Method and electronic device for obtaining hierarchical data structure and processing log entries

An electronic device, comprising:

• a processor;
• and
• a memory coupled to the processor and having instructions stored therein, wherein the instructions, when executed by the processor, cause the electronic device to execute actions, and the actions comprise:
• receiving a request for processing a target log entry;
• obtaining a hierarchical data structure at the electronic device, wherein obtaining comprises:
• obtaining corresponding characteristic information comprised in each log entry of a set of log entries;
• determining multiple log entry patterns based on the corresponding characteristic information, wherein pattern characteristic information of each log entry pattern corresponds to the characteristic information of a subset of log entries in the set of log entries;
• and
• storing the set of log entries according to the hierarchical data structure so that each log entry is associated with at least one of multiple nodes of the hierarchical data structure, wherein the multiple nodes respectively correspond to the multiple log entry patterns, and are hierarchically organized based on respective corresponding log entry patterns, and wherein the request comprises a first request for analyzing a first node of the multiple nodes;
• and
• processing the target log entry based on the hierarchical data structure, wherein processing comprises:
• determining a first subset of target log entries associated with the first node;
• determining, based on the first subset of target log entries and using a natural language processing model, a first pattern associated with the first subset of target log entries for responding to the first request by:
• determining a first characteristic representation of the first subset of target log entries;
• and
• determining the first pattern by using the first characteristic representation as an input to a classifier module;
• wherein the first pattern comprises key information in the first subset of target log entries, and wherein the natural language processing model comprises a pre-trained neural network;
• and
• removing, based on the first pattern, redundant information recorded in the first subset of target log entries.

A non-transitory computer readable medium comprising computer readable program code, which when executed by a computer processor, enables the computer processor to:

• receive a request for processing a target log entry;
• and
• obtain a hierarchical data structure by:
• obtaining corresponding characteristic information comprised in each log entry of a set of log entries;
• determining multiple log entry patterns based on the corresponding characteristic information, wherein pattern characteristic information of each log entry pattern corresponds to the characteristic information of a subset of log entries in the set of log entries;
• and
• storing the set of log entries according to the hierarchical data structure so that each log entry is associated with at least one of multiple nodes of the hierarchical data structure, wherein the multiple nodes respectively correspond to the multiple log entry patterns, and are hierarchically organized based on respective corresponding log entry patterns, and wherein the request comprises a first request for analyzing a first node of the multiple nodes;
• and
• processing the target log entry based on the hierarchical data structure, wherein processing comprises:
• determining a first subset of target log entries associated with the first node;
• determining, based on the first subset of target log entries and using a natural language processing model, a first pattern associated with the first subset of target log entries for responding to the first request by:
• combining target log entries in the first subset of target log entries to obtain a first combined log text;
• determining a first characteristic representation for the first combined log text with the natural language processing model;
• and
• determining the first pattern by using the first characteristic representation as an input to a classifier module;
• wherein the first pattern comprises key information in the first subset of target log entries, and wherein the natural language processing model comprises a pre-trained neural network;
• and
• removing, based on the first pattern, redundant information recorded in the first subset of target log entries.