Patent US6493744B1 successfully refreshed from Google Patents.
US6493744B1
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Automatic rating and filtering of data files for objectionable content
Assignee: International Business Machines Corp
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Filing: 1999-08-16
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Granted: 2002-12-10
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Expires: 2019-08-16
Abstract
Abstract An automatic method for rating data files for objectionable content in a distributed computer system includes preprocessing the file to create semantic units, comparing the semantic units with a rating repository containing entries and associated ratings, assigning content rating vectors to the semantic units, and creating a modified data file incorporating rating information derived from the content rating vectors. For text files, the semantic units are words or phrases, and the rating repository also contains words or phrases with corresponding content rating vectors. For audio files, the file is first converted to a text file using voice recognition software. For image files, image processing software is used to recognize individual objects and compare them to basic images and ratings stored in the rating repository. In one embodiment, a composite content rating vector is derived for the file from the individual content rating vectors, and the composite content rating vector is incorporated into the modified file. In an alternate embodiment, semantic units with content rating vectors exceeding preset user limit values of objectionable content are blocked out by display blocks or, for audio, audio blanking signals, for example, beeps. The user can then view or hear the remaining portions of the file. The invention can be used with any type of data file that can be divided into semantic units, and can be implemented in a server, client, search engine, or proxy server.
Inventors
- 👤 Michael Lawrence Emens
- 👤 Reiner Kraft
- 👤 Neelakantan Sundaresan
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-10-27 17:04
CPC Classifications
H; H04; H04L; H04L69/00; H04L69/30; H04L69/32; H04L69/322; H04L69/329; H04L67/00; H04L67/50; H04L67/56; H04L67/564; H04L67/568; H04L67/561; Y; Y10; Y10S; Y10S707/00; Y10S707/99931; Y10S707/99939
Claims Analysis
Total Claims: 46
Claim 1
Independent Claim
174 words
In a distributed computer system, a computer-implemented method for automatic rating a raw data file for objectionable content, wherein said raw data file is a hypermedia file, a text file, an audio file, or an image file, said method comprising the steps of: preprocessing said raw data file to create semantic units representative of semantic contents of said raw data file; comparing said semantic units with a content rating repository comprising semantic entries and corresponding content ratings; assigning content rating vectors to said semantic units based on said comparing step; and creating a modified data file incorporating rating information derived from said content rating vectors, wherein when said raw data file is an audio file and said modified data file is a modified audio file, said preprocessing step further comprising the steps of: using a voice recognition system to create text data from said audio file; creating an audio-to-text correlation between a location in said text data and a corresponding location in said audio file; and parsing said text data into said semantic units.
Claim 2
Dependent Claim
174 words
In a distributed computer system, a computer-implemented method for automatic rating a raw data file for objectionable content, wherein said raw data file is a hypermedia file, a text file, an audio file, or an image file, said method comprising the steps of: preprocessing said raw data file to create semantic units representative of semantic contents of said raw data file; comparing said semantic units with a content rating repository comprising semantic entries and corresponding content ratings; assigning content rating vectors to said semantic units based on said comparing step; and creating a modified data file incorporating rating information derived from said content rating vectors, wherein when said raw data file is an audio file and said modified data file is a modified audio file, said preprocessing step further comprising the steps of: using a voice recognition system to create text data from said audio file; creating an audio-to-text correlation between a location in said text data and a corresponding location in said audio file; and parsing said text data into said semantic units.
Claim 3
Dependent Claim
53 words
The computer-implemented method of claim 1 wherein said step of creating a modified data file comprises the steps of: deriving a composite content rating vector for said raw data file from said content rating vectors; and combining said composite content rating vector with said raw data file to produce said modified data file.
Claim 4
Dependent Claim
35 words
The computer-implemented method of claim 2 wherein said composite content rating vector comprises a set of components, wherein each component in said set of components is derived from corresponding components of said content rating vectors.
Claim 5
Dependent Claim
46 words
The computer-implemented method of claim 3 wherein each component of said composite content rating vector is a weighted average of said corresponding components of said content rating vectors, said weighted average including weighting factors related to values of said corresponding components of said content rating vectors.
Claim 6
Dependent Claim
59 words
The computer-implemented method of claim 3 wherein each component of said composite content rating vector is equal to a selected value of said corresponding components of said content rating vectors, wherein said selected value is a highest of said corresponding components of said content rating vectors and said selected value has at least a predetermined minimum number of occurrences.
Claim 7
Dependent Claim
13 words
The computer-implemented method of claim 2 wherein said method occurs in a server.
Claim 8
Dependent Claim
24 words
The computer-implemented method of claim 2 wherein said raw data file is stored in a server and said method occurs in a proxy server.
Claim 9
Dependent Claim
23 words
The computer-implemented method of claim 2 wherein said raw data file is stored in a server and said method occurs in a client.
