The present disclosure discloses a data mining method, a data mining apparatus, an electronic device and a storage medium, relates to the technical field of the Internet, and in particular to the Internet big data processing technology. The method includes: acquiring a current article to be mined; obtaining information values required for each data identification strategy of multiple data identification strategies from the current article, and each data identification strategy is used for identifying a preset type of data; identifying a data type of the current article according to the information values required for each data identification strategy to obtain a data type identification result; and determining whether the current article belongs to any preset type of data according to the data type identification result.

The present disclosure discloses a data mining method, a data mining apparatus, an electronic device and a storage medium, relates to the technical field of the Internet, and in particular to the Internet big data processing technology. The method includes: acquiring a current article to be mined; obtaining information values required for each data identification strategy of multiple data identification strategies from the current article, and each data identification strategy is used for identifying a preset type of data; identifying a data type of the current article according to the information values required for each data identification strategy to obtain a data type identification result; and determining whether the current article belongs to any preset type of data according to the data type identification result.

A data acquisition apparatus (200) comprises a processing resource operably coupled to an input unit (204) and an output unit (206). The processing resource (202) is arranged to provide an execution environment for supporting a user interface. An enquiry module (268) is provided and supported by the execution environment. The apparatus (200) also comprises a communications unit (166, 168) operably coupled to the processing resource for supporting communications over a communications network. The enquiry module (268) is arranged to generate (410) a search query relating to a point of interest and receive search results in response thereto via the communications unit (166, 168), the enquiry module (268) also being arranged to use the search results to derive data associated with the point of interest.

A data acquisition apparatus (200) comprises a processing resource operably coupled to an input unit (204) and an output unit (206). The processing resource (202) is arranged to provide an execution environment for supporting a user interface. An enquiry module (268) is provided and supported by the execution environment. The apparatus (200) also comprises a communications unit (166, 168) operably coupled to the processing resource for supporting communications over a communications network. The enquiry module (268) is arranged to generate (410) a search query relating to a point of interest and receive search results in response thereto via the communications unit (166, 168), the enquiry module (268) also being arranged to use the search results to derive data associated with the point of interest.

A system for providing a search service application is disclosed and includes an application builder component that provides a search model for a first object of a plurality of objects. The search model is based at least on an end-user input field corresponding to a first attribute of the first object and a search result output field corresponding to a second attribute of the first object. The search model is also associated with a backend data store that supports a storage structure that stores information relating to the first object. The system also includes a deployment engine that automatically configures a search engine system associated with the backend data store to place a portion of indexed data into a first partition and to place another portion of indexed data into at least another partition based on the search model.

A system for providing a search service application is disclosed and includes an application builder component that provides a search model for a first object of a plurality of objects. The search model is based at least on an end-user input field corresponding to a first attribute of the first object and a search result output field corresponding to a second attribute of the first object. The search model is also associated with a backend data store that supports a storage structure that stores information relating to the first object. The system also includes a deployment engine that automatically configures a search engine system associated with the backend data store to place a portion of indexed data into a first partition and to place another portion of indexed data into at least another partition based on the search model.

The disclosure discloses a method for analyzing educational big data on the basis of maps. The method includes acquiring educational resource data and storing the educational resource data into databases according to certain data structures; constructing theme map layers for each analysis theme, classifying and indexing data according to the analysis themes, and superimposing the theme map layers onto base maps to form data maps; analyzing data of the theme map layers according to the analysis themes and acquiring theme analysis results; extracting the data of the multiple theme map layers in target regions, fusing the data and acquiring region analysis results; acquiring learning preference of users; combining the learning preference of the users according to content of user requests and searching the region analysis results in response to the user requests. The disclosure further discloses a system for analyzing the educational big data on the basis of the maps.

The disclosure discloses a method for analyzing educational big data on the basis of maps. The method includes acquiring educational resource data and storing the educational resource data into databases according to certain data structures; constructing theme map layers for each analysis theme, classifying and indexing data according to the analysis themes, and superimposing the theme map layers onto base maps to form data maps; analyzing data of the theme map layers according to the analysis themes and acquiring theme analysis results; extracting the data of the multiple theme map layers in target regions, fusing the data and acquiring region analysis results; acquiring learning preference of users; combining the learning preference of the users according to content of user requests and searching the region analysis results in response to the user requests. The disclosure further discloses a system for analyzing the educational big data on the basis of the maps.

In an illustrative embodiment, systems and methods for cyber vulnerability assessment include obtaining assessment data including information pertaining to domains of cyber security vulnerability of an enterprise and, for each security domain, a respective domain-level vulnerability score, identifying risk(s) relevant to the enterprise based on domain-level vulnerability score(s), identifying recommended products or services for mitigating each of the risks, and preparing a graphical user interface for selecting a portion of the recommended products or services. A user may select one or more products or services through the user interface for purchase and/or deployment planning. The domain-level vulnerability scores may be compared to peer vulnerabilities scores, target vulnerability scores, or prospective vulnerability scores based upon application of certain recommended products or services.

In an illustrative embodiment, systems and methods for cyber vulnerability assessment include obtaining assessment data including information pertaining to domains of cyber security vulnerability of an enterprise and, for each security domain, a respective domain-level vulnerability score, identifying risk(s) relevant to the enterprise based on domain-level vulnerability score(s), identifying recommended products or services for mitigating each of the risks, and preparing a graphical user interface for selecting a portion of the recommended products or services. A user may select one or more products or services through the user interface for purchase and/or deployment planning. The domain-level vulnerability scores may be compared to peer vulnerabilities scores, target vulnerability scores, or prospective vulnerability scores based upon application of certain recommended products or services.