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US5675710A
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Method and apparatus for training a text classifier
Assignee: Nokia of America Corp
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Filing: 1995-06-07
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Granted: 1997-10-07
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Expires: 2015-06-07
Abstract
Abstract A method and apparatus for training a text classifier is disclosed. A supervised learning system and an annotation system are operated cooperatively to produce a classification vector which can be used to classify documents with respect to a defined class. The annotation system automatically annotates documents with a degree of relevance annotation to produce machine annotated data. The degree of relevance annotation represents the degree to which the document belongs to the defined class. This machine annotated data is used as input to the supervised learning system. In addition to the machine annotated data, the supervised learning system can also receive manually annotated data and/or a user request. The machine annotated data, along with the manually annotated data and/or the user request, are used by the supervised learning system to produce a classification vector. In one embodiment, the supervised learning system comprises a relevance feedback mechanism. The relevance feedback mechanism is operated cooperatively with the annotation system for multiple iterations until a classification vector of acceptable accuracy is produced. The classification vector produced by the invention is the result of a combination of supervised and unsupervised learning.
Inventors
- 👤 David Dolan Lewis
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-10-28 15:55
CPC Classifications
G; G06; G06F; G06F16/00; G06F16/30; G06F16/35; G06F16/353; Y; Y10; Y10S; Y10S706/00; Y10S706/902; Y10S706/934
Claims Analysis
Total Claims: 33
Claim 1
Independent Claim
89 words
A method for training a classifier to classify at least one document which has not been manually annotated with respect to a defined class; performing an operation on data including a retrieval status value associated with the document to generate at least one parameter value; calculating a degree of relevance representing the degree to which said document belongs to said defined class, said degree of relevance being a function of at least the retrieval status value and the parameter value; and training said classifier using said degree of relevance.
Claim 2
Independent Claim
89 words
A method for training a classifier to classify at least one document which has not been manually annotated with respect to a defined class; performing an operation on data including a retrieval status value associated with the document to generate at least one parameter value; calculating a degree of relevance representing the degree to which said document belongs to said defined class, said degree of relevance being a function of at least the retrieval status value and the parameter value; and training said classifier using said degree of relevance.
Claim 3
Dependent Claim
55 words
The method of claim 1 further comprising the steps of: automatically annotating said at least one document with said calculated degree of relevance to produce at least one automatically annotated document; and wherein said step of training said classifier further comprises the step of training said classifier using said at least one automatically annotated document.
Claim 4
Dependent Claim
43 words
The method of claim 2 wherein said step of training said classifier using said at least one automatically annotated document further comprises the step of: performing a relevance feedback function using said at least one automatically annotated document to produce a classification vector.
Claim 5
Dependent Claim
14 words
The method of claim 1 wherein said defined class is defined by a request.
Claim 6
Dependent Claim
18 words
The method of claim 1 wherein said defined class is defined by at least one manually annotated document.
Claim 7
Dependent Claim
22 words
The method of claim 1 wherein said defined class is defined by both a request and at least one manually annotated document.
Claim 8
Dependent Claim
34 words
The method of claim 1 wherein said degree of relevance is proportional to an estimate of the probability of said at least one document in said first set being relevant to said defined class.
Claim 9
Dependent Claim
11 words
The method of claim 1 wherein the operation includes logistic regression.
Claim 10
Dependent Claim
12 words
The method of claim 1 wherein the data includes logistic training data.
Claim 11
Dependent Claim
16 words
The method of claim 1 wherein the parameter value includes a value of a logistic parameter.
Claim 12
Independent Claim
115 words
A method for producing a classification vector for use in classifying at least one non-manually annotated document with respect to a defined class, said method comprising the steps of: performing an operation on data including a retrieval status value associated with the document to generate at least one parameter value; calculating a degree of relevance representing the degree to which said non-manually annotated document belongs to the defined class, said degree of relevance being a function of at least the retrieval status value and the parameter value; automatically annotating said non-manually annotated document with said degree of relevance to produce a machine annotated document; and performing a relevance feedback function using said machine annotated document.
Claim 13
Independent Claim
115 words
A method for producing a classification vector for use in classifying at least one non-manually annotated document with respect to a defined class, said method comprising the steps of: performing an operation on data including a retrieval status value associated with the document to generate at least one parameter value; calculating a degree of relevance representing the degree to which said non-manually annotated document belongs to the defined class, said degree of relevance being a function of at least the retrieval status value and the parameter value; automatically annotating said non-manually annotated document with said degree of relevance to produce a machine annotated document; and performing a relevance feedback function using said machine annotated document.
Claim 14
Dependent Claim
35 words
The method of claim 11 wherein said step of calculating a degree of relevance further comprises the step of: calculating an estimate of the probability that said non-manually annotated document belongs to the defined class.
