Natural language processing optimized for micro content

• US 8,832,092 B2
• Filed: 02/19/2013
• Issued: 09/09/2014
• Est. Priority Date: 02/17/2012
• Status: Active Grant

• Current Assignee: Blazent Incorporated (ServiceNow Incorporated)
• Original Assignee: Bottlenose, Inc. (ServiceNow Incorporated)
• Inventors: Spivack, Nova T., ter Heide, Dominiek
• Primary Examiner(s): Ortiz Ditren, Belix M
• Application Number:
  US13/771,069
• Publication Number:
  US 20130290317A1
• Time in Patent Office: 567 Days
• Field of Search: 707/740, 707/723
• US Class Current: 707/723
• CPC Class Codes: G06F 16/211 Schema design and management
• CPC Class Codes: G06F 16/24522 Translation of natural language queries to structured queries
• CPC Class Codes: G06F 40/205 Parsing
• CPC Class Codes: G06F 40/263 Language identification
• CPC Class Codes: G06F 40/279 Recognition of textual entities
• CPC Class Codes: G06F 40/40 Processing or translation of natural language natural language analysis G06F40/20; semantic analysis G06F40/30
• CPC Class Codes: G06N 20/00 Machine learning

Abstract

A system and a method for microcontent natural language processing are presented. The method comprising steps of receiving a microcontent message from a social networking server, tokenizing the microcontent message into one or more text tokens, detecting the language of the microcontent message and selecting the property dictionary for part-of-speech tag, part-of-speech tagging the microcontent message to identify related pronouns and nouns based on the selected dictionary, and extracting topics form the microcontent messages and assigning confidence values to the topics.

Claims

1. A method for message stream rank comprising:

receiving a message stream including a plurality of messages, wherein each of the messages is associated with metadata attributes;

counting the occurrence of the metadata attributes associated with the messages in the message stream;

generating a list of trending topics based on the occurrences of the metadata attributes;

tracking, by using a plurality of ratio counters, ratio progression as the message stream is received, wherein the plurality of ratio counters each records ratio data of the plurality of messages for a corresponding ratio genre based on the metadata attributes; and

correlating, based on the ratio progression, a trending topic to a plurality of ratio genre to identify one or more ratio trends in the list of trending topics,

wherein a ratio genre includes one or more of gender, ethnicity, or geographical region.

2. The method of claim 1, further comprising:

producing a trend database, wherein each record of the trend database includes a count for a specific condition based on the metadata attributes in which a message occurred in a timeframe.

3. The method of claim 2, further comprising:

presenting list of trending metadata attributes based on the counts of the records of the trend database.

4. The method of claim 1, wherein the metadata attributes include topics, types, hashtags, mentioned people, author, links, geographic segments, ethnicity, or genders.

5. The method of claim 2, wherein a record of the trend database further include a plurality of relative counters, each representing a percentage of how many messages out of a total volume of messages are with a particular metadata attribute, and

a plurality of acceleration counters, each representing an acceleration rate of a particular metadata attribute over a predetermined time period.

6. The method of claim 1, further comprising:

automatically identifying an audience segment correlated with a trending topic based on the messages from users of the audience segment.

7. The method of claim 1, further comprising:

presenting the trending topics as scatters in quadrant scatter plot, wherein a volume of each scatter indicates a metadata attribute of the topics.

8. The method of claim 7, further comprising:

producing an animation of the quadrant scatter plot over a time period to reflect how users'"'"' attentions changes on the trending topics.

9. A system comprising:

a network component configured to receive a microcontent message from a social networking server;

a processor; and

a memory storing instructions which, when executed by the processor, cause the system to perform a process including;

receiving a message stream including a plurality of messages, wherein each of the messages is associated with metadata attributes;

counting the occurrence of the metadata attributes associated with the messages in the message stream;

generating a list of trending topics based on the occurrences of the metadata attributes;

tracking, by using a plurality of ratio counters, ratio progression as the message stream is received, wherein the plurality of ratio counters each records ratio data of the plurality of messages for a corresponding ratio genre based on the metadata attributes; and

correlating, based on the ratio progression, a trending topic to a plurality of ratio genre to identify one or more ratio trends in the list of trending topics,

wherein a ratio genre includes one or more of gender, ethnicity, or geographical region.

10. The system of claim 9, wherein the process further comprises:

producing a trend database, wherein each record of the trend database includes a count for a specific condition based on the metadata attributes in which a message occurred in a timeframe.

11. The system of claim 10, wherein the process further comprises:

presenting list of trending metadata attributes based on the counts of the records of the trend database.

12. The system of claim 9, wherein the metadata attributes include topics, types, hashtags, mentioned people, author, links, geographic segments, ethnicity, or genders.

13. The system of claim 10, wherein a record of the trend database further include a plurality of relative counters, each representing a percentage of how many messages out of a total volume of messages are with a particular metadata attribute, and

a plurality of acceleration counters, each representing an acceleration rate of a particular metadata attribute over a predetermined time period.

14. The system of claim 9, wherein the process further comprises:

automatically identifying an audience segment correlated with a trending topic based on the messages from users of the audience segment.

15. The system of claim 9, wherein the process further comprises:

presenting the trending topics as scatters in quadrant scatter plot, wherein a volume of each scatter indicates a metadata attribute of the topics.

16. The system of claim 15, wherein the process further comprises:

producing an animation of the quadrant scatter plot over a time period to reflect how users'"'"' attentions changes on the trending topics.