Search Server Friend Webpage Entry Scoring
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Solution Overview
Problem
Existing information search methods do not effectively incorporate friend-uploaded webpage data into search results, failing to fully meet user search requirements by prioritizing friend-provided content.
Innovation Solution
A method and server system that store page information from network services in a user page database, allowing for the calculation and integration of friend webpage entries with common webpage entries based on keyword searches, sorting them by page scores to prioritize friend-provided content in search results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If friend webpage entries are integrated into search results, then user search requirements are better met, but search system complexity increases
Solution Approach 1:
The search system is segmented into multiple independent modules: a friend relationship module that manages user connections, a webpage crawling module that collects friend's webpages, a scoring module that calculates relevance scores, and a sorting module that integrates results. This segmentation allows each module to handle specific tasks independently, reducing overall system complexity while improving adaptability.
Solution Approach 2:
The system performs preliminary actions by pre-establishing friend relationships and pre-crawling webpages from friends' accounts before search queries are submitted. Friend webpage data is collected and stored in advance in a dedicated database, so when a search is performed, the system only needs to retrieve and score pre-collected data rather than crawling in real-time, simplifying the search execution process.
2Adaptability or versatility
If friend webpage data is prioritized in search results, then user satisfaction improves, but information loss increases
Solution Approach 1:
The system uses parameter changes by introducing a dynamic scoring mechanism that assigns different weights to different webpage sources. Friend webpage entries receive elevated scores based on a scoring formula that considers friendship strength and webpage relevance, while non-friend entries are scored normally. This parameter-based approach ensures friend content is prioritized without completely excluding other content, maintaining information completeness while improving user satisfaction.
Solution Approach 2:
The scoring mechanism acts as an intermediary between friend webpage priority and search result completeness. Instead of directly prioritizing friend content or using binary inclusion/exclusion, the system introduces a continuous scoring spectrum where friend webpages receive higher scores but all webpages are still considered. This intermediary scoring system balances the competing requirements of user satisfaction and information completeness.
Data Source
AI summary
A method, information processing apparatus, and a non-transitory computer-readable medium are provided. A search request including a keyword is received from a terminal of a user. A search is performed for a plurality of common webpage entries according to the keyword. A search is performed for a plurality of friend webpage entries of friends according to the keyword. Page scores for the plurality of common webpage entries and the plurality of friend webpage entries are determined based on the keyword. The page scores of only the plurality of friend webpage entries are weighted according to a first weighting factor. A combined list of webpage entries is generated based on the page scores for the plurality of common webpage entries and the weighted page scores for the plurality of friend webpage entries. The combined list includes a first subset of the plurality of common webpage entries and a second subset of the plurality of friend webpage entries. The generated combined list of webpage entries is sent to the terminal.