Distributed Document Store Dynamic Query Routing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current peer-to-peer networks face inefficiencies in search operations due to unstructured data and lack of dynamic adaptation to changes in document collections and user interests, leading to suboptimal search query routing and resource consumption.
Innovation Solution
The method involves assigning similarity measures between sub-collections, automatically generating search queries from their contents, and updating these measures based on query responses to strengthen connections between sub-collections that provide matching resources, thereby improving search efficiency and resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If search queries are routed in unstructured peer-to-peer networks, then search operations can be performed, but search efficiency and resource utilization are suboptimal
Solution Approach 1:
The patent segments the unstructured document collection into multiple sub-collections based on similarity measures. Each sub-collection is assigned a representative search query, enabling targeted routing of search requests to specific sub-collections rather than searching the entire unstructured network, thereby improving search efficiency and reducing resource consumption.
Solution Approach 2:
The patent implements dynamic adaptation by automatically generating search queries from sub-collection contents and updating similarity measures based on query responses. This dynamic process allows the system to adapt to changes in document collections and user interests over time, optimizing search routing continuously.
2Adaptability or versatility
If static categorization methods are used, then document structure is established, but the system cannot adapt to changes in document collections and user interests
Solution Approach 1:
The patent implements self-service through automatic generation of search queries from sub-collection contents and automatic updating of similarity measures based on query responses. The system self-adapts to changes in document collections and user interests without requiring manual re-categorization, maintaining adaptability while managing complexity through automation.
Solution Approach 2:
The patent incorporates feedback mechanisms where query responses are used to update similarity measures between sub-collections. This feedback loop enables the system to learn from actual search behavior and document changes, continuously improving its categorization and adaptability without manual intervention.
3Productivity
If manual categorization is performed, then document structure is created, but the process is time-consuming and cannot keep pace with document changes
Solution Approach 1:
The patent enables automatic categorization where the system generates search queries from sub-collection contents and automatically updates similarity measures based on query responses. This self-service approach eliminates manual categorization time while maintaining accuracy through continuous adaptation to document changes and user interests.
Solution Approach 2:
The patent performs preliminary action by automatically generating search queries from sub-collection contents before actual search operations. This pre-processing enables rapid categorization and indexing of documents, allowing the system to keep pace with document changes without manual intervention.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A peer-to-peer network providing a distributed document store is disclosed. A problem with known distributed document stores is that search engines are unable to respond quickly to changes in the stored documents or the addition or removal of peers. In the described embodiment, the peers in the network send search queries to one another and each keeps a record of which peers most frequently respond to those queries, and the quality of the responses. The peers each maintain a data structure 46 including connection weights to each of the other peers which depend on that record. By then forwarding search queries to peers selected on the basis of the connection weights, rapid retrieval of relevant documents is enabled. Search queries are generated automatically by peers as well as being generated by users. Because the generation of search queries (either automatically or by users) updates the connection weights, the peer-to-peer network is able to rapidly adapted to changes in the documents stored in the peer-to-peer network. In addition to document storage and retrieval the invention finds application in distributed applications which dynamically select a Web Service to perform a function at run-time.