WO2006052046A1 - Apparatus and method for classifying e-mail using decision tree - Google Patents
Apparatus and method for classifying e-mail using decision tree Download PDFInfo
- Publication number
- WO2006052046A1 WO2006052046A1 PCT/KR2004/003538 KR2004003538W WO2006052046A1 WO 2006052046 A1 WO2006052046 A1 WO 2006052046A1 KR 2004003538 W KR2004003538 W KR 2004003538W WO 2006052046 A1 WO2006052046 A1 WO 2006052046A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- mails
- decision tree
- classifying
- storing
- Prior art date
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/10—Office automation; Time management
- G06Q10/107—Computer-aided management of electronic mailing [e-mailing]
Definitions
- the present invention relates to an apparatus and method for classifying an e-mail by using a decision tree; and, more particularly, to an e-mail classifying apparatus based on a decision tree that generates a decision tree based on information about a folder created by a client and the e-mail stored therein, and classifies an e-mail transmitted from the outside based on the decision tree, and a method thereof.
- a decision tree learning technique is a representative learning technique of an inductive inference.
- the decision tree learning technique is commonly used for classification.
- the decision tree learning technique has a characteristic that it has robustness to noise.
- the decision tree includes a plurality of nodes.
- the node on top in the decision tree is called a root node.
- the decision tree is grown up by pruning child nodes out of the root node.
- the node at the bottom of the decision tree is called a leaf node.
- the iteration of pruning stops at the leaf node.
- the steps from the root node to the leaf node are called depth.
- the decision tree learning technique forms a tree- type classifying model based on collected data and classifies received data according to the classifying model. Therefore, the decision tree learning technique is regarded as an excellent automatic classifying method.
- Conventional automatic e-mail classifying methods classify e-mails based on an assumption-and-decision method. That is, they classify the e-mails according to predetermined rules defined based on sender address, title and contents of an e-mail. Once the rules are defined that if a classifier, such as the sender address, title and contents, has a specific value, the e-mail is automatically classified into a specific folder, the e-mails received after the definition of the rules are classified according to the rules.
- the rule must be defined by carefully considering other variables except e-mail address to transfer an e-mail sent out from one e-mail address to different folders.
- the rules may not be applied effectively according to the characteristics of an added variable.
- an object of the present invention to provide an e-mail classifying apparatus and method based on a decision tree that can classify many e-mails simply and rapidly based on the decision tree by generating the decision tree based on information about a folder created by a client and an e-mail stored therein and classifying the e-mail based on the decision tree.
- an apparatus for classifying e-mails using a decision tree including: a client e- mail storing unit for storing e-mails according to each folder; a decision tree generating unit for generating a decision tree based on information about e-mails stored according to folders in the client e-mail storing unit; a received e-mail processing unit for receiving e-mails; an e-mail storing unit for storing the e-mails received in the receiving e-mail processing unit; an e-mail classifying unit for classifying the e-mails stored in the e-mail storing unit based on the decision tree; an e-mail transmitting unit for transmitting the classified e-mail to the client e-mail storing unit; and a controlling unit for controlling the units to generate the decision tree based on the e-mails stored in the client e-mail storing unit and to classify the e-mail transmitted from outside based on the decision
- a method for classifying e- mails based on a decision tree including the steps of: a) generating a decision tree based on information about folders created by a client and e-mails stored in the folders; b) temporally storing e-mails transmitted from outside in an e-mail storing means; c) comparing correlation between the folders and the stored e- mail based on the decision tree; d) determining a folder having highest correlation with the stored e-mail based on the comparison; and e) storing the e-mail in the above determined folder.
- the present invention can classify a great deal of electric mails (e-mails) simply and rapidly by generating a decision tree based on folders created by a client and information that e-mails stored therein, and classifying the e-mails transmitted from the outside based on the created decision tree. Also, the present invention can provide differentiated additional service to clients by analyzing an e-mail classification pattern of a client.
- Fig. 1 is a block diagram showing an e-mail classifying apparatus using a decision tree in accordance with a preferred embodiment of the present invention
- Fig. 2 is a diagram showing e-mails of each folder in a client E-mail storing unit in accordance with a preferred embodiment of the present invention
- Fig. 3 is a flowchart describing a method for generating a decision tree in accordance with a preferred embodiment of the present invention
- Fig. 4 shows a decision tree in accordance with a preferred embodiment of the present invention
- Fig. 5 is a flowchart describing a method for classifying e-mails based on a decision tree in accordance with a preferred embodiment of the present invention.
- FIG. 1 is a block diagram showing an e-mail classifying apparatus using a decision tree in accordance with a preferred embodiment of the present invention.