Claim 10
Dependent Claim
73 words
The computer-implemented method of claim 1 wherein said step of creating a modified data file comprises the steps of: comparing said content rating vectors with preset user limit values to identify objectionable semantic units, wherein said preset user limit values define objectionable content rating vectors; and replacing objectionable content corresponding to the identified objectionable semantic units in a copy of said raw data file with display blocks to produce said modified data file.
Claim 11
Dependent Claim
24 words
The computer-implemented method of claim 9 wherein said raw data file is a file chosen from the group consisting of text, audio, and image.
Claim 12
Dependent Claim
23 words
The computer-implemented method of claim 9 wherein said raw data file is stored in a server and said method occurs in a client.
Claim 13
Dependent Claim
24 words
The computer-implemented method of claim 9 wherein said preset user limit values are stored in a client and said method occurs in a server.
Claim 14
Dependent Claim
34 words
The computer-implemented method of claim 9 wherein said preset user limit values are stored in a client, said raw data file is stored in a server, and said method occurs in a proxy server.
Claim 15
Dependent Claim
74 words
The computer-implemented method of claim 9 , wherein said step of creating a modified data file further comprises the steps of: deriving a modified composite content rating vector for said modified data file from a modified set of content rating vectors, wherein said modified set of content rating vectors does not contain content rating vectors corresponding to said objectionable semantic units; and storing said modified composite content rating vector in said modified data file.
Claim 16
Dependent Claim
24 words
The computer-implemented method of claim 14 wherein said preset user limit values are stored in a client and said method occurs in a server.
Claim 17
Dependent Claim
34 words
The computer-implemented method of claim 14 wherein said preset user limit values are stored in a client, said raw data file is stored in a server, and said method occurs in a proxy server.
Claim 18
Dependent Claim
86 words
The computer-implemented method of claim 1 wherein said step of creating a modified audio file comprises the steps of: comparing said content rating vectors with preset user limit values to identify objectionable semantic units, wherein said preset user limit values define objectionable content rating vectors; using said audio-to-text correlation to locate objectionable portions of said audio file corresponding to the identified objectionable semantic units; and replacing said objectionable portions in a copy of said audio file with audio blanking signals to produce said modified audio file.
Claim 19
Dependent Claim
22 words
The computer-implemented method of claim 17 wherein said audio file is stored in a server and said method occurs in a client.
Claim 20
Dependent Claim
24 words
The computer-implemented method of claim 17 wherein said preset user limit values are stored in a client and said method occurs in a server.
Claim 21
Dependent Claim
33 words
The computer-implemented method of claim 17 wherein said preset user limit values are stored in a client, said audio file is stored in a server, and said method occurs in a proxy server.
Claim 22
Dependent Claim
47 words
The computer-implemented method of claim 1 wherein said raw data file is an image file, said modified data file is a modified image file, said semantic units are discrete objects in regions within said image file, and said preprocessing step is performed by an image processing system.
Claim 23
Dependent Claim
72 words
The computer-implemented method of claim 21 wherein said step of creating a modified image file comprises the steps of: comparing said content rating vectors with preset user limit values to identify objectionable discrete objects, wherein said preset user limit values define objectionable content rating vectors; and replacing objectionable content corresponding to the identified objectionable discrete objects in a copy of said image file with image blocks to produce said modified image file.
Claim 24
Dependent Claim
22 words
The computer-implemented method of claim 22 wherein said image file is stored in a server and said method occurs in a client.
Claim 25
Dependent Claim
24 words
The computer-implemented method of claim 22 wherein said preset user limit values are stored in a client and said method occurs in a server.
Claim 26
Dependent Claim
33 words
The computer-implemented method of claim 22 wherein said preset user limit values are stored in a client, said image file is stored in a server, and said method occurs in a proxy server.
Claim 27
Independent Claim
198 words
A method for automatic rating and filtering in a network environment a raw data file for objectionable content, wherein said raw data file is a hypermedia file, a text file, an audio file, or an image file, said method comprising the steps of: preprocessing said raw data file to create semantic units representative of semantic contents of said raw data file, wherein if said raw data file is an audio file said preprocessing step farther comprises the steps of: using a voice recognition system to create text data from said audio file; creating an audio-to-text correlation between a location in said text data and a corresponding location in said audio file; and parsing said text data into said semantic units; and wherein if said raw data file is an image file said semantic units are discrete objects in regions within said image file and said preprocessing step is performed by an image processing system; comparing said semantic units with a content rating repository comprising semantic entries and corresponding content ratings; assigning content rating vectors to said semantic units based on said comparing step; and creating a modified data file incorporating rating information derived from said content rating vectors.
