Location Name Identification in Text Documents
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional keyword-based search engines struggle to precisely identify and disambiguate location names within documents, often returning irrelevant results due to ambiguity between geographical and non-geographical meanings, and fail to effectively associate documents with specific locations.
Innovation Solution
Implementing a system that uses a gazetteer and machine learning algorithms, such as SVM models, for location detection and recognition, which differentiate between location names and common words, and disambiguate between multiple location senses by leveraging contextual hints and statistical probabilities, to enhance the relevance of search results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional keyword-based search is used to find location names in documents, then the search process is simple and fast, but the accuracy of location identification deteriorates due to ambiguity between geographical and non-geographical meanings
Solution Approach 1:
The patent segments the location identification process into two distinct stages: location detection (identifying potential location names using statistical probabilities) and location recognition (disambiguating between multiple location senses using contextual hints). This segmentation allows the system to achieve high accuracy while managing complexity through modular processing steps.
Solution Approach 2:
The patent introduces an intermediary disambiguation process that uses contextual hints from surrounding text to resolve ambiguity between multiple location senses. This intermediary step acts as a mediator between the initial location detection and the final location identification, improving accuracy without requiring complete system redesign.
2Measurement precision
If location disambiguation using contextual hints is implemented, then location recognition accuracy is improved, but processing time and computational complexity increase
Solution Approach 1:
The patent performs preliminary location detection using statistical probabilities from a corpus before conducting the more computationally intensive disambiguation process. This preliminary action filters and prioritizes potential location names, reducing the search space for the subsequent disambiguation step and thereby reducing overall processing time.
Solution Approach 2:
The patent implements a feedback mechanism where results from location recognition are used to validate and refine location detection results. This iterative feedback process improves accuracy by allowing the system to learn from contextual patterns while optimizing processing efficiency through targeted re-evaluation of ambiguous cases.
Data Source
AI summary
Concepts and technologies are described herein for identifying location names within document text. Through an implementation of the concepts and technologies presented herein, functionality can be provided for identifying location names within articles, websites, travelogues, or other such documents. For instance, documents containing the names of cities, regions, countries, landmarks, or other locations may be associated with those locations. The location names may be unambiguously identified even when the location names may also have common word meanings that are not location associated or when the location name may be associated with more than one location.