Content Prioritization via Weighted Keyword Frequency
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Solution Overview
Problem
Current content processing methods for patent document searches are inefficient, often resulting in irrelevant documents being included (noise documents) or important documents being omitted, due to inadequate filtering, which increases operator workload and reduces search accuracy.
Innovation Solution
A content processing method that assigns weights to keywords related and unrelated to the research target, allowing for a prioritization of content presentation based on the frequency of keyword appearance and operator evaluation, enabling operators to efficiently browse and review relevant documents by adjusting the presentation order and displaying priorities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional content processing methods are used for patent document searches, then search coverage is maintained, but search accuracy deteriorates due to inclusion of noise documents and omission of important documents
Solution Approach 1:
The system automatically calculates priority scores for documents based on keyword frequency and operator weights without requiring manual review of all documents. The calculation process is self-executing, taking operator-defined weights and automatically ranking documents by priority, thereby improving search accuracy while reducing the quantity of documents requiring operator attention.
2Ease of operation
If all search results are presented to operators without prioritization, then completeness is maintained, but operator workload increases
Solution Approach 1:
The system performs preliminary prioritization of documents before presentation to operators by calculating priority scores based on keyword frequency and operator-defined weights. This preliminary sorting ensures that important documents are presented first, reducing operator workload while preventing important document omission through structured prioritization.
3Reliability
If keyword frequency alone is used for document ranking, then simplicity is maintained, but relevance deteriorates due to lack of operator expertise integration
Solution Approach 1:
The system enhances simple keyword frequency counting by introducing operator-defined weights as an additional parameter. Each keyword is assigned a weight reflecting its importance to the search topic, and the priority score is calculated as the sum of products of keyword frequencies and their corresponding weights. This parameter enhancement improves document relevance while maintaining relatively simple processing through straightforward mathematical calculation.
Data Source
AI summary
Provided is a content processing method for determining a degree of priority of presentation of each of a plurality of contents, comprising: identifying the plurality of contents; receiving keyword information including a plurality of keywords designated by an operator and a weight for each of the plurality of keywords; deriving a total for each of the plurality of contents by summing, over the plurality of keywords, a product of a frequency of appearance of each of the plurality of keywords and the weight for the each of the plurality of keywords to obtain the total for each of the plurality of contents; and determining the degree of priority of presentation of each of the plurality of contents based on the total for the each of the plurality of contents.