- the apparatus for classifying e- mail using the decision tree includes a client e-mail storing unit 10 for storing an e-mail according to a folder; a decision tree generating unit 11 for generating a decision tree based on information about the e-mail stored according to a folder in the client mail storing unit 10; a received e-mail processing unit 15 for receiving e-mails from web-sites; an e-mail storing unit 16 for storing the e-mail received in the received e-mail storing unit 15; an e-mail classifying unit 17 for classifying e-mails stored in the e-mail storing unit 16 by using the decision tree; an e-mail transmitting unit 18 for transmitting the classified e-mail in the e-mail classifying unit 17 to the client e-mail storing unit 10; and a controlling unit 12 for controlling the aforementioned units for generating the decision tree based on information about the folder generated by the client and about the e-mail stored in the generated folder
- the apparatus for classifying e-mail using the decision tree further includes a sent e-mail processing unit 14 for sending an e-mail from the client to external devices .
- various folders are created by the client having an e- mail account "CMS" for classifying received e-mails and storing the classified e-mails.
- CMS e- mail account
- the client e-mail storing unit 10 of the "CMS" client is first divided into an "In Box” folder and an "Out box” folder.
- the "In Box” folder is further divided to a "company mail” folder, an "ad mail” folder, an "external mail” folder, and an "important mail” folder.
- the "company mail” folder is also divided according to departments such as a "my department (dept.)” folder and an “other dept” folder.
- the "my dept” folder is divided to a "past work” folder and a "work of 2004" folder.
- the "work of 2004" folder may store e- mails of "AOOlQmajor.etri. re. kr, 2003" and
- "A002@major.etri.re.kr, 2002" represent that the e-mails are received e-mails, which are transmitted from a company “etri” and same departments “major”, and they are e-mails received before the year 2004. Also, e-mails having properties of "A001@major.etri.re.kr, 2004" and “A002@major.etri.re. kr, 2004" are stored in the "work of 2004" folder. That is, the properties of e-mails stored in the "work of 2004" folder represent that they are e-mails from the company "etri", and the same department "major” and received in 2004.
- e-mails "A003@etri.re. kr" and “A004@etri. re. kr” are stored in the "other department” folder. The e-mails
- an e-mail of "A005@kaist.ac.kr” may be stored in the "external mail” folder.
- the email "A005@kaist.ac.kr” represents that the e-mail is a received e-mail and transmitted from "kaist.”
- an e-mail "A005@kaist.ac.kr, inquiry” may be stored in the "important mail” folder.
- inquiry represents that the e-mail is a received e-mail and an important (inquiry) e-mail and it is transmitted from "kaist.”
- the client can effectively manage the received e-mails and easily recognize that the e-mail of the folder is received.
- Fig. 3 is a flowchart describing a method for generating a decision tree in accordance with a preferred embodiment of the present invention.
- folders are created by a client in a client e-mail storing unit 10 at step S200.
- E-mails are transferred to the folders at step S201.
- a decision tree is generated based on the folders and e-mails stored in corresponding folders at step S203.
- the generated decision tree is transferred to the controlling unit 12 at step S204.
- Fig. 4 shows a decision tree in accordance with a preferred embodiment of the present invention.
- the decision tree has a classification pattern classifying the e-mail to a "mail server D class" and a "title” based on whether it is a mail of a company, e.g., etri.re.kr, beginning from a "mail server C class.”
- the "mail server D class” is further divided into “period” and "other department” based on whether the department, for example, major.etri.re. kr.
- the "period” also has another classifying pattern classifying the email into "past work” and "work of 2004” according to the year of e-mail reception.
- the "title” also has another classifying pattern classifying the email to "important mails” and “casual mails” according to significance, e.g., inquiry.
- the preferred embodiment of the present invention is explained based on the decision tree having a depth of three steps.
- the depth may be deeper and the depth is not limit the scope of the present invention.
- Fig. 5 is a flowchart describing a method for classifying e-mails based on a decision tree in accordance with a preferred embodiment of the present invention.
- the decision tree is generated through the process shown in Fig. 3.
- the e-mails received from the outside are temporally stored in the e-mail storing unit 16 at steps S310 and S302. Correlation between the received e-mail and the folders is analyzed by calling the decision tree at steps S303 and S304. That is, the received e-mail and the decision tree are compared.
- one of folders is determined as a folder for storing the received e-mail and transferred to the client e-mail storing unit 10 to store the e-mail in the folder at steps S305 and S306.
- the folder storing the e-mail is a folder turned out to have the highest correlation in the comparison.
- step S307 the temporally stored e-mail is deleted out of the e-mail storing unit 16.
