Hot Topic Mining via Frequency-Based Word Selection

Solution Overview

Problem

Conventional methods for collecting hot topics are resource-intensive, inaccurate, and lack timeliness, relying on manual human effort to identify and categorize trending topics from community data.

Innovation Solution

A method and apparatus that automatically acquire hot topics by selecting words from community data based on frequency and relevance, forming a word set, and then determining topics as hot topics using a computing device with modules for data acquisition, selection, and processing, which includes periodic data collection and semantic analysis.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual collection of hot topics is used, then human resources can be allocated flexibly, but the accuracy and timeliness of hot topic mining deteriorates

Engineering Contradiction:

Improveaccuracy of hot topic miningVSAvoidtimeliness of hot topic mining

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system performs self-service by automatically collecting community data, extracting keywords through text mining, and identifying hot topics without human intervention. The automated workflow includes data acquisition from multiple sources, keyword extraction using frequency analysis, and hot topic determination based on keyword co-occurrence, enabling the system to serve itself and eliminate manual labor while improving accuracy and timeliness.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces the mechanical manual system with an automated computational system. Text mining algorithms, frequency analysis, and keyword extraction techniques substitute human manual collection methods. The system uses computer-implemented processes to analyze community data, identify patterns, and determine hot topics, replacing the mechanical human effort with automated electronic processing.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Productivity

If manual collection of hot topics is used, then resource consumption can be controlled, but productivity and accuracy of hot topic identification deteriorates

Engineering Contradiction:

Improvehot topic mining efficiencyVSAvoidhuman resources consumed

Core Design Contradiction:

ProductivityVSQuantity of substance

Solution Approach 1:

The system performs self-service by automatically collecting community data, extracting keywords through text mining, and identifying hot topics without human intervention. The automated workflow includes data acquisition from multiple sources, keyword extraction using frequency analysis, and hot topic determination based on keyword co-occurrence, enabling the system to serve itself and eliminate manual labor while improving accuracy and timeliness.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces the mechanical manual system with an automated computational system. Text mining algorithms, frequency analysis, and keyword extraction techniques substitute human manual collection methods. The system uses computer-implemented processes to analyze community data, identify patterns, and determine hot topics, replacing the mechanical human effort with automated electronic processing.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Measurement precision

If automated text mining is implemented, then accuracy and timeliness of hot topic acquisition is improved, but system complexity increases

Engineering Contradiction:

Improveaccuracy of hot topic acquisitionVSAvoidsystem complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent segments the hot topic acquisition process into distinct modular stages: data acquisition from multiple sources, text preprocessing and cleaning, keyword extraction using frequency analysis, hot topic determination based on keyword co-occurrence, and result output. Each stage is implemented as a separate computational module that can be independently optimized and maintained, reducing overall system complexity while maintaining high accuracy.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces intermediary components such as keyword extraction modules and frequency analysis mechanisms that mediate between raw community data and final hot topic identification. These intermediaries process and transform data in standardized ways, simplifying the overall system architecture by breaking down complex transformations into manageable intermediate steps with clear interfaces.

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS9477747B2Method and apparatus for acquiring hot topics

Publication Date: 2016.10.25 TENCENT TECHNOLOGY (SHENZHEN) CO LTD

AI summary

A method includes: a first word set is acquired from community data within a period; words are selected from the first word set according to a frequency that each word of the first word set appears in the community data during a first group of days, the selected words are determined as hot words and form a second word set, wherein the first group of days are a plurality of days backward from a designated day; and topics are selected from a community topic set according to the second word set, and are determined as hot topics.