Recommending personally interested contents by text mining, filtering, and interfaces
Abstract
A personalized content recommendation system includes a client interface device configured to monitor a user's information data stream. A collaborative filter remote from the client interface device generates automated predictions about the interests of the user. A database server stores personal behavioral profiles and user's preferences based on a plurality of monitored past behaviors and an output of the collaborative user personal interest inference engine. A programmed personal content recommendation server filters items in an incoming information stream with the personal behavioral profile and identifies only those items of the incoming information stream that substantially matches the personal behavioral profile. The identified personally relevant content is then recommended to the user following some priority that may consider the similarity between the personal interest matches, the context of the user information consumption behaviors that may be shown by the user's content consumption mode.
- Inventors:
- Issue Date:
- Research Org.:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1224433
- Patent Number(s):
- 9171068
- Application Number:
- 13/785,117
- Assignee:
- UT-Battelle, LLC (Oak Ridge, TN)
- Patent Classifications (CPCs):
-
G - PHYSICS G06 - COMPUTING G06F - ELECTRIC DIGITAL DATA PROCESSING
- DOE Contract Number:
- AC05-00OR22725
- Resource Type:
- Patent
- Resource Relation:
- Patent File Date: 2013 Mar 05
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 96 KNOWLEDGE MANAGEMENT AND PRESERVATION
Citation Formats
Xu, Songhua. Recommending personally interested contents by text mining, filtering, and interfaces. United States: N. p., 2015.
Web.
Xu, Songhua. Recommending personally interested contents by text mining, filtering, and interfaces. United States.
Xu, Songhua. Tue .
"Recommending personally interested contents by text mining, filtering, and interfaces". United States. https://www.osti.gov/servlets/purl/1224433.
@article{osti_1224433,
title = {Recommending personally interested contents by text mining, filtering, and interfaces},
author = {Xu, Songhua},
abstractNote = {A personalized content recommendation system includes a client interface device configured to monitor a user's information data stream. A collaborative filter remote from the client interface device generates automated predictions about the interests of the user. A database server stores personal behavioral profiles and user's preferences based on a plurality of monitored past behaviors and an output of the collaborative user personal interest inference engine. A programmed personal content recommendation server filters items in an incoming information stream with the personal behavioral profile and identifies only those items of the incoming information stream that substantially matches the personal behavioral profile. The identified personally relevant content is then recommended to the user following some priority that may consider the similarity between the personal interest matches, the context of the user information consumption behaviors that may be shown by the user's content consumption mode.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Oct 27 00:00:00 EDT 2015},
month = {Tue Oct 27 00:00:00 EDT 2015}
}
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