Abstract
Description
Claims
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US11/719,079 US20090125528A1 (en) | 2004-11-10 | 2004-12-30 | Apparatus and Method For Classifying E-Mail Using Decision Tree |
Applications Claiming Priority (4)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
KR20040091585 | 2004-11-10 | ||
KR10-2004-0091585 | 2004-11-10 | ||
KR10-2004-0104908 | 2004-12-13 | ||
KR1020040104908A KR100581084B1 (en) | 2004-11-10 | 2004-12-13 | Apparatus and method for classifying e-mail using decision tree |
Publications (1)
Publication Number | Publication Date |
---|---|
WO2006052046A1 true WO2006052046A1 (en) | 2006-05-18 |
Family
ID=36336695
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/KR2004/003538 WO2006052046A1 (en) | 2004-11-10 | 2004-12-30 | Apparatus and method for classifying e-mail using decision tree |
Country Status (1)
Country | Link |
---|---|
WO (1) | WO2006052046A1 (en) |
Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
KR20000063974A (en) * | 2000-08-14 | 2000-11-06 | 박민우 | Integral E-mail management method based on Web |
KR20000071732A (en) * | 1999-04-20 | 2000-11-25 | 이데이 노부유끼 | Data reproducing apparatus and method |
US20040090457A1 (en) * | 2002-11-12 | 2004-05-13 | Microsoft Corporation | System and apparatus for sending complete responses to truncated electronic mail messages on a mobile device |
-
2004
- 2004-12-30 WO PCT/KR2004/003538 patent/WO2006052046A1/en active Application Filing
Patent Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
KR20000071732A (en) * | 1999-04-20 | 2000-11-25 | 이데이 노부유끼 | Data reproducing apparatus and method |
KR20000063974A (en) * | 2000-08-14 | 2000-11-06 | 박민우 | Integral E-mail management method based on Web |
US20040090457A1 (en) * | 2002-11-12 | 2004-05-13 | Microsoft Corporation | System and apparatus for sending complete responses to truncated electronic mail messages on a mobile device |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US6718367B1 (en) | Filter for modeling system and method for handling and routing of text-based asynchronous communications | |
TWI390420B (en) | Method, system and computer program product to determine a user specific relevance score of a message within a messaging system | |
US8230032B2 (en) | Message data management | |
CN1517928B (en) | Technology truss for allowing integrated anti-peddle information | |
US20110055264A1 (en) | Data mining organization communications | |
WO2004030296A1 (en) | Method and devices for prioritizing electronic messages | |
CN104508691A (en) | Multi-tiered approach to e-mail prioritization | |
US20150039703A1 (en) | Systems and methods for electronic message prioritization | |
US20090125528A1 (en) | Apparatus and Method For Classifying E-Mail Using Decision Tree | |
US11270316B2 (en) | Systems, methods, and apparatuses for implementing automatic entry of customer relationship management (CRM) data into a CRM database system | |
US20040019850A1 (en) | Constraint-optimization system and method for document component layout generation | |
US20100235367A1 (en) | Classification of electronic messages based on content | |
US9699129B1 (en) | System and method for increasing email productivity | |
CN1742266A (en) | Adaptive junk message filtering system | |
CN1508718A (en) | Interface for user of person to contact | |
EP3711007A1 (en) | Ai system to determine actionable intent | |
US7000178B2 (en) | Electronic document classification system | |
JP4802523B2 (en) | Electronic message analysis apparatus and method | |
CN111401988A (en) | Product configuration demand response system based on semantics and order generation method | |
WO2006052046A1 (en) | Apparatus and method for classifying e-mail using decision tree | |
CN112434140B (en) | Reply information processing method and system | |
US20050096922A1 (en) | Approximating hierarchies | |
Al-Alwani | A novel email response algorithm for email management systems | |
JP2001256251A (en) | Device and system for automatically evaluating document information | |
CN115604669B (en) | Short message sending queuing system |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
AK | Designated states |
Kind code of ref document: A1 Designated state(s): AE AG AL AM AT AU AZ BA BB BG BR BW BY BZ CA CH CN CO CR CU CZ DE DK DM DZ EC EE EG ES FI GB GD GE GH GM HR HU ID IL IN IS JP KE KG KP KZ LC LK LR LS LT LU LV MA MD MG MK MN MW MX MZ NA NI NO NZ OM PG PH PL PT RO RU SC SD SE SG SK SL SM SY TJ TM TN TR TT TZ UA UG US UZ VC VN YU ZA ZM ZW |
|
AL | Designated countries for regional patents |
Kind code of ref document: A1 Designated state(s): BW GH GM KE LS MW MZ NA SD SL SZ TZ UG ZM ZW AM AZ BY KG KZ MD RU TJ TM AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HU IE IS IT LT LU MC NL PL PT RO SE SI SK TR BF BJ CF CG CI CM GA GN GQ GW ML MR NE SN TD TG |
|
121 | Ep: the epo has been informed by wipo that ep was designated in this application | ||
WWE | Wipo information: entry into national phase |
Ref document number: 11719079 Country of ref document: US |
|
122 | Ep: pct application non-entry in european phase |
Ref document number: 04808666 Country of ref document: EP Kind code of ref document: A1 |