Keyword Aggregation System for Automated Search Query Generation
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Solution Overview
Problem
Current information search systems require manual input of keywords and phrases by users, which can lead to irrelevant results and waste time, especially for untrained users like students searching for academia-related documents.
Innovation Solution
A system that automatically extracts keywords and phrases from text sources such as course descriptions and assignment documents, and submits them to search engines for relevant results, allowing for real-time or batch processing, and displaying results directly to the user.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual keyword input is used for information search, then users can control the search process, but it requires significant user time and effort, especially for untrained users
Solution Approach 1:
The system automatically extracts keywords from course descriptions and assignment documents without requiring manual user input. The keyword aggregation function parses text sources and generates search queries autonomously, allowing the system to serve itself rather than requiring continuous user intervention for keyword generation.
Solution Approach 2:
The system pre-extracts and aggregates keywords from text sources before the actual search is needed. By preparing keyword lists in advance from course descriptions and assignments, the system eliminates the need for users to manually create keywords at the moment of searching, thus saving time and effort.
2Reliability
If users manually enter keywords for search, then they can specify search criteria, but they often enter incorrect keywords leading to irrelevant results
Solution Approach 1:
The keyword aggregation function serves as an intermediary between the text sources (course descriptions, assignments) and the search engine. It automatically parses and extracts relevant keywords from these sources, acting as a mediator that translates user needs into accurate search queries without requiring users to manually select or enter keywords.
Solution Approach 2:
The system replaces the manual mechanical process of keyword selection and entry with an automated computational process. The keyword aggregation function uses text parsing and pattern recognition algorithms to automatically generate search keywords, substituting human cognitive effort with automated information processing.
3Productivity
If automated keyword extraction is implemented, then search efficiency improves, but system complexity increases
Solution Approach 1:
The system is divided into distinct functional modules: text source access, keyword aggregation function, and search submission mechanism. This segmentation allows each component to perform its specific task independently, making the overall automated system manageable and maintainable despite its complexity.
Solution Approach 2:
The keyword aggregation function serves multiple purposes: it extracts keywords from various text sources (course descriptions, assignments, documents), generates search queries, and submits them to search engines. This multi-functionality reduces the need for separate specialized components, thereby managing system complexity while maintaining high productivity.
Data Source
AI summary
A system for creating keywords or phrases to be used for mining online information has a text source accessible by the system, a keyword aggregation function, and a mechanism for configuring the system. The system extracts keywords and phrases from the text source according to the configuration, for submission to a search facility.