18183847. AUTOMATIC DOCUMENT RANKING FOR COMPUTER ASSISTED INNOVATION simplified abstract (Dell Products L.P.)
Contents
AUTOMATIC DOCUMENT RANKING FOR COMPUTER ASSISTED INNOVATION
Organization Name
Inventor(s)
Iam Palatnik De Sousa of Rio de Janeiro (BR)
Alexander Eulalio Robles Robles of Valinhos (BR)
Werner Spolidoro Freund of Rio de Janeiro (BR)
AUTOMATIC DOCUMENT RANKING FOR COMPUTER ASSISTED INNOVATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 18183847 titled 'AUTOMATIC DOCUMENT RANKING FOR COMPUTER ASSISTED INNOVATION
The abstract of the patent application describes a method that involves receiving input from a user, which includes reference information and a document corpus consisting of a group of documents. The method then performs a byte pair encoding (BPE) process and/or preprocessing on the documents in the corpus to generate a TDF-IDF vector for each document. These vectors are compared to the reference information, and based on this comparison, the documents are ranked according to their relevance to the reference information.
- Byte pair encoding (BPE) process and/or preprocessing on documents
- Generation of TDF-IDF vectors for each document in the corpus
- Comparison of TDF-IDF vectors to reference information
- Ranking of documents based on relevance to reference information
Potential Applications: - Information retrieval systems - Document classification algorithms - Search engine result ranking
Problems Solved: - Efficient document ranking based on relevance - Improved information retrieval accuracy
Benefits: - Enhanced search result relevance - Time-saving in information retrieval processes
Commercial Applications: Title: "Enhanced Document Ranking Technology for Information Retrieval Systems" This technology can be used in search engines, content management systems, and data analysis tools to improve the accuracy and efficiency of document ranking and information retrieval processes.
Questions about the technology: 1. How does the byte pair encoding (BPE) process contribute to the generation of TDF-IDF vectors? 2. What are the potential limitations of using TDF-IDF vectors for document ranking in information retrieval systems?
Original Abstract Submitted
One example method includes receiving input from a user, the input including reference information, and a document corpus that comprises a group of documents, performing a byte pair encoding (BPE) process, and/or preprocessing, on the documents in the document corpus, so as to generate a respective TDF-IDF (term frequency-inverse document frequency) vector for each of the documents in the document corpus, comparing each of the TDF-IDF vectors to the reference information, and based on the comparing, ranking the documents according to their respective relevance to the reference information.
