Synaptica: AutoMatch Tool Overview New Version 7.1 Feature- Due out: July 2009 by: [email_address] (Synaptica Product Manager) [email_address] (Business Development Manager, Synaptica and Taxonomy Services)

What Does the AutoMatch Tool Do? The AutoMatch tool works with any 2 object classes (vocabularies) loaded into a Synaptica system. To begin the process, the user selects 2 object classes and the desired match types and starts the process). Upon completion, the user can select one of the following: 1. Download the results to be edited with Excel. The Excel file can then be imported into Synaptica to create the relationships between terms in the 2 object classes. The results can be reviewed on screen. Undesirable matches can be deleted, then the list can be submitted directly to the import tool to create the relationships between terms in the 2 object classes. The Following Screens provide an overview of the process

The AutoMatch tool works with any 2 object classes (vocabularies) loaded into a Synaptica system. To begin the process, the user selects 2 object classes and the desired match types and starts the process). Upon completion, the user can select one of the following:

1. Download the results to be edited with Excel. The Excel file can then be imported into Synaptica to create the relationships between terms in the 2 object classes.

The results can be reviewed on screen. Undesirable matches can be deleted, then the list can be submitted directly to the import tool to create the relationships between terms in the 2 object classes.

The Following Screens provide an overview of the process

Select Two Object Classes (Vocabularies) Select Object Classes from existing vocabularies loaded in system

Select Mapping Types (see next slides for definitions) and Relationship Type Select Relationship Type for Term Matching

Select Mapping Types (see next slides for definitions) and Relationship Type Select Match Types to Display

AutoMatch - Explanation of 5 Match Types 1 - Exact Match This will match terms that are considered to be exact matches. Case is ignored and diacritical characters are removed before the terms are compared. It is considered to be the most relevant match. Examples: First Object Class Second Object Class Applied Zoology Applied Zoology applied zoology applied zoology Cafe Café 2 - Keywords Match This will match terms where all words are the same, but the order is different. Case is ignored and diacritical characters are removed before the terms are compared. Examples: First Object Class Second Object Class Applied Zoology Zoology Applied applied zoology zoology (applied)

1 - Exact Match

This will match terms that are considered to be exact matches. Case is ignored and diacritical characters are removed before the terms are compared. It is considered to be the most relevant match.

Examples:

First Object Class Second Object Class

Applied Zoology Applied Zoology

applied zoology applied zoology

Cafe Café

2 - Keywords Match

This will match terms where all words are the same, but the order is different. Case is ignored and diacritical characters are removed before the terms are compared.

Examples:

First Object Class Second Object Class

Applied Zoology Zoology Applied

applied zoology zoology (applied)

AutoMatch - Explanation of 5 Match Types 3 - Keywords Soundex Match This is an extension of the Keywords Match. The words for each term are sorted alphabetically (just like the Keywords Match), then each word is converted to a Soundex code before matching. Soundex converts an alpha string to a four-character code to find similar-sounding words or names. Examples: First Object Class Second Object Class James Smith James Smyth James Smith Smyth James Plant and Animal Plants and Animals

3 - Keywords Soundex Match

This is an extension of the Keywords Match. The words for each term are sorted alphabetically (just like the Keywords Match), then each word is converted to a Soundex code before matching. Soundex converts an alpha string to a four-character code to find similar-sounding words or names.

Examples:

First Object Class Second Object Class

James Smith James Smyth

James Smith Smyth James

Plant and Animal Plants and Animals

4 - Multiple word Smart Search This uses each term in the first Object Class (that contain multiple words) to run Synaptica "Smart" searches in the second Object Class. Case is ignored and diacritical characters are removed from terms in both Object Classes. This can produce many results and can be a time consuming process for large Object Classes. Examples: First Object Class Second Object Class Applied Zoology zoology (applied) Applied Zoology Applied Zoology Studies Applied Zoo zoology (applied) Applied Zoo Applied Zoology Studies AutoMatch - Explanation of 5 Match Types

4 - Multiple word Smart Search

This uses each term in the first Object Class (that contain multiple words) to run Synaptica "Smart" searches in the second Object Class. Case is ignored and diacritical characters are removed from terms in both Object Classes. This can produce many results and can be a time consuming process for large Object Classes.

Examples:

First Object Class Second Object Class

Applied Zoology zoology (applied)

Applied Zoology Applied Zoology Studies

Applied Zoo zoology (applied)

Applied Zoo Applied Zoology Studies

5 - Single word Smart Search This uses each term in the first Object Class (that contain single words) to run Synaptica "Smart" searches in the second Object Class. Case is ignored and diacritical characters are removed from terms in both Object Classes. This can produce many results and can be a time consuming process for large Object Classes. It is considered to be the least relevant match. Examples: First Object Class Second Object Class Zoology Applied Zoology Zoology zoology (applied) Zoology Applied Zoology Studies Zoo Applied Zoology Zoo zoology (applied) Zoo Applied Zoology Studies AutoMatch - Explanation of 5 Match Types

5 - Single word Smart Search

This uses each term in the first Object Class (that contain single words) to run Synaptica "Smart" searches in the second Object Class. Case is ignored and diacritical characters are removed from terms in both Object Classes. This can produce many results and can be a time consuming process for large Object Classes. It is considered to be the least relevant match.

Examples:

First Object Class Second Object Class

Zoology Applied Zoology

Zoology zoology (applied)

Zoology Applied Zoology Studies

Zoo Applied Zoology

Zoo zoology (applied)

Zoo Applied Zoology Studies

Review Results Summary Download Matches to edit offline and re-import or Review and Apply Matches online via the browser

Displaying Match Types 1. Each term name is displayed as a link so one may enter the item summary for any term and edit the term directly. 2. Each term will display an "Existing Relationship Count" that shows the number of relationships from that term to terms in the other object class. 3. Match result display can be adjusted to: Display all matches Display matches except where match already exists Display matches with no existing match from first to second object class

1. Each term name is displayed as a link so one may enter the item summary for any term and edit the term directly.

2. Each term will display an "Existing Relationship Count" that shows the number of relationships from that term to terms in the other object class.

3. Match result display can be adjusted to:

Display all matches

Display matches except where match already exists

Display matches with no existing match from first to second object class

Displaying Match Types The first option displays all matches. The second option will hide matches where relationship already exists. The third option has functionality that will only show matches where the existing relationship count is 0. This means that the term from the first object class has no relationships to the second object class.

The first option displays all matches.

The second option will hide matches where relationship already exists.

The third option has functionality that will only show matches where the existing relationship count is 0. This means that the term from the first object class has no relationships to the second object class.

Reviewing Matches Online Remove undesired matches by clicking delete [del]

Reviewing Matches Online Synonym matching allows for matching between “preferred” and “non-preferred” terms, finding matches using synonyms that might otherwise be missed. Preferred Terms will be linked For ‘Match occurs on Synonym

Please contact me with any additional questions. Daniela Barbosa Synaptica and Taxonomy Services Business Development [email_address] 415.321.9502 www.synaptica.com