Claim 15
Dependent Claim
29 words
The method of claim 11 wherein said step of performing a relevance feedback function further comprises the step of: performing the relevance feedback function using a manually annotated document.
Claim 16
Dependent Claim
11 words
The method of claim 11 wherein the operation includes logistic regression.
Claim 17
Dependent Claim
12 words
The method of claim 11 wherein the data includes logistic training data.
Claim 18
Dependent Claim
16 words
The method of claim 11 wherein the parameter value includes a value of a logistic parameter.
Claim 19
Independent Claim
127 words
An apparatus for training a classifier to classify at least one document which has not been manually annotated with respect to a defined class, said apparatus comprising: an operating processor for performing an operation on data including a retrieval status value associated with the document to generate at least one parameter value; an annotation processor for automatically annotating the document to produce at least one automatically annotated document, said annotation including a degree of relevance representing the degree to which said at least one automatically annotated document belongs to said defined class, said degree of relevance being a function of at least the retrieval status value and the parameter value; and a supervised learning processor for training the classifier using said at least one automatically annotated document.
Claim 20
Independent Claim
127 words
An apparatus for training a classifier to classify at least one document which has not been manually annotated with respect to a defined class, said apparatus comprising: an operating processor for performing an operation on data including a retrieval status value associated with the document to generate at least one parameter value; an annotation processor for automatically annotating the document to produce at least one automatically annotated document, said annotation including a degree of relevance representing the degree to which said at least one automatically annotated document belongs to said defined class, said degree of relevance being a function of at least the retrieval status value and the parameter value; and a supervised learning processor for training the classifier using said at least one automatically annotated document.
Claim 21
Dependent Claim
14 words
The system of claim 17 wherein said defined class is defined by a request.
Claim 22
Dependent Claim
16 words
The system of claim 17 wherein said supervised learning system further comprises: a relevance feedback module.
Claim 23
Dependent Claim
44 words
The system of claim 17 wherein said annotation system further comprises: classification means for calculating a retrieval status value for said at least one document; and means responsive to said classification means for calculating said degree of relevance for said at least one document.
Claim 24
Dependent Claim
11 words
The apparatus of claim 17 wherein the operation includes logistic regression.
Claim 25
Dependent Claim
12 words
The apparatus of claim 17 wherein the data includes logistic training data.
Claim 26
Dependent Claim
16 words
The apparatus of claim 17 wherein the parameter value includes a value of a logistic parameter.
Claim 27
Independent Claim
98 words
An apparatus for training a classifier to classify at least one document which has not been manually annotated with respect to a defined class, said apparatus comprising: means for performing an operation on data including a retrieval status value associated with the document to generate at least one parameter value; means for calculating a degree of relevance representing the degree to which the document belongs to said defined class, said degree of relevance being a function of at least the retrieval status value and the parameter value; and means for training the classifier using said degree of relevance.
Claim 28
Independent Claim
98 words
An apparatus for training a classifier to classify at least one document which has not been manually annotated with respect to a defined class, said apparatus comprising: means for performing an operation on data including a retrieval status value associated with the document to generate at least one parameter value; means for calculating a degree of relevance representing the degree to which the document belongs to said defined class, said degree of relevance being a function of at least the retrieval status value and the parameter value; and means for training the classifier using said degree of relevance.
Claim 29
Dependent Claim
54 words
The apparatus of claim 24 further comprising: annotation means for automatically annotating said at least one document with said calculated degree of relevance to produce at least one automatically annotated document; and wherein said means for training the classifier comprises a relevance feedback mechanism responsive to said annotation means for producing a classification vector.
Claim 30
Dependent Claim
30 words
The apparatus of claim 24 wherein said degree of relevance is proportional to an estimate of the probability of said at least one document being relevant to said defined class.
Claim 31
Dependent Claim
11 words
The apparatus of claim 24 wherein the operation includes logistic regression.
Claim 32
Dependent Claim
12 words
The apparatus of claim 24 wherein the data includes logistic training data.
Claim 33
Dependent Claim
16 words
The apparatus of claim 15 wherein the parameter value includes a value of a logistic parameter.
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USPTO Annuity & Maintenance Windows
| Annuity Stage | Window Opens | Payment Deadline | Surcharge Period Until | Estimated Fee | Status |
|---|---|---|---|---|---|
| 3.5 Years (Year 4) | 2000-10-06 | 2001-04-07 | 2001-10-07 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2004-10-06 | 2005-04-07 | 2005-10-07 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2008-10-06 | 2009-04-07 | 2009-10-07 | $7700.00 | Window Closed / Lapsed |