SYSTEMS AND METHODS FOR DETERMINING ATYPICAL LANGUAGE

• US 20140344279A1
• Filed: 03/07/2014
• Published: 11/20/2014
• Est. Priority Date: 09/30/2011
• Status: Active Grant

• Current Assignee: Thomson Reuters Enterprise Centre GmbH (The Woodbridge Co. Ltd.)
• Original Assignee: Thomson Reuters Global Resources
• Inventors: Sisk, Jacob, Al-Kofahi, Khalid, SHAH, Sameena, Dorr, Dietmar
• Granted Patent: US 9,690,849 B2
• Time in Patent Office: Days
• US Class Current: 707/738
• CPC Class Codes: G06F 16/335 Filtering based on additional data, e.g. user or group profiles filtering in web context G06F16/9535, G06F16/9536
• CPC Class Codes: G06F 16/35 Clustering; Classification
• CPC Class Codes: G06F 40/242 Dictionaries
• CPC Class Codes: G06F 40/284 Lexical analysis, e.g. tokenisation or collocates
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 50/18 Legal services

Abstract

A method includes analyzing a cluster of conceptually-related portions of text to develop a model and calculating a novelty measurement between a first identified conceptually-related portion of text and the model. The method further includes transmitting a second identified conceptually-related portion of text and a score associated with the novelty measurement from a server to an access device via a signal. Another method includes determining at least two corpora of conceptually-related portions of text. The method also includes calculating a common neighbors similarity measurement between the at least two corpora of conceptually-related portions of text and if the common neighbors similarity measurement exceeds a threshold, merging the at least two corpora of conceptually-related portions of text into a cluster or if the common neighbors similarity measurement does not exceed a threshold, maintaining a non-merge of the at least two corpora of conceptually-related portions of text.

Claims

1. A computer-implemented method comprising:

analyzing a cluster of conceptually-related portions of text to develop a model;

calculating a novelty measurement between a first identified conceptually-related portion of text and the model; and

transmitting a second identified conceptually-related portion of text and a score associated with the novelty measurement.

2. The method of claim 1 further comprising:

determining at least two corpora of conceptually-related portions of text; and

calculating a common neighbors similarity measurement between the at least two corpora of conceptually-related portions of text and;

if the common neighbors similarity measurement exceeds a threshold, merging the at least two corpora of conceptually-related portions of text into a cluster;

or

if the common neighbors similarity measurement does not exceed a threshold, maintaining a non-merge of the at least two corpora of conceptually-related portions of text.

3. The method of claim 1 further comprising receiving a first identified conceptually-related portion of text from a third party.

4. A system comprising:

a processor,

a memory coupled to the processor;

a processing program stored in the memory for execution by the processor, the processing program comprising;

an analysis module, the analysis module configured to analyze a cluster of conceptually-related portions of text to develop a model;

a novelty module, the novelty module configured to calculate a novelty measurement between a first identified conceptually-related portion of text and the model; and

a transmission module, the transmission module configured to transmit a second identified conceptually-related portion of text and a score associated with the novelty measurement.

5. The system of claim 4 further comprises a common neighbors module, the common neighbors module configured to:

determine at least two corpora of conceptually-related portions of text; and

calculate a common neighbors similarity measurement between the at least two corpora of conceptually-related portions of text and;

if the common neighbors similarity measurement exceeds a threshold, merge the at least two corpora of conceptually-related portions of text into a cluster, or

if the common neighbors similarity measurement does not exceed a threshold, maintain a non-merge of the at least two corpora of conceptually-related portions of text.

6. The system of claim 4 wherein the novelty module is further configured to receive a first identified conceptually-related portion of text from a third party.