Match Identity

Match Studio comes preloaded with an index in the form of the OFAC list, a data file obtained from the Office of Foreign Assets Control. The list contains Latin-script names from many countries. This index is used for our Guided Tours. It's also available for you to experiment with and learn more about the features of Match Studio.

To perform a search on the OFAC list, navigate to the Search page, either by selecting Search from the navigation bar at the top of the page, or by selecting Search an Index from the dashboard.  Then, select the OFAC list from the index dropdown menu. Since Match Studio is multilingual, you can enter a name to search in any script; the matches will all be Latin-script.

The index is only created on the bundled instance of Elasticsearch. It isn't uploaded if you are using your own Elasticsearch instance, for instance in locked mode.

Match Studio processes each query in two passes to provide the best combination of speed and accuracy.

The first pass gives the system the speed necessary for high-transaction environments, eliminating values in the index from consideration. The slower second pass re-compares each selected value directly in their original script using enhanced scoring algorithms.

The scores from the first pass are discarded and the match candidates are re-ranked according to the similarity scores returned by the second pass. The match scores for all search terms are combined to generate a match score. All entries with a match score equal to or greater than the display threshold are displayed in a list. Those values that are equal to or greater than the match threshold are displayed with their match score highlighted in green.

The number of scores moved along to the second pass is determined by the window size setting. See Configure index for more information on adjusting this setting.

Single search returns a list of records from your index which are potential matches for a single query, as determined by the calculated match score.

To perform a single search:

Scores higher than the display threshold are displayed in descending order by match score. Results with match values greater than the match threshold are displayed with their match score highlighted in green.

For each result:

Click Export at the top of the results list to download a .csv or .xlsx file of the match results.

Batch search performs multiple searches in a single task, using each record in a file as a query value against the index.

To perform a batch search:

For each line in the batch file, the Batch Results Overview displays the searched data (input) and the index data with which it has the best match score (output). Hover over a result and select the blue arrow on the right to see all results (over the display threshold) for a given query. Match scores above the match threshold will be highlighted in green.

To initiate a new batch search with another dataset, select Upload New Batch.

To initiate a new batch search with the same dataset (and different import settings), select the vertical ellipsis for that batch in the All Batches list and then select Modify & Rerun.

To view the results from another batch, select that batch in the All Batches list.

When comparing two names, a match score will be displayed below the names being compared, along with a table including additional data about the names such as language, script, entity type, and what the names look like after normalization.

Below the match score, you will find the score matrix, a tabular representation of component scores and match types. For more details on how name matching works, see Understanding name match scores.

For Name fields, the score matrix includes:

The tokens from Name 1 are listed down the first column, while the tokens from Name 2 are along the top row. The shaded boxes highlight the token pairs selected during matching that produce the best score. A token pair is a token from Name 1 and its matching token from Name 2. The matchtype column lists the match phenomenon for each token pair. The context score takes into consideration the placement of the token in the score calculation. A penalty is applied if the tokens are out of order. When the tokens line up on the diagonal, they are all in order.

Match Studio compares addresses by comparing the fields within each address. You can enter the address as a single field or as separate fields.

Match Studio optimizes the matching algorithm to the field type. Named entity fields, such as street name, city, and state are matched using an algorithm similar to name matching. Numeric and alphanumeric fields such as house number, postal code, and unit, are matched using numerically-based methods.

The Match Score Computation displays the match matrix for the address fields. Each field in address 1 is compared with each field in address 2, similar to how name tokens are scored.

Use Show Configurations to apply different parameter configurations or edit individual address matching parameters, respectively, similar to name and date matching.

Matching records which include names is a challenging problem because name spellings can differ in so many ways, including simple misspellings, to nicknames, truncations, variable spaces (Mary Ellen, Maryellen), spelling variations, and names written in different languages. Nicknames have a strong cultural component. The terminology itself is problematic because matching implies two things that are the same or equal, but name matching is more about how similar two entities are. Once you have a measure of similarity, you may need additional rules or human analysis to determine if it is a match. It is important to understand these challenges when evaluating name accuracy.

