Split Vacation Deal Server Batching Queries
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional electronic booking systems face challenges in finding near-optimal hotel booking splits efficiently while adhering to look-to-book policies and ensuring responsive customer queries, especially when dealing with multiple Global Distribution Systems (GDS) and varying pricing strategies.
Innovation Solution
The system employs a combination of technologies such as Bloom filters, Distributed Caches, Machine Learning Classification algorithms, and Scalable infrastructure to identify near-optimal hotel booking splits by decomposing queries into smaller time periods, classifying requests, and optimizing price quote requests to comply with look-to-book ratios and reduce query latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the system queries all possible hotel booking splits to find near-optimal deals, then the quality of booking recommendations improves, but the number of price quote requests increases and query response time deteriorates
Solution Approach 1:
The patent segments the set of all possible booking splits into multiple batches. Instead of querying all splits simultaneously, the system divides them into sequential batches and queries them in stages. This segmentation allows the system to find good enough splits within time constraints while avoiding the need to query every possible split, thus resolving the contradiction between optimization quality and response time.
Solution Approach 2:
The patent implements preliminary actions by sorting and prioritizing booking splits before querying. The system pre-processes the split list to identify and query the most promising splits first based on certain criteria. This preliminary ordering ensures that the system queries the most likely optimal splits early in the process, achieving good optimization quality within limited time while reducing the total number of queries needed.
2Measurement precision
If the system increases the number of price quote requests to find better booking splits, then the quality of deals improves, but the look-to-book ratio policy compliance worsens
Solution Approach 1:
The patent applies partial action by querying only a subset of all possible booking splits rather than all of them. The system determines that querying a carefully selected portion of splits (based on sorting and batching) is sufficient to find near-optimal deals without excessively increasing the look-to-book ratio. This partial querying approach maintains policy compliance while still achieving good optimization quality.
3Productivity
If the system processes multiple GDS splits simultaneously in parallel, then the productivity improves, but the complexity of managing queries and responses increases
Solution Approach 1:
The patent segments parallel query processing into sequential batches. Instead of managing all parallel queries simultaneously which increases complexity, the system divides them into batches processed in sequence. This segmentation reduces the complexity of query management at any given moment while maintaining reasonable productivity through efficient batch processing.
4Productivity
If the system sends all queries in one batch, then the productivity improves, but the ability to respond responsively to customer queries worsens
Solution Approach 1:
The patent segments the query batch into smaller sub-batches that are processed and returned in stages. This allows the system to maintain productivity by processing multiple queries while improving responsiveness by returning partial results to customers earlier rather than waiting for all queries to complete. The segmented approach balances both efficiency and responsiveness.
Solution Approach 2:
The patent implements periodic action by processing and returning query results in periodic batches rather than all at once. The system processes queries in time intervals, returning results periodically to customers. This periodic approach maintains overall productivity while improving perceived responsiveness by providing interim results during the processing period.
Data Source
AI summary
A split vacation deal server sending queries in plural batches wherein at least one batch is sent, via at least one API, to at least one data supplier server having at least one policy limiting at least one current aspect of the at least one data supplier server's interaction with the split vacation deal server.