Domain Name Evaluation via Micro-Dictionary Word Splitting
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Solution Overview
Problem
Current methods for evaluating domain names lack efficiency in providing reliable scores and keyword derivations, making it difficult to assess domain name value and availability effectively.
Innovation Solution
A system and method for word splitting and reliability score calculation that involves creating a micro-dictionary from a character string input, identifying the largest contiguous words, and calculating reliability scores based on dictionary matches and uniqueness, allowing for automated appraisal and display of domain name values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated domain name evaluation methods are used, then productivity is improved, but measurement precision deteriorates
Solution Approach 1:
The domain name evaluation process is segmented into multiple independent components: micro-dictionary creation from character strings, largest contiguous word identification, dictionary database matching, uniqueness scoring, and reliability score calculation. Each component processes specific aspects separately and contributes to the final evaluation, enabling automated processing while maintaining precision through specialized sub-functions.
Solution Approach 2:
A micro-dictionary is created as an intermediary structure between the input character string and the final evaluation. This micro-dictionary contains extracted words and their properties, serving as a bridge that enables systematic analysis. Additionally, dictionary database matches act as intermediaries to verify word validity and calculate reliability scores objectively.
2Reliability
If comprehensive keyword derivation is performed, then reliability is improved, but device complexity increases
Solution Approach 1:
The complexity is segmented by dividing the evaluation into distinct modules: character string processing, micro-dictionary generation, word extraction, dictionary matching, uniqueness calculation, and reliability scoring. Each module handles a specific task with clear inputs and outputs, making the overall complex system manageable and maintainable while achieving comprehensive evaluation.
Solution Approach 2:
The system employs universal data structures and algorithms that can handle various types of domain names and character strings. The micro-dictionary approach and largest contiguous word identification method are general-purpose techniques that work across different evaluation scenarios, reducing the need for specialized complex logic for each case.
3Measurement precision
If multiple reliability variables are evaluated, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The micro-dictionary is created in advance from the character string, extracting and storing all identifiable words with their properties before the main evaluation process. This preliminary action prepares the data structure so that subsequent reliability calculations can proceed efficiently without re-processing the same information multiple times.
Solution Approach 2:
The evaluation process maintains continuity by using the micro-dictionary and extracted words as the foundation for all subsequent calculations. Each reliability variable (dictionary matches, uniqueness, keyword derivation) builds upon the previous results without redundant processing, ensuring that the continuous flow of calculations remains efficient while comprehensively evaluating multiple factors.
Data Source
AI summary
Systems and methods of the present invention provide for the word splitting and reliability score for an entered character string. A list of keywords may be extracted from the character string entered into a user interface on a client. These keywords may be compared to potential matches in a dictionary database and a reliability score for word splits and keywords strings may be compiled and displayed to the user. The client may also display the reliability score using a plurality of logical groupings within a reliability score process.