IP Library Granted Patent US 9,727,641
Granted Patent B2
US 9,727,641 · App. 13/870,267 · Granted Aug 8, 2017

Generating a summary based on readability

Inventor: Vinay Deolaikar (Sunnyvale, CA)
Assignee: EntIT Software LLC
G06F17/30719
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Quick Facts
Patent No.
US 9,727,641
App. No.
13/870,267
Granted
Aug 8, 2017
Kind
B2
Abstract

A technique to generate a summary of a set of sentences. Each sentence in the set can be evaluated based on a criterion, such as informativeness of the sentence. The sentences may also be evaluated for readability based on a readability measure. Sentences can be selected for inclusion in the summary based on the evaluations.

Claims (53)

1. A method executed by a computer system, comprising:

extracting a set of sentences from a digital document;

scoring each sentence of the set of sentences using a respective informativeness measure;

scoring each sentence of the set of sentences using a readability measure, wherein the readability measure is based at least in part on one of: a number of words in the sentence, a number of syllables per word, a frequency of a word based on a vocabulary frequency, a frequency of a word based on context, or if words of the sentence appear on a reading list;

selecting selected sentences in the set of sentences based on the readability measures and informativeness measures, wherein the selecting comprises:

determining a subset of sentences from the set of sentences, wherein the sentences in the subset of sentences have informativeness measures greater than a threshold, and

selecting, from the subset of sentences, the selected sentences based on a ranking of the sentences in the subset of sentences according to readability measures of the sentences in the subset of sentences, wherein the selected sentences are the to ranked sentences in the subset of sentences;

identifying a low readability, high informativeness sentence from the set of sentences, wherein:

a low readability sentence includes at least one of fewer syllables per word, fewer words on a reading list, or a lower frequency of words associated with a vocabulary frequency list; and

a high informativeness sentence includes greater similarity to other sentences in the set of sentences and more words having term frequency-inverse document frequency (tf-idf) values indicating that the words are key words;

generating a concatenated sentence by concatenating at least one contextual sentence with the low readability, high informativeness sentence, wherein the concatenated sentence has a higher readability than the low readability, high informativeness sentence; and

generating a readable summary of the digital document, the readable summary including the concatenated sentence and the selected sentences.

2. The method of claim 1 , wherein the contextual sentence comprises a sentence preceding or following the identified low readability, high informativeness sentence in the digital document.

3. The method of claim 1 , wherein the selected sentences are selected using a linear program optimization that maximizes informativeness and readability of the readable summary as measured by the informativeness measures and the readability measures of the sentences in the set of sentences.

4. The method of claim 1 , further comprising:

computing a readability measure of the concatenated sentence; and

including the concatenated sentence in the readable summary in response to the readability measure of the concatenated sentence satisfying a specified criterion.

5. The method of claim 4 , wherein the specified criterion comprises a specified threshold, and including the concatenated sentence in the readable summary is in response to the readability measure of the concatenated sentence exceeding the specified threshold.

6. The method of claim 4 , wherein the specified criterion comprises a threshold amount greater than a readability measure of the low readability, high informativeness sentence, and including the concatenated sentence in the readable summary is in response to the readability measure of the concatenated sentence exceeding the readability measure of the low readability, high informativeness sentence by greater than the threshold amount.

7. A system comprising:

a processor; and

a non-transitory storage medium storing instructions executable on the processor to:

extract a plurality of sentences from a digital document;

identify sentences from the plurality of sentences for inclusion in a summary of the digital document based on a criterion;

evaluate a readability of the identified sentences using respective readability measures, wherein each readability measure assigned to each sentence is based at least in part on one of: a number of words in the sentence, a number of syllables per word, a frequency of a word based on a vocabulary frequency, a frequency of a word based on context, or if words of the sentence appear on a reading list;

select sentences based in part on the evaluated readability of the identified sentences, wherein the selecting comprises:

determining a subset of sentences from the plurality of sentences, wherein the sentences in the subset of sentences have informativeness measures greater than a threshold, and

selecting, from the subset of sentences, the selected sentences based on a ranking of the sentences in the subset of sentences according to readability measures of the sentences in the subset of sentences, wherein the selected sentences are the to ranked sentences in the subset of sentences;

add a low readability, high informativeness sentence to at least one of the selected sentences to create a concatenated sentence, wherein the concatenated sentence has a higher readability than the low readability, high informativeness sentence, and wherein:

a low readability sentence includes at least one of fewer syllables per word, fewer words on a reading list, or a lower frequency of words associated with a vocabulary frequency list; and

a high informativeness sentence includes greater similarity to other sentences in the plurality of sentences and more words having term frequency-inverse document frequency (tf-idf) values indicating that the words are key words.

8. The system of claim 7 , wherein the instructions are executable on the processor to assign an informativeness measure to each sentence of the plurality of sentences, wherein the identifying is based on the informativeness measures.

