Tiered Search Index Fields for Group Communication Platforms
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Solution Overview
Problem
Existing data search index management systems in group-based communication platforms are inefficient, leading to slow response times and excessive network resource usage due to exhaustive searches in large databases, as they generate non-tiered search index fields for each data object, rather than utilizing tiered search index fields based on retrieval probability.
Innovation Solution
Implementing tiered search index fields that divide group-based communication data objects into high and low retrieval probability corpora, allowing for parallel querying and selective data retrieval based on retrieval scores, thereby reducing the volume of data searched and conserving network resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If exhaustive search is performed on non-tiered search index fields for each group-based communication data object, then complete search results are obtained, but response time becomes extremely slow and network resources are exhausted
Solution Approach 1:
The search index fields are segmented into multiple tiers based on retrieval probability. High retrieval probability search index fields contain data objects likely to be searched, while low retrieval probability search index fields contain less likely candidates. This segmentation allows the system to prioritize searching high-probability fields first, significantly reducing response time while maintaining result completeness by falling back to low-probability fields if needed.
2Reliability
If exhaustive search is performed on all group-based communication data objects in the database, then all matching data objects are retrieved, but network resources are exhausted
Solution Approach 1:
The database is segmented into high retrieval probability corpus and low retrieval probability corpus based on retrieval scores. The system first searches the high-probability corpus which contains a small subset of data objects most likely to match the search query. This dramatically reduces network resource usage compared to searching the entire database, while maintaining retrieval completeness by subsequently searching the low-probability corpus if the threshold is not met.
3Productivity
If tiered search index fields are used to divide data objects into high and low retrieval probability corpora, then response time is shortened and network resources are reduced, but search system complexity increases
Solution Approach 1:
The system performs preliminary action by pre-calculating retrieval scores for each group-based communication data object and organizing them into tiered search index fields before search queries are executed. High retrieval probability search index fields and low retrieval probability search index fields are pre-populated based on these scores. This preliminary organization enables fast search execution without complex real-time calculations, improving productivity while managing complexity through advance preparation.
Data Source
AI summary
Methods, apparatus and computer program product for generating tiered search index fields based on a divided group-based communication data corpus in a group-based communication platform are described herein. In some embodiments, the system provides for receiving a group-based communication data corpus, generating a retrieval score, and assigning each group-based communication data object associated with a retrieval score. Each group-based communication data object may meet or exceed a retrieval score threshold of a high retrieval probability corpus. Each group-based communication data object associated with a retrieval score below the retrieval score threshold may be assigned to a low retrieval probability corpus. High and a low retrieval probability search index fields may be generated and associated with the high and low retrieval probability corpus.