Construction Document Search System with Entity Indexing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems for processing and analyzing large volumes of construction project specification documents are inefficient, often returning irrelevant results due to lack of advanced search functionality and inability to synthesize actionable information from vast datasets.
Innovation Solution
A construction document storage and search system that utilizes an indexing and annotation engine to identify named entities, extract relationships, and provide context-sensitive searching, generating user-friendly charts and displays to filter and analyze documents based on user queries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If basic text search is used to search for documents, then search speed is fast, but search accuracy deteriorates because documents containing unrelated references (page numbers, section numbers, area codes) are returned as matches
Solution Approach 1:
The patent applies preliminary action by pre-processing documents to create a structured index before searching. The indexing system预先 identifies and extracts named entities (companies, products, projects, locations) and organizes them in a structured format with contextual relationships, so that when a search is performed, the system can quickly retrieve relevant documents without having to analyze the full text during the search operation itself.
Solution Approach 2:
The patent introduces an intermediary indexing layer between the raw documents and the search query. This index acts as a mediator that contains extracted named entities and their contextual relationships, allowing the search system to query structured data rather than scanning unstructured text, thereby improving accuracy while maintaining speed.
2Measurement precision
If hand-labeled table of contents is used to limit searches to specific sections, then search accuracy improves, but processing time increases and ease of operation deteriorates
Solution Approach 1:
The system performs preliminary action by automatically extracting and organizing named entities and their hierarchical relationships during the indexing phase. This pre-processing creates a structured representation of document sections and their contents, enabling the search system to quickly filter and retrieve relevant sections without requiring manual table of contents creation or extensive processing during search operations.
3Loss of information
If comprehensive document analysis is performed to synthesize actionable information from large volumes of documents, then information quality improves, but productivity of manual analysis deteriorates as a single person cannot analyze fifty million pages per year
Solution Approach 1:
The patent replaces manual mechanical analysis with an automated computer-based system. The indexing and search system automatically processes and analyzes large volumes of documents, extracting named entities, establishing relationships, and synthesizing actionable information without human intervention. This substitution enables the system to handle fifty million pages per year, far exceeding human analysis capacity.
Solution Approach 2:
The system performs self-service by automatically analyzing and synthesizing information from documents without requiring manual review. The indexing engine autonomously extracts named entities, establishes contextual relationships, and generates searchable structures, enabling the system to independently process and synthesize information from large document volumes at high speed.
4Loss of information
If multiple publishers' feeds are subscribed to for comprehensive coverage, then data completeness improves, but the volume of documents to be analyzed increases making manual processing impossible
Solution Approach 1:
The patent applies universality by designing a single indexing and search system that can handle multiple publishers' feeds with different formats and structures. The system universally processes documents from various sources, extracting named entities and establishing relationships in a standardized manner, thereby managing data from multiple publishers without proportionally increasing system complexity.
Data Source
AI summary
A system comprises a data storage system, data analysis logic, and user interface logic. The data analysis logic is configured to analyze the documents and to identify documents that satisfy search criteria received from a user. The user interface logic is configured to generate a user interface. The user interface logic is also configured to generate a plurality of charts for display to the user. The user can interact with the charts to specify modified search criteria. The user interface logic is configured to receive modified search criteria from the user via one of the charts and update the remaining charts to reflect the modified search criteria.