9. The system of claim 8 , wherein the criterion is informativeness.

10. The system of claim 7 , wherein the instructions are executable on the processor to:

compute a readability measure of the concatenated sentence; and

include the concatenated sentence in the summary in response to the readability measure of the concatenated sentence satisfying a specified criterion.

11. A non-transitory computer readable storage medium storing instructions that when executed cause a computer system to:

assign a respective informativeness measure to each sentence of a set of sentences in a digital document;

assign a respective readability measure to each sentence of the set of sentences;

select selected sentences in the set of sentences based on the readability measures and informativeness measures, wherein the selecting comprises:

determining a subset of sentences from the set of sentences, wherein the sentences in the subset of sentences have informativeness measures greater than a threshold, and

selecting, from the subset of sentences, the selected sentences based on a ranking of the sentences in the subset of sentences according to readability measures of the sentences in the subset of sentences, wherein the selected sentences are the top ranked sentences in the subset of sentences;

identify a low readability, high informativeness sentence from the set of sentences, wherein:

a low readability sentence includes at least one of fewer syllables per word, fewer words on a reading list, or a lower frequency of words associated with a vocabulary frequency list; and

a high informativeness sentence includes greater similarity to other sentences in the set of sentences and more words having term frequency-inverse document frequency (tf-idf) values indicating that the words are key words;

generate a concatenated sentence by concatenating at least one contextual sentence onto the low readability, high informativeness sentence, wherein the concatenated sentence has a higher readability than the low readability, high informativeness sentence; and

generate a summary of the digital document by adding the selected sentences and the concatenated sentence to the summary.

12. The non-transitory computer readable storage medium of claim 11 , wherein the contextual sentence comprises a sentence preceding or following the identified low readability, high informativeness sentence in the digital document.

13. The non-transitory computer readable storage medium of claim 11 , wherein the instructions when executed cause the computer system to:

compute a readability measure of the concatenated sentence; and

include the concatenated sentence in the summary in response to the readability measure of the concatenated sentence satisfying a specified criterion.

14. The non-transitory computer readable storage medium of claim 13 , wherein the specified criterion comprises a specified threshold, and including the concatenated sentence in the summary is in response to the readability measure of the concatenated sentence exceeding the specified threshold.

15. The non-transitory computer readable storage medium of claim 13 , wherein the specified criterion comprises a threshold amount greater than a readability measure of the low readability, high informativeness sentence, and including the concatenated sentence in the summary is in response to the readability measure of the concatenated sentence exceeding the readability measure of the low readability, high informativeness sentence by greater than the threshold amount.

Assignments (8)
RELEASE OF SECURITY INTEREST REEL/FRAME 044183/0577 Recorded Feb 2, 2023
From: JPMORGAN CHASE BANK, N.A.
To: MICRO FOCUS LLC (F/K/A ENTIT SOFTWARE LLC)
Reel/Frame 063560/0001 →
RELEASE OF SECURITY INTEREST REEL/FRAME 044183/0718 Recorded Feb 2, 2023
From: JPMORGAN CHASE BANK, N.A.
To: MICRO FOCUS LLC (F/K/A ENTIT SOFTWARE LLC); BORLAND SOFTWARE CORPORATION; MICRO FOCUS (US), INC.; SERENA SOFTWARE, INC; ATTACHMATE CORPORATION; MICRO FOCUS SOFTWARE INC. (F/K/A NOVELL, INC.); NETIQ CORPORATION
Reel/Frame 062746/0399 →
CHANGE OF NAME Recorded Aug 8, 2019
From: ENTIT SOFTWARE LLC
To: MICRO FOCUS LLC
Reel/Frame 050004/0001 →
SECURITY INTEREST Recorded Oct 11, 2017
From: ENTIT SOFTWARE LLC; ARCSIGHT, LLC
To: JPMORGAN CHASE BANK, N.A.
Reel/Frame 044183/0577 →
SECURITY INTEREST Recorded Oct 11, 2017
From: ATTACHMATE CORPORATION; BORLAND SOFTWARE CORPORATION; NETIQ CORPORATION; MICRO FOCUS (US), INC.; MICRO FOCUS SOFTWARE, INC.; ENTIT SOFTWARE LLC; ARCSIGHT, LLC; SERENA SOFTWARE, INC.
To: JPMORGAN CHASE BANK, N.A.
Reel/Frame 044183/0718 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 9, 2017
From: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
To: ENTIT SOFTWARE LLC
Reel/Frame 042746/0130 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 9, 2015
From: HEWLETT-PACKARD DEVELOPMENT COMPANY, L.P.
To: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
Reel/Frame 037079/0001 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 10, 2013
From: DEOLAIKAR, VINAY
To: HEWLETT-PACKARD DEVELOPMENT COMPANY, L.P.
Reel/Frame 030576/0012 →
Continuity (1)
Related Publication 20140324883A1 · Oct 30, 2014