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Title: Method and system to discover and recommend interesting documents

Abstract

Disclosed are several examples of systems that can read millions of news feeds per day about topics (e.g., your customers, competitors, markets, and partners), and provide a small set of the most relevant items to read to keep current with the overwhelming amount of information currently available. Topics of interest can be chosen by the user of the system for use as seeds. The seeds can be vectorized and compared with the target documents to determine their similarity. The similarities can be sorted from highest to lowest so that the most similar seed and target documents are at the top of the list. This output can be produced in XML format so that an RSS Reader can format the XML. This allows for easy Internet access to these recommendations.

Inventors:
; ;
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1341872
Patent Number(s):
9,558,185
Application Number:
13/737,652
Assignee:
UT-Battelle LLC (Oak Ridge, TN) ORNL
DOE Contract Number:  
AC05-00OR22725
Resource Type:
Patent
Resource Relation:
Patent File Date: 2013 Jan 09
Country of Publication:
United States
Language:
English
Subject:
99 GENERAL AND MISCELLANEOUS

Citation Formats

Potok, Thomas Eugene, Steed, Chad Allen, and Patton, Robert Matthew. Method and system to discover and recommend interesting documents. United States: N. p., 2017. Web.
Potok, Thomas Eugene, Steed, Chad Allen, & Patton, Robert Matthew. Method and system to discover and recommend interesting documents. United States.
Potok, Thomas Eugene, Steed, Chad Allen, and Patton, Robert Matthew. Tue . "Method and system to discover and recommend interesting documents". United States. doi:. https://www.osti.gov/servlets/purl/1341872.
@article{osti_1341872,
title = {Method and system to discover and recommend interesting documents},
author = {Potok, Thomas Eugene and Steed, Chad Allen and Patton, Robert Matthew},
abstractNote = {Disclosed are several examples of systems that can read millions of news feeds per day about topics (e.g., your customers, competitors, markets, and partners), and provide a small set of the most relevant items to read to keep current with the overwhelming amount of information currently available. Topics of interest can be chosen by the user of the system for use as seeds. The seeds can be vectorized and compared with the target documents to determine their similarity. The similarities can be sorted from highest to lowest so that the most similar seed and target documents are at the top of the list. This output can be produced in XML format so that an RSS Reader can format the XML. This allows for easy Internet access to these recommendations.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Jan 31 00:00:00 EST 2017},
month = {Tue Jan 31 00:00:00 EST 2017}
}

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