NAME1,NAME1_LANG,NAME2,NAME2_LANG,ENTITY_TYPE,MATCH
Peter Harding,eng,Pete Harding,eng,PERSON,Y
Peter Harding,eng,Harding Peter,eng,PERSON,Y
Peter Harding,,Pete Michael Harding,eng,PERSON,Y
Peter Harding,eng,P. M. Harding,eng,PERSON,N
Peter Harding,eng,Pat Harding,,PERSON,N
Peter Harding,eng,P. B. Harding,eng,PERSON,N
Peter Harding,eng,Pietro Hardin,eng,PERSON,N

123 Fake Street Springfield MO,,123 Fake St Springfield IL,,ADDRESS,N
820 Forest Road,,820 Forrest Rd,,ADDRESS,Y

Creates a new evaluation to run Match against a data set along with a selected configuration, helping you configure Match for your environment.

Before you can run a new evaluation, you must:

Select View Evaluations to display all evaluations performed for a given evaluation data file. Use the Display settings to view the evaluation results for the best threshold, or for a specific threshold. Once you have specified the threshold, you can download the evaluation results for that threshold. Use Threshold report to visualize how the results change as the threshold increases or decreases.

A key feature of Match is that it returns a normalized score between 0 and 1 indicating how similar two names are. This makes integrating Match into existing workflows powerful. However, it leads to the inevitable question: “What threshold should I use?” Without quantitative error analysis, this question is difficult to answer. Match Studio determines the correct value by processing your evaluation data against various thresholds, calculating precision, recall, and F1 for each data type.

The threshold report graphs the precision, recall, and F1 for each threshold value and each data type. As you can see from the graph, the threshold can be adjusted to favor precision or recall. With a high threshold, false positives will be less likely, leading to a higher precision. With a low threshold, false negatives will be less likely, leading to a higher recall. For applications involving border checking, you may be inclined to favor recall to avoid allowing potential threats into a country. Conversely, for Know Your Customer(KYC) applications, leaning your threshold towards precision may be best to reduce false positives. Your choice of threshold should ultimately be based on an analysis of accuracy as a function of threshold for your particular data, as well as your business requirements.

Select Threshold Report from the Options menu for the specific Parameter Configuration.

The threshold report page contains a table listing the Precision, Recall, and F1 values for each data type, along with the threshold value, along with a threshold graph. The threshold is the value which produces the best F1 score.

Figure 1. Threshold report graph

From this page, you can download the following reports as .csv files:

Before searching with Match Studio, you must create an index by uploading a recordset containing your searchable data.

Match Studio imports structured data. Supported file formats are:

For .csv files, the first row must be a header row, containing the names of the fields in the source file. For other file types the key names are the field names. The field names must be unique. For .json and .xml files, multi-value fields are automatically detected. For .csv and .tsv files, multi-valued fields must use a delimiter to separate values (for example, John|Jon|Jonathan).

To create a new index:

As part of the process of creating a new index, you must select the delimiter used to separate fields in the data file.

You will also have to map fields to the columns in the recordset. For more information, see Mapping.

Mapping

Mapping is the process of assigning data types to the columns in your dataset. Each column must have a data type assigned to it.

The mapping process is different depending on the data file format.

Mapping for .csv and .tsv

Review the following when mapping fields to your index:

• Import: Deselect any fields you do not want to import into Match Studio. Fields not imported will not be used for matching, nor will they appear in search results.

• Data Field: The name of the field as it appears in the index file.

• Display Name: In this column, enter the name of the field as you want it to appear in Match Studio.

• Searchable: When this is enabled, the field will be considered when determining a match. When disabled, the field will not be considered when determining a match, but will still appear in search results.

• Grouped Field: Enable this if the data file contains one of the following group field types:

  • Name split into first name, middle name, and last name in separate columns.

