Customized Search Platform with Neural Ranker
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Solution Overview
Problem
Users have limited control and transparency over search results in existing search engines, which can lead to inefficient searches, especially when looking for specific data from dedicated databases, and there is a lack of control over personal information collection and usage.
Innovation Solution
A customized search platform that allows users to prioritize and select data sources based on search query characteristics and personal preferences, using a neural-network based ranker and parser to intelligently recommend and filter search results, providing users with control over their search experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If existing search engines crawl all web data to provide comprehensive search results, then the quantity of search results is improved, but the user has little control or transparency on how or where the search engines conduct their search
Solution Approach 1:
The patent segments the monolithic search engine into multiple independent data source modules, each representing a specific data source (e.g., web crawl, dedicated databases, personal information). Users can selectively enable or disable individual data sources, providing granular control while maintaining comprehensive search capabilities when all sources are active.
Solution Approach 2:
The patent adds a new dimension of user control by introducing a visibility and selection layer above the traditional search result list. This dimension allows users to control which data sources are accessed and how results are presented, transforming the flat search interface into a multi-dimensional system with source selection, transparency indicators, and customizable result views.
2Loss of information
If search engines provide results from all data sources, then the comprehensiveness of search results is improved, but the search efficiency decreases when looking for specific data from dedicated databases
Solution Approach 1:
The patent implements preliminary action by allowing users to pre-configure their preferred data sources and search preferences before performing searches. The system pre-establishes the search configuration, so when a search is executed, it immediately queries only the selected data sources without needing to process or filter results from all possible sources, significantly improving efficiency for targeted searches.
Solution Approach 2:
The patent applies local quality by allowing different search configurations for different data sources. Each data source can be individually optimized and selected based on the specific search needs. For example, users can dedicate certain searches to specific databases while maintaining comprehensive web crawling for other types of queries, ensuring optimal performance for each search context.
3Adaptability or versatility
If search engines collect personal information to improve search results, then the personalization of search experience is improved, but the user has little control over personal information collection and usage
Solution Approach 1:
The patent implements self-service by giving users direct control over their personal information settings and data source selections. Users can independently configure which data sources are accessed, what personal information is collected, and how results are personalized. The system provides tools for users to manage their own search experience without requiring system administrator intervention or complex settings management.
Solution Approach 2:
The patent incorporates feedback mechanisms that allow users to review and adjust their search configurations, data source selections, and personal information settings. The system provides visibility into how personal information is being used and allows users to modify their preferences based on this feedback, creating a continuous loop of user control and system adaptation.
Data Source
AI summary
Embodiments described herein provide systems and methods for a customized search platform that provides users control and transparency in their searches. The system may use a ranker and parser to utilize input data and contextual information to identify search applications, sort the search applications, and present search results via user-engageable elements. The system may also use input from a user to personalize and update search results based on a user's interaction with user-engageable elements.