Apparatus for learning classification model and method and program thereof

• US 20070136220A1
• Filed: 09/22/2006
• Published: 06/14/2007
• Est. Priority Date: 12/08/2005
• Status: Abandoned Application

• Current Assignee: Kabushiki Kaisha Toshiba (Toshiba Corporation)
• Original Assignee: Kabushiki Kaisha Toshiba (Toshiba Corporation)
• Inventors: Sakurai, Shigeaki
• Application Number:
  US11/525,168
• Publication Number:
  US 20070136220A1
• Time in Patent Office: Days
• US Class Current: 706/20
• CPC Class Codes: G06N 20/00 Machine learning

Abstract

A classification model learning apparatus for learning a classification model for extracting a particular event from a text includes an evaluation unit for evaluating the existence or nonexistence of the particular event for a plurality of learning texts having both a text and information on the existence or nonexistence of the particular event by applying an event related expression for evaluating the existence or nonexistence of the particular event to each learning text of the plurality of learning texts, an extracting unit for extracting a learning text in accordance with the existence or nonexistence of the particular event evaluated by the evaluation unit, and a learning unit for learning a classification model based on the learning text extracted by the extracting unit.

Claims

1. A classification model learning apparatus for learning a classification model for extracting a particular event from a text having both a text and information on the existence or nonexistence of the particular event, comprising:

an evaluation unit configured to evaluate the existence or nonexistence of the particular event for a plurality of learning texts having both a text and information on the existence or nonexistence of the particular event by applying an event related expression for evaluating the existence or nonexistence of the particular event to each learning text of the plurality of learning texts;

an extracting unit configured to extract a learning text in accordance with the existence or nonexistence of the particular event evaluated by the evaluation unit; and

a learning unit configured to learn a classification model based on the learning text extracted by the extracting unit.

2. The apparatus according to claim 1, further comprising a storing unit for storing the classification model learnt by the learning unit.

3. The apparatus according to claim 1, further comprising;

a first storing unit configured to a plurality of learning texts each possessing the text and information of existence or nonexistence of the particular event; and

a second storing unit configured to store event related expressions for extracting a particular event from the learning text;

wherein, the evaluation unit evaluates the existence or nonexistence of a particular event for the learning text by applying event related expressions stored in the second storing unit to each of the plurality of learning texts included in a group of learning texts stored in the first storing unit.

4. The apparatus according to claim 1, further comprising a second evaluation unit configured to evaluate the existence or nonexistence of an event for the text by applying a text desired to be evaluated the existence or nonexistence of an event to a classification model learnt by the learning unit.

5. The apparatus according to claim 4, further comprising a storing unit configured to store the text desired to be evaluated the existence or nonexistence of an event by the second evaluation unit.

6. The apparatus according to claim 1, wherein the learning unit learns a classification model of a tree structure form from learning texts including an event and those not including an event by using a text mining method.

7. A classification model learning method for learning a classification model to extract a particular event from a text comprises;

evaluating the existence or nonexistence of a particular event for a plurality of learning texts having both a text and information on the existence or nonexistence of the particular event by applying an event related expression for evaluating the existence or nonexistence of the particular event to each of the plurality of learning texts;

extracting a learning text in accordance with the existence or nonexistence of the particular event evaluated by the event related expression evaluation unit; and

learning a classification model based on the extracted learning text.

8. A program for learning a classification model to extract a particular event from a text comprises;

evaluating the existence or nonexistence of a particular event for a plurality of learning texts having both a text and information on the existence or nonexistence of the particular event by applying an event related expression for evaluating the existence or nonexistence of the particular event to each of the learning texts of the plurality of learning texts;

extracting a learning text in accordance with the existence or nonexistence of the particular event evaluated by the event related expression evaluation unit; and

learning a classification model based on the extracted learning text.