System for identifying textual relationships

Patent metadata

Field	Value
Publication number	US-9400778-B2
Application number	US-201113325596-A
Country	US
Kind code	B2
Filing date	Dec 14, 2011
Priority date	Feb 1, 2011
Publication date	Jul 26, 2016
Grant date	Jul 26, 2016

Abstract

A computer-implemented method identifies textual statement relationships. Textual statement pairs including a first and second textual statement are identified, and parsed word group pairs are extracted from first and second textual statements. The parsed word groups are compared, and a parsed word score for each statement pair is calculated. Word vectors for the first and second textual statements are created and compared. A word vector score is calculated based on the comparison of the word vectors for the first and second textual statements. A match score is determined for the textual statement pair, with the match score being representative of at least one of the parsed word score and the word vector score.

First claim

We claim:

1. A computer-implemented method for identifying textual statement relationships, the method comprising:
identifying a textual statement pair that includes a first textual statement and a second textual statement, the first textual statement comprising a first set of words and the second textual statement comprising a second set of words;
removing, by a pre-processing module, non-alpha numeric characters from the first textual statement and the second textual statement;
communicating, by the pre-processing module, the pre-processed first textual statement and second textual statement to a processor;
extracting, by the processor, a first parsed word group from the first textual statement and a second parsed word group from the second textual statement, wherein each parsed word group is a verb-object-preposition (VOP) triple including a verb, an object, and a preposition from each respective textual statement;
comparing, for the textual statement pair, the first parsed word group and the second parsed word group; and
calculating, through the use of the processor, a parsed word score for the textual statement pair, wherein the parsed word score is based on the comparison of the first parsed word group and the second parsed word group;
determining a match score for the textual statement pair based on the parsed word score wherein calculating the parsed word score for the textual statement pair comprises:
extracting, through the use of the processor, a parsed word group pair from the textual statement pair, wherein the parsed word group pair includes a plurality of term pairs, the plurality of term pairs including a verb pair comprising a verb from the VOP triple for the first word group and a verb from the VOP triple for the second word group, an object pair comprising an object from the VOP triple for the first word group and an object from the VOP triple for the second word group, and a preposition pair comprising a preposition from the VOP triple for the first word group and a preposition from the VOP triple for the second word group;
calculating a verb pair sub-score, an object pair sub-score, and a preposition pair sub-score, the calculation of each pair sub-score based on a string similarity, a semantic similarity, and a lexicon similarity between each verb, object, or preposition of the respective verb pair, object pair, or preposition pair; and
wherein the parsed word score is the product of at least one of the verb pair sub-score, the object pair sub-score, and the preposition pair sub-score;

generating, by the processor, a user interface configured to depict one or more first textual statements and one or more second textual statements along with one or more match indicators that visually indicate a match between one or more of the first textual statements and one or more of the second textual statements;
communicating, by a graphics processor in communication with the processor and a display the generated user interface to thereby cause the display to visually display the generated user interface.

2. The method of claim 1 , wherein the first textual statement is selected from a first set of textual statements, and wherein the second textual statement is selected from a second set of textual statements.

3. The method of claim 2 , wherein the first set of textual statement is a set of requirement statements and the second set of textual statements is a set of process model capabilities.

4. The method of claim 3 , wherein match scores are determined for a plurality of textual statement pairs, each textual statement pair including one requirement statement from the set of requirement statements and one capability statement from the set of process model capabilities.

5. The method of claim 4 , further comprising visually displaying, for each requirement statement, a list of capability statements included in textual statement pairs that also include the requirement statement.

6. The method of claim 5 , wherein each list of the capability statements is ordered based on the match score for the textual statement pair that includes the requirement statement and the respective capability statement.

7. The method of claim 1 , wherein
calculating the verb pair sub-score, the object pair sub-score, and the preposition pair sub-score comprises:
calculating a string similarity score, the string similarity score based on a string comparison of a base word of each verb, object, or preposition of the verb pair, object pair, or preposition pair, respectively;
calculating a semantic similarity score, the semantic similarity score based on a semantic relationship between each verb, object, or preposition of the verb pair, object pair, or preposition pair;
calculating a lexicon similarity score, the lexicon similarity score based on relative positions in a taxonomy of each verb, object, or preposition of the verb pair, object pair, or preposition pair; and
comparing the string similarity score, the semantic similarity score, and the lexicon similarity, wherein the pair sub-score is based on at least one of the string similarity score, the semantic similarity score, and the lexicon similarity score; and

wherein the parsed word score is the product of at least one of the verb pair sub-score, the object pair sub-score, and the preposition pair sub-score.

8. The method of claim 1 , wherein
calculating the verb pair sub-score, the object pair sub-score, and the preposition pair sub-score comprises:
calculating a string similarity score, the string similarity score based on a string comparison of a base word of each verb, object, or preposition of the verb pair, object pair, or preposition pair, respectively;
calculating a semantic similarity score and a lexicon similarity score when the string similarity score does not indicate a string match of a base word of each verb, object, or preposition of the verb pair, object pair, or preposition pair, respectively;
comparing the semantic similarity score and the lexicon similarity score when the string similarity score does not indicate a string match of a base word of each verb, object, or preposition of the verb pair, object pair, or preposition pair, respectively;
wherein the sub-score is the string similarity score when the string similarity score indicates a string comparison of a base word of each verb, object, or preposition of the verb pair, object pair, or preposition pair respectively; and
wherein the sub-score is a maximum of the semantic similarity score and the lexicon similarity score when the string similarity score does not indicate a string match of a base word of each verb, object, or preposition of the verb pair, object pair, or preposition pair respectively; and

wherein the parsed word score is the product of at least one of the verb pair sub-score, the object pair sub-score, and the preposition pair sub-score.

9. The method of claim 1 , wherein calculating the verb pair sub-score, the object pair sub-score, and the preposition pair sub-score comprises:
calculating a string similarity score, the string similarity score based on a string comparison of a base word of each verb, object, or preposition of the verb pair, object pair, or preposition pair, respectively; and
using the string similarity score as the pair sub-score when the string similarity score indicates a string comparison of a base word of each verb, object, or preposition of the verb pair, object pair, or preposition pair, respectively.

10. The method of claim 1 , further comprising:
creating a first word vector based on the first set of words;
creating a second word vector based on the second set of words;
comparing, for the textual statement pair, the first word vecto

Assignees

• Ramani Senthil
• Mujumdar Malharrao
• Vaidhyanathan Venkatraman
• Nuggehally Reshma
• Verma Kunal
• Vasquez Reymonrod
• Shivaram Santhosh Kumar
• Subramanian Venkatesh
• Dayal Sumit
• Kass Alex
• Accenture Global Services Ltd

Inventors

• Ramani Senthil
• Mujumdar Malharrao
• Vaidhyanathan Venkatraman
• Nuggehally Reshma
• Verma Kunal
• Vasquez Reymonrod
• Shivaram Santhosh Kumar
• Subramanian Venkatesh
• Dayal Sumit
• Kass Alex

Classifications

• G06F40/247

  Thesauruses; Synonyms · CPC title

• G06F40/268 Primary

  Morphological analysis · CPC title

• G06F40/30

  Semantic analysis · CPC title

• G06F17/2785

  Physics · mapped topic

• G06F17/2795

  Physics · mapped topic