Longest Increasing Subsequence Sorting for Mobile App Store Workload
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Mobile app stores face significant system workload and expense challenges when updating frequently changing item rankings, as existing methods require updating all items, leading to excessive load and unsuitable for large content providers.
Innovation Solution
The method involves selecting excluded items using the longest increasing subsequence from an item list, updating only the remaining items, and employing multiple sorting indexes to minimize system workload, thereby reducing the number of updates needed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all items are updated frequently to maintain accurate exposure rankings, then the ranking accuracy is improved, but the system workload increases significantly
Solution Approach 1:
The patent extracts and identifies a subset of items that actually require updates by applying the longest increasing subsequence algorithm to update order sequences. Instead of updating all items, only items not included in the LIS are updated, thereby extracting the essential update operations from the redundant ones and reducing system workload while maintaining ranking accuracy.
Solution Approach 2:
The patent changes the parameter of update frequency by using multiple sorting indexes (primary index and auxiliary indexes) to determine which items need updates. By analyzing changes in update orders across different indexes and applying LIS algorithm, the system dynamically adjusts update parameters to minimize workload while preserving ranking precision.
2Productivity
If the number of mobile items is reduced to decrease system load, then the system workload is reduced, but the service capability deteriorates
Solution Approach 1:
The patent applies partial action by updating only the necessary subset of items identified through LIS algorithm rather than all items. This partial update approach maintains sufficient service capability for large item sets while reducing system workload, avoiding the need to reduce the total number of mobile items available in the store.
3Measurement precision
If multiple sorting indexes are used to improve item sorting accuracy, then the sorting precision is improved, but the update complexity increases
Solution Approach 1:
The patent segments the sorting process into multiple independent sorting indexes (primary index and auxiliary indexes). Each index handles specific sorting dimensions, and the LIS algorithm is applied separately to each index's update order sequence. This segmentation improves sorting precision by considering multiple dimensions while managing complexity through modular processing of each index independently.
Data Source
AI summary
An apparatus and method for sorting items using a longest increasing subsequence are disclosed. Item sorting may be performed by selecting excluded items, which correspond to a longest increasing subsequence, from among items in an item list, selecting update items by excluding the excluded items from the items, and performing update for the update items. It is possible to more efficiently use a system by selecting items to be updated from among various items in an item list and updating them to reduce the system workload for updating the items.