Persistent Cluster ID Assignment for Search Result Organization
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Solution Overview
Problem
Existing search engine clustering technologies only maintain clusters for a short period, typically when documents are 'fresh', failing to provide long-term organization and retrieval of similar content events across different timelines.
Innovation Solution
Assigning persistent identification numbers to clusters and subdividing them by publication date, allowing for the continued clustering and separation of similar content events beyond their initial 'fresh' lifespan, enabling the delivery of clustered search results for recent and non-recent events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Duration of action of stationary object
If clusters are maintained only during the 'fresh' lifespan of documents, then storage and processing resources are conserved, but long-term organization and retrieval of similar content events across different timelines is lost
Solution Approach 1:
The patent segments the cluster maintenance function by creating separate data structures: a temporary cluster store for fresh documents and a persistent cluster store for long-term retention. This segmentation allows the system to maintain clusters indefinitely without overwhelming temporary memory resources, resolving the contradiction between extended duration and information loss.
Solution Approach 2:
The patent performs preliminary action by assigning persistent cluster identifiers and storing cluster metadata in advance, before the fresh document lifespan expires. This preliminary organization enables seamless transition from temporary to long-term storage, ensuring continuous accessibility without information loss.
2Ease of operation
If all similar documents are clustered together regardless of time, then comprehensive organization is achieved, but separation of similar events across different timelines becomes difficult
Solution Approach 1:
The patent segments clusters by introducing a temporal dimension through date-based subdivision. Each main cluster is divided into sub-clusters organized by publication date or time period. This segmentation maintains comprehensive organization while preserving temporal context, allowing users to navigate both broad categories and specific time periods.
Solution Approach 2:
The patent adds a temporal dimension to the clustering structure by organizing documents not only by content similarity but also by publication date. This multi-dimensional organization enables simultaneous achievement of comprehensive grouping and temporal separation, resolving the contradiction between ease of operation and loss of temporal information.
Data Source
AI summary
Methods, systems, and media are provided for delivering clustered search results for recent and non-recent events by maintaining the identification (ID) numbers of the respective clustered documents beyond the “fresh” life span of the clustered documents. When clusters are formed according to similar content, an ID number and associated attributes are assigned to each of the clusters. This provides a mechanism to track and retrieve the respective clusters for subsequent delivery of search results. The respective ID numbers of the clusters are maintained, even after the documents are no longer considered “fresh.” These similar-content clusters are further subdivided according to publication date. This provides individual subdivided clusters for similar content events that occurred at different time spans, which are delivered along with individual non-clustered search results in a SERP.