Getting Started
Information that will help you to get started with SPARQUE.
Datasets
Information on creating knowledge graphs from data sources, defining mappings with SPARQUE Language, and loading triples into Sparque's graph database.
Strategies
Information on managing strategies using the Strategy Editor, connecting and configuring building blocks, setting API outputs, adding parameters, and creating stacked strategies for complex search tasks.
- Building Blocks
APIs
Information on managing APIs in SPARQUE Desk to connect strategies to your application.
Evaluation
Information on assessing strategy performance in SPARQUE Desk using testsets and evaluations.
Users
Information on managing user permissions and roles.
Settings
Information on managing your account settings.
Query API
Information on using the Query API. Learn about endpoints, faceted search, response types, and request options.
Miscellaneous
Information on Tuple-notation, encoding, error messages and short-hand notation.
Shopware Extension
The SPARQUE Shopware extension allows you to seamlessly integrate our powerful tools into your Shopware store, providing advanced data analytics and insights.
SPARQUE API Wrapper
Information on the SPARQUE API Wrapper, which streamlines interactions between clients, internal users, and SPARQUE Desk.
SPARQUE Hub
Information on SPARQUE Hub, the front-end component designed to simplify the interactions of clients and internal users with SPARQUE Desk.
Glossary
Discover important terms and concepts used throughout SPARQUE Desk.

Home
Strategies
Information on managing strategies using the Strategy Editor, connecting and configuring building blocks, setting API outputs, adding parameters, and creating stacked strategies for complex search tasks.
Building Blocks
Match
Select Match

Getting Started
Information that will help you to get started with SPARQUE.
Datasets
Information on creating knowledge graphs from data sources, defining mappings with SPARQUE Language, and loading triples into Sparque's graph database.
Strategies
Information on managing strategies using the Strategy Editor, connecting and configuring building blocks, setting API outputs, adding parameters, and creating stacked strategies for complex search tasks.
- Building Blocks
APIs
Information on managing APIs in SPARQUE Desk to connect strategies to your application.
Evaluation
Information on assessing strategy performance in SPARQUE Desk using testsets and evaluations.
Users
Information on managing user permissions and roles.
Settings
Information on managing your account settings.
Query API
Information on using the Query API. Learn about endpoints, faceted search, response types, and request options.
Miscellaneous
Information on Tuple-notation, encoding, error messages and short-hand notation.
Shopware Extension
The SPARQUE Shopware extension allows you to seamlessly integrate our powerful tools into your Shopware store, providing advanced data analytics and insights.
SPARQUE API Wrapper
Information on the SPARQUE API Wrapper, which streamlines interactions between clients, internal users, and SPARQUE Desk.
SPARQUE Hub
Information on SPARQUE Hub, the front-end component designed to simplify the interactions of clients and internal users with SPARQUE Desk.
Glossary
Discover important terms and concepts used throughout SPARQUE Desk.

Select Match

Description

Given list of [OBJ,OBJ] pairs, these are assumed to be the result of a mapping operation, with the first and second columns identifying the Source and Target of such mappings, respectively. This block selects the best (most likely) match for each OBJ in a column, if there are multiple candidates for a match. With the Group on parameter, the column to group on can be selected. All other pairs in the input will be discarded.

Input

MAPPING [OBJ,OBJ]: the candidate matches

Output

RESULT [OBJ,OBJ]: the best match for every item in the Grouped on column.

Parameters

Group on: whether to group on the first column (Source) or the second column (Target).
Method: how to select the best match
- Highest score: for each group, select the match with highest score
- Quadratic-normalized highest score: for each group, consider only the first Normalization window size matches, normalize weights and select the highest score.