Personalized Action-Based Deeplinks for Search Results
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Solution Overview
Problem
Users face inefficiencies when searching for information online as they often need to browse through websites after selecting search results, as traditional deeplinks are not consistently formatted across web pages, leading to a fragmented experience and missed opportunities for quick access to desired information or actions.
Innovation Solution
The implementation of action-based deeplinks that categorize web pages and identify common actions within specific categories, providing consistent hyperlinks for tasks like checking flights or booking reservations across airline websites, and the use of user behavior information to personalize search results with relevant deeplinks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional deeplinks are used for search results, then users can access specific web pages within websites, but the inconsistent formatting across web pages leads to fragmented user experience and requires additional browsing to find desired information
Solution Approach 1:
The patent transforms traditional deeplinks from static, website-specific URLs into dynamic, context-aware action links. The system changes the parameters of deeplinks by incorporating user behavior data, website category information, and action-type classifications to generate personalized, consistent action-based links across different websites within the same category.
Solution Approach 2:
The patent segments the web page content into distinct action types (e.g., booking, checking, searching) and creates separate action-based deeplinks for each identified action. This segmentation allows users to directly access specific actions without browsing through entire web pages, thereby reducing navigation time and improving operational ease.
2Adaptability or versatility
If personalized deeplinks are generated based on user behavior information, then the relevance and usefulness of search results is improved, but the complexity of tracking and processing user behavior data increases
Solution Approach 1:
The system performs preliminary actions by pre-tracking and storing user behavior information, website category classifications, and action type identifications in advance. This preliminary data collection and organization enables rapid generation of personalized deeplinks without requiring complex real-time processing when users submit search queries.
Solution Approach 2:
The patent introduces intermediary components including a user behavior tracking system, a website category classification system, and an action type identification system. These intermediaries process and structure raw data into usable formats, mediating between user interactions and the final personalized deeplink generation, thereby reducing the complexity burden on the core search system.
3Productivity
If action-based deeplinks are implemented to provide consistent formatting across category-specific web pages, then quick access to desired actions is enabled, but the requirement to categorize websites and identify actions increases system complexity
Solution Approach 1:
The patent creates a universal action-based deeplink system that works across multiple website categories (travel, shopping, news, etc.). The same action identification and link generation mechanisms are applied universally to different website types, allowing the system to handle diverse websites with a single, multi-functional framework rather than requiring separate systems for each category.
Data Source
AI summary
Search results are provided with personalized deeplinks for an end user. User behavior information is gathered regarding web pages visited by the end user. When the end user submits a search query, the website category of a search result is identified and user behavior information regarding web pages visited at other websites within the website category is identified. At least one deeplink is selected for the search result based on that user behavior information. In some instances, user behavior information may be tracked for a group of end users. The user behavior information for the group of end users may be used in conjunction with the user behavior information for the end user to facilitate deeplink selections for search results returned in response to search queries from the end user.