Automated Document Assembly via Triggering Item Feature Extraction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing data management methods are time-consuming and inefficient, as they rely heavily on user knowledge and iteration, often failing to locate all relevant documents related to an event or task, such as business trips or interviews, due to the manual nature of desktop searches.
Innovation Solution
A method and apparatus that automatically extracts features from a triggering item to assemble relevant documents from various electronic sources, using a system comprising a harvester, full text query processor, classifier, and set builder to rank and filter documents, which can be connected to network storage and the World Wide Web, and utilizes user feedback to refine future document sets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual desktop search is used to locate relevant documents, then the searcher can find documents they already know about, but the search is time-consuming and may miss relevant documents
Solution Approach 1:
The system performs automatic desktop search without requiring user initiation or manual querying. The computing device autonomously identifies and assembles relevant documents based on triggering items, eliminating the need for users to manually search and reducing search time while improving completeness through automated feature extraction and multiple search iterations
Solution Approach 2:
The system pre-assembles relevant document sets in advance by continuously monitoring for triggering items and automatically gathering related documents. When a triggering item is detected, the corresponding document set is already prepared and immediately presented to the user, eliminating the need for on-demand manual searching
2Reliability
If multiple search iterations are performed to locate all relevant documents, then more documents may be found, but the search process becomes increasingly time-consuming
Solution Approach 1:
The system performs continuous automated searching and document assembly in the background without interruption. Multiple search iterations are executed automatically with different search strategies and features, maintaining continuous useful action to gather comprehensive document sets while improving efficiency by eliminating manual iteration overhead
Solution Approach 2:
The system dynamically adjusts search parameters and strategies based on the triggering item characteristics and previously found documents. The automated search process adapts by extracting different features from triggering items and adjusting search queries across multiple iterations, improving both completeness and efficiency through dynamic optimization
3Productivity
If the system automatically assembles document sets without user requests, then document gathering becomes faster and more comprehensive, but the system complexity increases
Solution Approach 1:
The automated document assembly system is divided into distinct functional modules: triggering item detection, feature extraction, document search, document assembly, and user feedback processing. Each module performs a specific function independently, making the overall complex system manageable through segmentation while maintaining high productivity through automated operation
Solution Approach 2:
Feature extraction acts as an intermediary process between triggering items and document search. The system extracts relevant features from triggering items to guide the document search process, serving as a mediator that translates user context into searchable criteria, thereby managing system complexity through structured intermediate processing
Data Source
AI summary
The present invention relates to a method and apparatus for assembling a set of documents related to a triggering item. One embodiment of a method for assembling a set of electronic documents related to an electronic triggering item detected by a computing device being operated by a user includes automatically extracting by the computing device a set of features from the triggering item, without receiving a request by the user to assemble the set of electronic documents, and assembling as the set of electronic documents a plurality of documents that is relevant to the set of features, wherein the plurality of documents is retrieved from a plurality of different types of electronic sources.