Text analytics Solution

Enterprise Search

Search solutions are ubiquitous these days, but modern search systems can take advantage of advanced semantic extraction and name matching capabilities offered by NetOwl to provide key new functionality to end-users.

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Semantic-based Faceted Search

Semantic-based faceted search is a popular search capability to navigate and filter a large amount of text data effectively. It enables discovery of new information as well as search refinement based on how documents are enriched according to a variety of semantic dimensions. When using NetOwl’s entity extraction and event extraction, users can navigate the enterprise data through NetOwl’s built-in semantic concepts such as people, places, organizations, and events.

Faceted search allows users not only to search for a name as a particular type of entity, like “Virginia” as part of a person name, not a place name, but also to discover entities in the facets. For example, while a traditional search would return only a list of documents, faceted search adds capabilities to also show the most frequently mentioned entities mentioned in those documents by type, helping to bring forth key information that was not part of the original document-level search.

Geospatially-oriented Search

NetOwl’s Smart Geotagging capabilities can be leveraged to build a geospatial index of the places mentioned in texts as well as the semantic events or other entities linked to those geo-locatable places. This advanced geotagging capability provides users the ability to search and analyze documents geospatially using a map or other GIS components. NetOwl has been integrated with leading GIS software products like ESRI ArcGIS to automatically populate geospatial indexes from the extracted location entities.

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Graph-based Search

NetOwl’s advanced relationship extraction and event extraction can be used to populate graph databases. The entities and events extracted by NetOwl can be stored as semantically typed “nodes” of a graph. Extracted relationships can then be added as semantically typed “edges” connecting each pair of entity nodes in the relationships. Semantically typed edges can be also added between an event node and the entity nodes that are involved in each specific event describing the role of the entity in the event (e.g., attacker, victim, location, date). This turns interesting queries like “Show me all people affiliated with a particular company” or “Show me all organizations involved in meeting events that took place in Europe” into relatively simple graph patterns to look for in the underlying graph database.

Intelligent Name Search

In some applications, enterprise search functionality is challenged by many different spellings of person and organization names due to misspellings, transliteration variations, nicknames, or other reasons. This makes finding all relevant documents for those entities extremely difficult.

Search applications that leverage NetOwl’s name matching capabilities can present users with possible name variants and allow them to select specific name variants to be included in their searches. The users no longer need to list all the possible name variations manually in their queries.

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Easy Integration with Leading Search Engines

Leading search platforms, including both commercial products and open-source platforms, all support the creation of facet indexes. The facet indexes themselves can be exposed to end-users in any number of ways through end-user facing interfaces. NetOwl’s entity extraction and event extraction results can be easily integrated with these search engines through its REST API and JSON output.