Introducing PoolParty GraphSearch: Cognitive Search based on Graphs

What is PoolParty GraphSearch?

With PoolParty GraphSearch companies can search over a variety of content types and business objects and analyze the data on a more granular level. All content and data repositories that are connected to GraphSearch are annotated with semantic metadata that makes the search, recommendation and analytics operations highly precise. GraphSearch is a front-end application put on top of a semantic infrastructure and an API providing the following features:

  • Ontology-based data access (OBDA)
  • Faceted search including hierarchies
  • Autocomplete combined with context information
  • Custom views on entity-centric and document-centric data
  • Statistical charts for the unified data repositories
  • Plug-in system for recommendation and similarity algorithms

How does it work?

Business users query knowledge assets in GraphSearch along data models. As multiple systems can be connected to GraphSearch, the variety of knowledge models are additionally linked by an ontology layer.

System administrators can define which part of the ontology and corresponding entities in the taxonomy should be used in the GraphSearch front-end application. That way, they define specific views on data. They can also provide multiple search spaces within GraphSearch and enable the user to switch between them. A search space is a customized search configuration over a specific data set. The selected search facets for each search space are derived from the knowledge graph.

GraphSearch can be enhanced with recommendation algorithms. These can work with similarity-based recommendations, or for some use cases, a matchmaking algorithm is more suitable. The research team of Semantic Web Company has a strong focus on machine learning and is continuously extending the library of machine learning algorithms in GraphSearch.

Data analytics functionalities support the business user to derive even more granular insights. Search facets can be combined into statistical charts and display which kind of data is actually available for specific topics.

Agile Data Management and Integration

The implementation of PoolParty GraphSearch is the beginning of consolidating data silos without data migration. Various functional roles have to work together in order to deliver a unified data environment. PoolParty takes the heterogeneous technical backgrounds of the involved professionals into consideration.

Specific user-friendly solutions support the whole knowledge management team in their collaborative work processes:

  • Subject matter experts can define a semantic data layer to describe the meaning of metadata in the PoolParty taxonomy management tool.
  • Knowledge engineers can link separate taxonomies and maintain the knowledge graph in the same tool.
  • Information architects and developers can link various content and data repositories with the semantic metadata via the PoolParty API.
  • Data scientists can adapt embedded machine-learning algorithms to finetune the search, classification, and recommendation results that are mainly derived through the knowledge graph.
  • This semi-automatic knowledge engineering approach sustains that the query results will gradually get more precise and applicable to a continuously growing data environment.
  • On top of that, GraphSearch enables business users to search over data repositories and analyze available information.

Want to learn more?

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