  • Date split into day, month, and year

  • Address split into different fields supported by Match Address matching

  • Multi-value grouped fields

  For more information, see Grouped fields.

• Data Type: For fields used for match, provide the data type to tell Match Studio how it should match this field. For more information, see Data types.

  • For fields that use the Name - General (Match) data type, you must also specify the values used for the Name Type (Match) field later in the wizard.

• Multi-Value: Enable this if the data file contains fields with multiple values. Such fields with multiple aliases must separate values with a delimiter. You will be prompted to specify the type of delimiter used later in the wizard.

Mapping for .json and .xml

Enable a field by selecting its corresponding checkbox on the left side of the screen. Only enabled fields will be imported to Match Studio. Disabled fields will not be used for matching, nor will they appear in search results. For each field, the following options are available:

• Display Name: In this column, enter the name of the field as you want it to appear in Match Studio.

• Searchable: When this is enabled, the field will be considered when determining a match. When disabled, the field will not be considered when determining a match, but will still appear in search results.

• Data Type: For fields used for match, provide the data type to tell Match Studio how it should match this field. For more information, see Data types.

  • For fields that use the Name - General (Match) data type, you must also specify the values used for the Name Type (Match) field on the next step of the wizard.

Grouped fields

Match Studio allows for fields to be grouped together when multiple fields in an index map to a single field for searching. For example, if an index contains separate fields for the first name, middle name, and last name, these fields should be mapped to a single full name field for improved matching. The same is true for an index that separates dates into month, day, and year fields.

When mapping an index that contains group fields, you will have to do a bit of setup to create those groups. After the initial mapping step of the wizard, you will reach the Create Field Groups step.

1. Enter a name for the grouped field under Combined Field Name. For example, for a group consisting of first, middle, and last name, you might name the grouped field "Full Name".

   

2. Select the appropriate field type under Combined Field Type. For example, for a group consisting of first, middle, and last name, you should select Name - Person.

3. Select the checkbox next to all items in the Items Available box which should be included in the group.

4. Add.

5. Create Group.

6. Map each field included in the group. For example, for a group consisting of first, middle, and last name, you should map them to Name Field 1, Name Field 2, and Name Field 3, respectively.

   Tip

   If the data contains a title field, it should be indexed as 1 with the other fields indexed as 2, 3, and 4.

   

7. Save.

8. Create.

The Configure Index section allows you to change how your data can be searched and how the results are displayed.

To access the Configure Index section:

Configurations

Use this tab to control the matching behavior of an index, including the weight of each field and the details of how match scores are calculated.

Matching weights

A data field's weight value represents the magnitude of its impact on the final match score. When determining a match, some fields are more important than others. For example, the person name is likely more important in determining a match between two people than the location name. Adjust the weight slider for each field based on its relative importance.

Weight is distributed equally among all fields by default. If a field is missing from a record, that field is ignored and its weight evenly distributed across other fields.

Parameter configuration

Individual name tokens are scored by a number of algorithms. These algorithms can be optimized by modifying parameters, thus changing the final match score. A parameter configuration contains a set of parameter values for one or more specific language pairs and entity types.

Use the Parameter Configuration dropdown menu to set the default parameter configuration for search and batch search. You can use the default parameter configuration (Match-Studio-<version> Default) or create a new parameter configuration. See New parameter configuration for more information on creating a new parameter configuration.

New parameter configurations can also be selected directly from the search page.

Window size

Each Match Studio query is processed in two passes to provide the best combination of speed and accuracy.

1. The first pass is designed to quickly generate a set of candidates for the second pass to consider.

2. The second pass compares every value returned by the first pass against the value in the query and computes a similarity score. Multiple scorers are applied in the second pass, to generate the best possible score.

Window size determines the number of scores moved along to the second pass. Increasing window size improves recall, but results in a slower search.

Window size can also be adjusted directly from the search page.