Claim 28
Independent Claim
198 words
A method for automatic rating and filtering in a network environment a raw data file for objectionable content, wherein said raw data file is a hypermedia file, a text file, an audio file, or an image file, said method comprising the steps of: preprocessing said raw data file to create semantic units representative of semantic contents of said raw data file, wherein if said raw data file is an audio file said preprocessing step farther comprises the steps of: using a voice recognition system to create text data from said audio file; creating an audio-to-text correlation between a location in said text data and a corresponding location in said audio file; and parsing said text data into said semantic units; and wherein if said raw data file is an image file said semantic units are discrete objects in regions within said image file and said preprocessing step is performed by an image processing system; comparing said semantic units with a content rating repository comprising semantic entries and corresponding content ratings; assigning content rating vectors to said semantic units based on said comparing step; and creating a modified data file incorporating rating information derived from said content rating vectors.
Claim 29
Dependent Claim
78 words
The method of claim 26 , wherein said step of creating a modified data file further comprises the steps of: deriving a composite content rating vector for said raw data file from said content rating vectors, wherein said composite content rating vector comprises a set of components each of which is derived from corresponding components of said content rating vectors; and combining said composite content rating vector with said raw data file to produce said modified data file.
Claim 30
Dependent Claim
46 words
The method of claim 27 , wherein each component of said composite content rating vector is a weighted average of said corresponding components of said content rating vectors, said weighted average including weighting factors related to values of said corresponding components of said content rating vectors.
Claim 31
Dependent Claim
60 words
The method of claim 27 , wherein each component of said composite content rating vector is equal to a selected value of said corresponding components of said content rating vectors, and wherein said selected value is the highest of said corresponding components of said content rating vectors and said selected value has at least a predetermined minimum number of occurrences.
Claim 32
Dependent Claim
13 words
The method of claim 26 , wherein said method occurs in a server.
Claim 33
Dependent Claim
24 words
The method of claim 26 , wherein said raw data file is stored in a server and said method occurs in a proxy server.
Claim 34
Dependent Claim
23 words
The method of claim 26 , wherein said raw data file is stored in a server and said method occurs in a client.
Claim 35
Dependent Claim
73 words
The method of claim 26 , wherein said step of creating a modified data file comprises the steps of: comparing said content rating vectors with preset user limit values to identify objectionable semantic units, wherein said preset user limit values define objectionable content rating vectors; and replacing objectionable content corresponding to the identified objectionable semantic units in a copy of said raw data file with display blocks to produce said modified data file.
Claim 36
Dependent Claim
24 words
The method of claim 33 , wherein said preset user limit values are stored in a client and said method occurs in a server.
Claim 37
Dependent Claim
34 words
The method of claim 33 , wherein said preset user limit values are stored in a client, said raw data file is stored in a server, and said method occurs in a proxy server.
Claim 38
Dependent Claim
73 words
The method of claim 33 , wherein said step of creating a modified data file further comprises the steps of: deriving a modified composite content rating vector for said modified data file from a modified set of content rating vectors, wherein said modified set of content rating vectors does not contain content rating vectors corresponding to said objectionable semantic units; and storing said modified composite content rating vector in said modified data file.
Claim 39
Dependent Claim
105 words
The method of claim 26 , wherein said raw data file is an audio file and said modified data file is a modified audio file, said step of creating a modified data file further comprises the steps of: comparing said content rating vectors with preset user limit values to identify objectionable semantic units, wherein said preset user limit values define objectionable content rating vectors; using said audio-to-text correlation to locate objectionable portions of said audio file corresponding to the identified objectionable semantic units; and replacing said objectionable portions in a copy of said audio file with audio blanking signals to produce said modified audio file.
Claim 40
Dependent Claim
22 words
The method of claim 37 , wherein said audio file is stored in a server and said method occurs in a client.
Claim 41
Dependent Claim
24 words
The method of claim 37 , wherein said preset user limit values are stored in a client and said method occurs in a server.
Claim 42
Dependent Claim
33 words
The method of claim 37 , wherein said preset user limit values are stored in a client, said audio file is stored in a server, and said method occurs in a proxy server.
Claim 43
Dependent Claim
91 words
The method of claim 26 , wherein said raw data file is an image file and said modified data file is a modified image file, said step of creating a modified data file further comprises the steps of: comparing said content rating vectors with preset user limit values to identify objectionable discrete objects, wherein said preset user limit values define objectionable content rating vectors; and replacing objectionable content corresponding to the identified objectionable discrete objects in a copy of said image file with image blocks to produce said modified image file.
Claim 44
Dependent Claim
22 words
The method of claim 41 , wherein said image file is stored in a server and said method occurs in a client.
Claim 45
Dependent Claim
24 words
The method of claim 41 , wherein said preset user limit values are stored in a client and said method occurs in a server.
Claim 46
Dependent Claim
33 words
The method of claim 41 , wherein said preset user limit values are stored in a client, said image file is stored in a server, and said method occurs in a proxy server.
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