyword of the table that the developer depends on, and/or Or the developer at the preset time The search keywords within them together constitute developer behavior history information. The method of claim 7, wherein extracting the search keyword of the developer within the preset time comprises: obtaining a history of the search keyword of the developer within a preset time, from the history of the search keyword Obtaining valid search keywords after deleting invalid keywords in the record; the invalid keywords include: stop words and special characters; using a weighted algorithm to count the weights of valid search keywords; according to the rights of valid search keywords The value and the search time calculate a time weighted value of the valid search keyword; according to the calculated time weighted value, the first preset number of search keywords are extracted from the effective search keyword as the search key of the developer within the preset time word. The method of claim 7, wherein extracting the relay data extraction keyword of the table created by the developer comprises: acquiring a relay data label of the table created by the developer, and collecting the obtained relay data label. The weight value in the full amount of the relay data label; according to the weight of the relayed data label, the second preset number of relay data labels are extracted from the obtained relay data label as the developer creates The relay data extraction keyword for the table. The method of claim 7, wherein extracting the relay data extraction keyword of the table that the developer depends on includes: obtaining a relay data label of the table that the developer depends on, and collecting the obtained relay data label. The weight in the full amount of relay data labels; according to the weight of the statistical relay data label, the obtained relay The third preset number of relay data tags are extracted from the data tag as relay data extraction keywords of the table that the developer depends on. According to the method of claim 6, wherein extracting the relay data label in the preset recommendation range comprises: extracting a keyword as a relay data label in the table information of the data table; using a weighted algorithm statistical office Deriving a weight of a keyword as a relay data tag; extracting, according to the weight of the keyword as the relay data tag, a fourth preset number of keywords in each data table as a preset recommended range Relay data tag. The method of claim 11, wherein the weighting of the keyword as a relay data tag by using a weighting algorithm comprises: if the keyword used as a relay data tag is derived from the table information The table name or the table comment adds the weight of the keyword as the relay data tag to the preset value. According to the method of claim 6, wherein extracting the relationship data for narrowing the recommended range includes: selecting a developer having a preset hierarchical relationship among the developers according to the depth of the developer relationship to form a reduction The relationship data of the recommended range. The method of claim 6, wherein the recommending the data to the interactive device based on the determined preset recommendation logic and the basic information used includes: When the interactive device is in the current state without context, the developer behavior history information is matched with the relay data label in the preset recommendation range, and the extracted relationship data is used to narrow the search range, and the search scope is narrowed and the matching is successful. The information corresponding to the data label is recommended to the interactive device. The method of claim 6, wherein the recommending the data to the interactive device according to the determined preset recommendation logic and the basic information used thereof comprises: searching for the interactive device when the interactive device is in the state of the search keyword The keyword is matched with the relay data label in the preset recommendation range, and the extracted relationship data is used to narrow the search range, and the data corresponding to the successfully matched relay data label is narrowed down to the interactive device for recommendation. The method of claim 6, wherein the recommending the data to the interactive device according to the determined preset recommendation logic and the basic information used thereof comprises: browsing the interactive device when the interactive device is in the state of browsing the data table The label of the data table is matched with the relay data label in the preset recommended range, and the data corresponding to the successfully matched relay data label is recommended to the interactive device. An interactive method for data recommendation, the method being applied to an interactive device, wherein the method comprises: an interactive device acquiring information information used by a developer; and transmitting the data information to a data processing device for data processing The device extracts basic information for performing data recommendation from the material information; and receives data recommended by the data processing device to recommend to the developer. According to the method of claim 17, wherein the basic information for performing the data recommendation includes: developer behavior history information for recommending the data, a relay data label within the preset recommendation range, and/or Reduce the relationship data of the recommended range. The method of claim 18, wherein receiving the data recommended by the data processing device comprises: when the interactive device is in a current state without context, receiving the data processing device by using the developer behavior history information and the preset recommendation The relay data labels in the range are matched, and the data corresponding to the successfully matched relay data labels obtained by narrowing the search range are used. The method of claim 18, wherein the receiving the information recommended by the data processing device comprises: when the interactive device is in the state of searching for a keyword, the receiving data processing device searches for keywords and presets by the interactive device. The relay data labels in the recommended range are matched, and the data corresponding to the successfully matched relay data labels obtained by narrowing the search range are used. The method of claim 18, wherein the receiving the information recommended by the data processing device comprises: when the interactive device is in the state of browsing the data table, receiving the data processing device by using the tag of the data table browsed by the interactive device Default recommendation range The data corresponding to the successfully matched relay data label obtained after the matching of the relay data label is matched. An interactive method for data recommendation, the method being applied to an interactive device, wherein the method comprises: the interaction device determining a current state; and transmitting the determined state data corresponding to the state to the data processing device, So that the data processing device determines the