Predictive Session-Based Search Engine for Faster Data Retrieval

Solution Overview

Problem

Large data stores used in computing systems, such as those in customer service centers, are inefficient in providing relevant information due to the vast quantity of irrelevant data, leading to slow response times and high computing resource consumption during search queries.

Innovation Solution

Implementing a predictive session-based search engine that pre-fetches and indexes information likely to be accessed during a session, using a machine learning model to identify relevant data and store it in an ad-hoc data store for faster retrieval, reducing the need for extensive querying of original data sources.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of time

If a predictive session-based search engine pre-fetches and indexes information likely to be accessed during a session, then response time is reduced and computing resource consumption is reduced, but device complexity increases

Engineering Contradiction:

Improveresponse timeVSAvoiddevice complexity

Core Design Contradiction:

Loss of timeVSDevice complexity

Solution Approach 1:

The system performs preliminary actions by pre-fetching and indexing information that is likely to be accessed during a session before the actual search query is executed. The predictive session-based search engine identifies and retrieves relevant data from data sources in advance, storing it in an optimized format for faster retrieval during the session, thereby reducing response time while managing complexity through automated prediction algorithms

Inventive Principle:

Principle #10Preliminary action

2Use of energy by moving object

If a predictive session-based search engine pre-fetches and indexes information likely to be accessed during a session, then computing resource consumption is reduced, but device complexity increases

Engineering Contradiction:

Improvecomputing resource consumptionVSAvoiddevice complexity

Core Design Contradiction:

Use of energy by moving objectVSDevice complexity

Solution Approach 1:

The system performs preliminary actions by pre-fetching and indexing information that is likely to be accessed during a session before the actual search query is executed. The predictive session-based search engine identifies and retrieves relevant data from data sources in advance, storing it in an optimized format for faster retrieval during the session, thereby reducing response time while managing complexity through automated prediction algorithms

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system extracts only the necessary subset of information from large data stores that is relevant to the current session. By using prediction algorithms to identify and extract only the data that will be needed, the system avoids processing and storing unnecessary information, reducing computing resource consumption while maintaining manageable system complexity

Inventive Principle:

Principle #2Taking out (Extraction)

3Reliability

If extensive querying of original data sources is performed, then comprehensive search results are obtained, but response time increases and computing resource consumption increases

Engineering Contradiction:

Improvesearch result comprehensivenessVSAvoidresponse time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system extracts only the necessary subset of information from large data stores that is relevant to the current session. By using prediction algorithms to identify and extract only the data that will be needed, the system avoids processing and storing unnecessary information, reducing computing resource consumption while maintaining manageable system complexity

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The system performs partial querying by retrieving only the subset of data that is predicted to be relevant to the session, rather than querying all available data. This partial action approach balances comprehensiveness with efficiency, providing sufficient search results for the session context while significantly reducing response time and resource consumption

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS10572531B1Predictive session-based search engine

Publication Date: 2020.02.25 AMAZON TECH INC

AI summary

Systems and methods are described for providing a predictive session-based search engine. A predictive session-based search engine may identify and pre-fetch data from various data sources that is likely to be accessed during a particular session. Data sources may include other search engines, databases, web servers, and other sources of information. A plug-in controller architecture, which may include templates, computer-executable instructions, application programming interface (API) calls, or other information that enables access to a particular data source, may be used to allow the predictive session-based search engine to obtain data from the data sources. The predictive session-based search engine may store and index the data it obtains, and may answer search queries during the session with data that is stored and indexed locally rather than retrieving data from the original sources. The predictive session-based search engine may similarly process updates to the session data using the plug-in architecture.