Content Processing With Weighted Keywords for Search Result Prioritization
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Solution Overview
Problem
Existing content search methods struggle to efficiently prioritize relevant documents while minimizing noise documents, leading to increased operator workload in reviewing large sets of search results.
Innovation Solution
A method for determining the degree of priority of presentation of contents by identifying positive and negative keywords, assigning weights based on frequency of appearance, and using optimization criteria to order and present contents efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional content search methods are used to retrieve all relevant documents, then the completeness of search results is improved, but the operator workload increases due to the large volume of documents to review
Solution Approach 1:
The patent segments the large set of search results into prioritized subsets based on relevance scoring. The content processing apparatus divides documents into high-priority, medium-priority, and low-priority groups, allowing operators to focus on the most relevant content first while still ensuring comprehensive coverage across all segments.
Solution Approach 2:
The patent performs preliminary processing of search results by automatically calculating relevance scores and generating priority rankings before operator review. The content processing apparatus pre-evaluates all documents using keyword matching, frequency analysis, and weighting algorithms, so that when operators receive the results, they are already organized in optimal review order.
2Loss of information
If conventional search methods retrieve all documents without prioritization, then no relevant content is missed, but the efficiency of content review deteriorates due to uniform presentation of all documents
Solution Approach 1:
The patent implements dynamic prioritization where the presentation order of documents changes based on calculated relevance scores. The content processing apparatus continuously adjusts the priority ranking of documents based on keyword frequency, document length, and other factors, creating a dynamic rather than static presentation order that adapts to the specific search query and result set.
Solution Approach 2:
The patent changes multiple parameters to determine document priority, including keyword frequency, document length, keyword weightings, and relevance thresholds. The content processing apparatus modifies these parameters based on the specific search context, allowing flexible adjustment of prioritization criteria to optimize both completeness and efficiency for different search scenarios.
3Ease of operation
If all documents are presented in uniform order, then the simplicity of presentation is maintained, but the ability to highlight relevant content deteriorates
Solution Approach 1:
The patent applies different presentation qualities to different documents based on their relevance scores. High-priority documents receive prominent placement and enhanced visual indicators, while lower-priority documents are presented with reduced emphasis. The content processing apparatus creates local variations in presentation quality (positioning, formatting, highlighting) that correspond to the relevance level of each document.
Solution Approach 2:
The patent adds a priority dimension to the traditional binary presentation of search results. Instead of simply showing or hiding documents, the system creates a multi-dimensional presentation where documents are positioned along a priority axis, allowing operators to quickly assess relevance through the added dimensional information without losing the basic simplicity of list-based presentation.
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 a first set including contents given positive evaluations and a second set including contents given negative evaluations from among the plurality of contents; extracting a first word set included in the first set and a second word set included in the second set; identifying a plurality of keywords including a plurality of positive keywords related to the first set and a plurality of negative keywords related to the second set according to a first evaluation criterion, the plurality of positive keywords being identified based on the first word set, the plurality of negative keywords being identified based on the second word set; giving weights to the plurality of keywords according to a second evaluation criterion so as to give a weight of zero or more to each of the plurality of positive keywords and give a weight of zero or less to each of the plurality of negative 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 given 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.