Match threshold

Once the match score is calculated for all values in the index, those with scores greater than or equal to the match threshold are highlighted in the search results.

Display threshold

Once the match score is calculated for all values in the index, only those with scores greater than or equal to the display threshold are returned in the search results. If you aren't seeing results you expect, try lowering the display threshold value to return more results.

Hover over the Configure tab and select Parameters to view the Parameters page.

Individual name tokens are scored by a number of algorithms. These algorithms can be optimized by modifying configuration parameters, thus changing the final match score. Match Studio provides an easy way to compare and test different parameter settings based on your data.

A parameter configuration contains a set of parameter values for one or more specific language pairs and entity types.

The Configure page contains a list of existing parameter configuration files. You can:

Configuring language pairs and types

When editing a parameter configuration, you can edit parameters for all language pairs and entity types, or for specific language pairs and entity types. Control which pairs and types you are configuring using the tree in the upper-left corner of the View Parameters page.

If you want to edit parameters for a specific language pair and entity type that is not included in the tree, you can add it using the Add New Pair section in the lower-left corner of the View Parameters page.

When you edit a parameter in your parameter configuration, that parameter's value will be inherited by any language-pair-specific or type-specific parameters "below" it in the hierarchy. For example, if you change adjustOneSidedDeletionScores to "1" for all language pairs and types, the adjustOneSidedDeletionScores parameter will also be set to "1" for English to English matching, and that parameter will be marked as "Inherited" when viewing it in the context of that language pair. Select Jump To to go where the value is inherited from.

If you then set that parameter to "1.2" for English to English Person matching, the parameter value will not change for any other language pairs or types. The parameter will be marked as "Local" to indicate that the value was specified for this language pair and type, and not inherited from anywhere. Click Reset to reset the parameter to the value it would inherit from "above" in the hierarchy.

Note

Specific language profiles inherit values from global profiles. If there is a value in a more specific profile, it will not inherit the global value. Lower level (more specific) profiles always take precedence over global values.

Only values set in Match Studio are marked as local. If lower level values are set in the parameters file, those values will take precedence, but won't be marked as local.

Hover over the Configure tab and select Overrides to view the Overrides page. This page allows you to add or remove token pairs that are considered a match regardless of similarity. You can use this list for things like names with unusual nicknames, such as "Margaret" and "Peggy."

An override pair can be one of four types, each of which has a different behavior:

To add a new override set:

To find an override set:

To delete an override set:

To add a token to an existing override set:

To remove a token from an existing override set:

Hover over the Configure tab and select Stop Words to view the Stop Words page. This page allows you to add or remove words that are ignored during string matching so that they do not affect the match score. You can use this list for parts of names or titles that are not significant when determining a match, such as "Mr." or "Prime Minister."

You can create new stop words as prefixes to names. To add a new prefix stop word:

To find a stop word:

To delete a stop word:

For servers without authentication, the following parameters must be set in elasticsearch-<version>/config/elasticsearch.yml:

For servers with basic authentication, the following parameters must be set in elasticsearch-<version>/config/elasticsearch.yml:

For all servers, the following parameters must be set in elasticsearch-<version>/plugins/babel-street-match/bt_root/rlpnc/data/etc/parameter_defs.yaml:

Match Studio requires certain permissions in order to function. Using Match Studio with Match-OS necessitates a bit of extra setup regarding these permissions.

To add a new external server:

After you finish adding the server, Match Studio will automatically switch to it, and it will become visible on the Configure Servers page. Any parameter configurations will automatically be imported into Match Studio. If you are adding a server to Match Studio in locked mode, you will next be asked to link the desired indices from the new server.

If there are external servers added to your instance of Match Studio, you can connect to them at any time by completing the following steps:

While you cannot create new indices within Match Studio in locked mode, you can link indices from the connected server(s). You will be prompted to do this the first time you use Match Studio, but you can also do it at any time afterwards.