current state of the interactive device according to the status data; and receives the recommended data sent by the data processing device corresponding to the current state of the interactive device. The method of claim 22, wherein the recommended information of the current state of the corresponding interactive device sent by the receiving data processing device comprises: corresponding to the data processing device when the interactive device is in the current state without context Recommended information for no context. The method of claim 22, wherein the recommended information of the current state of the corresponding interactive device sent by the receiving data processing device comprises: when the interactive device is in the state of the search keyword, receiving the corresponding information sent by the data processing device Search for the status of the search keyword. The method of claim 22, wherein the recommended information of the current state of the corresponding interactive device sent by the receiving data processing device comprises: receiving the data processing when the interactive device is in the state of browsing the data table The recommended information of the status of the corresponding browsing data table sent by the device. A processing device for data recommendation, characterized in that: the device comprises: an extracting unit, configured to extract basic information for performing data recommendation, the basic information is used for data matching in a data recommendation process; and a logic determining unit is configured to: Corresponding preset recommendation logic is determined according to a state of the interaction device, the preset recommendation logic uses at least one basic information in the basic information to perform data recommendation; and the processing unit is configured to: according to the determined preset recommendation logic and Use the basic information to recommend data to interactive devices. The apparatus according to claim 26, wherein the extracting unit comprises: a first extracting subunit for extracting developer behavior history information for performing material recommendation; and a second extracting subunit for extracting A relay data tag within a preset recommended range; and a third extraction sub-unit for extracting relationship data for narrowing the recommended range. The device of claim 27, wherein the first extraction subunit comprises: a first acquisition module, configured to acquire a history record of a search keyword of a developer within a preset time, from a search key An effective search keyword is obtained after the invalid keyword is removed from the history of the word; the invalid keyword includes: a stop word and a special character; a first statistic module, configured to use a weighted algorithm to calculate a weight of the effective search keyword; and a first calculating module, configured to calculate a time weighted value of the valid search keyword according to the weight corresponding to the effective search keyword and the search time The first extraction module is configured to extract, according to the calculated time weighting value, the first preset number of search keywords in the effective search keyword as the search keyword of the developer within the preset time. The device according to claim 27, wherein the first extraction subunit comprises: a second acquisition module, configured to acquire a relay data label of a table created by a developer; and a second statistical module, The second extraction module is configured to collect the weight of the relay data label in the full amount of the relay data label, and the second extraction module is configured to use the weight of the relayed data label in the obtained relay data label. A second preset number of relay data tags are extracted as relay data extraction keywords of the table created by the developer. The device of claim 27, wherein the first extraction subunit comprises: a third acquisition module, configured to acquire a relay data label of a table that the developer depends on; and a third statistical module, The weight of the relay data tag obtained in the statistics of the full amount of the relay data tag; the third extraction module is configured to use the right of the relayed data tag according to the statistics And a value, in the obtained relay data label, extracting a third preset number of relay data labels as a relay data extraction keyword of a table that the developer depends on. The device of claim 27, wherein the second extraction subunit comprises: a fourth acquisition module, configured to extract a keyword as a relay data label in the table information of the data table; a statistical module, configured to use a weighted algorithm to count the weight of the keyword as a relay data tag; and a fourth extraction module, configured to use, according to the weight of the keyword as the relay data tag, The data of the fourth preset number of relay data labels is extracted from the data table as the relay data label in the preset recommended range. The device according to claim 27, wherein the third extraction subunit is configured to select a developer having a preset hierarchical relationship among developers to form a recommendation range according to a developer relationship depth. Relationship information. An information recommendation interactive device, wherein the device comprises: an obtaining unit, configured to acquire material information used by a developer; and a first sending unit, configured to send the data information to the data processing device for data processing The device extracts basic information for performing data recommendation from the material information, and the first receiving unit is configured to receive the recommended data of the data processing device and make recommendations to the developer. An information recommendation interactive device, the device comprising: a state determining unit, configured to determine a current state of the interaction device; and a second sending unit, configured to send the determined state data corresponding to the state And the data processing device is configured to determine, according to the status data, a state in which the interactive device is currently located; and the second receiving unit is configured to receive the recommended data of the current state of the corresponding interactive device sent by the data processing device. The device according to claim 34, wherein the second receiving unit is configured to receive the recommended information of the corresponding non-context state sent by the data processing device when the interactive device is in the current state without context. The device according to claim 34, wherein the second receiving unit is configured to receive the recommended information of the status of the corresponding search keyword sent by the data processing device when the interactive device is in the state of the search keyword. The device according to claim 34, wherein the second receiving unit is configured to receive the recommended information of the status of the corresponding browsing data table sent by the data processing device when the interactive device is in the state of browsing the data table.