Dynamic Personal Region of Interest for Adaptive POI Search
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Solution Overview
Problem
Current location-based POI search systems fail to provide results tailored to individual users' contexts and preferences, often returning unnecessary information and missing relevant results due to their lack of adaptability.
Innovation Solution
The system computes a personal region of interest based on user disposition, incorporating current location, history, user profile, and context, to dynamically and continuously adapt search results to the user's specific needs, using a more sophisticated database structure that includes user-profiles, user-histories, and time-associated events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a fixed-radius search area is used for location-based POI searching, then the search process is simple and fast, but the search results are not tailored to individual users' needs and contexts
Solution Approach 1:
The patent applies dynamics by transforming the static fixed-radius search area into a dynamic personal region of interest that continuously adapts to user behavior, preferences, and context. The search radius and boundaries are no longer fixed but evolve over time based on user interactions, making the system adaptable while managing complexity through automated learning mechanisms.
Solution Approach 2:
The patent implements feedback by continuously monitoring user interactions with search results and using this information to refine and adjust the personal region of interest. User preferences, selection patterns, and contextual data feed back into the system to dynamically modify search parameters, enabling personalized results without manual reconfiguration.
2Loss of information
If search results are customized to individual users, then relevance and utility improve, but the system requires more complex data structures and processing
Solution Approach 1:
The patent applies segmentation by dividing the database structure into distinct modules: user profiles storing preferences and characteristics, interaction histories recording user behaviors, and contextual data structures capturing situational information. This modular segmentation enables personalized search results while managing complexity through organized, separable data components.
Solution Approach 2:
The patent implements nesting by organizing data structures in hierarchical layers where user profiles contain interaction histories, which in turn contain contextual information about specific searches. This nested organization allows the system to access relevant information at appropriate levels of detail without requiring complex flat structures.
3Measurement precision
If the search area is dynamically adjusted based on user disposition, then search precision and personalization improve, but the computational requirements increase
Solution Approach 1:
The patent applies partial action by computing user disposition and adjusting the personal region of interest to a degree sufficient for personalization without requiring complete recalculation of all search parameters. The system dynamically adjusts search precision based on user context rather than maximizing computational effort for every query, achieving acceptable personalization with moderate computational investment.
Data Source
AI summary
Embodiments of the present invention are directed to flexible, user-adapted, continuous searching, on behalf of a particular user, for points of interest relevant to the user's current location within a specifically computed personal region of interest. In a general case, the personal region of interest is computed as a function of the user's level of disposition towards the searched-for points of interest. The level of disposition towards the searched-for points of interest may, in turn, be based on two or more of the user's location, the current date and time, a history of the user's interaction with the POI-searching system, including user-initiated searches and user selections from displayed search results, a user profile developed for, and continuously updated on behalf of, the user, and a current context for the search, as specified by a search query or by other context-specifying means. The personal region of interest generally defines an abstract area, volume, or hypervolume within which method and system embodiments of the present invention search for points of interest.