Intrafind Software AG profile
IntraFind is a specialist in the field of enterprise search, tagging, metadata generation and classification of unstructured and structured enterprise data. The company provides its customers with a rich portfolio of software products for on-premise as well as cloud usage. We also provide customer-specific solutions and consulting based on Lucene and Solr.
IntraFind’s team of experts is focused only on information mining and searching. With more than 10 years of experience in enterprise search we provide excellent know-how and market expertise.
The excellence of our products is proven by the list of renowned customers such as Audi, Bosch, the European Patent Office, Krauss-Maffei-Wegmann, Merck, Signal Iduna, Voith, Volkswagen, Webasto and ZEIT ONLINE.
iFinder Enterprise Search
iFinder, based on Lucene, is IntraFind´s basic product for searching structured and unstructured data.
The iFinder basic product includes a user-friendly, scalable and high-performance full-text search that supports the user during the entire search process.
iFinder comes with a bunch of built-in connectors to data sources such as various file systems, database systems, web pages, intranets, MS Exchange and Lotus Notes, SharePoint, wikis, SAP, archive and document management systems. The connector framework can be easily customized for connecting almost any other document source.
From the user’s perspective the biggest advantage of searching with iFinder is that he can access various content sources and systems via one unique user interface with full inclusion of access rights.
iFinder Enhancement Modules
In order to improve the relevance of the search results iFinder can easily be enhanced by modules for linguistics, similarity search, semantic search, thesaurus- or taxonomy-based search, cross-lingual search, entity recognition, content-related document classification, text clustering, tagging and knowledge maps.
Knowledge Map—a sample for a Search-Based Application
IntraFind´s Knowledge Map offers a user-friendly surface. All available data are clearly visualized in a "360 degree view" and can be quickly and easily narrowed to the desired result document just by a couple of mouse clicks without a need to enter one single search term.
Each Knowledge Map is generated out of metadata which are either already part of the single documents or pieces of information (e.g. document properties) or which are automatically recognized via text mining methods (Named Entity Recognition, Text Classification, Pattern Matching, Tagging). By this, every employee can filter the data pool by specific entities which helps to increase his efficiency as an information worker.
By applying our product TopicFinder for automated text classification you are able to automatically capture and use additional information, which goes beyond the pure word-based content of documents. TopicFinder combines several supervised and unsupervised learning methods. The customer´s use case defines the most suitable method.
TopicFinder analyzes the content of documents and assigns them to predefined topics and taxonomies. The product is mainly used for generating topic metadata for unstructured content, filtering and managing information streams as well as for tagging purposes. Typical use cases include, for example, incoming customer mails or news forwarded to the responsible person or editorial staff based on the topic identified. Customers can use TopicFinder for assigning their complete content to their company- or department-taxonomy.
As the tool works fully automatically, there is no need for manual tagging which provides significant value to TopicFinder users like for example editorial offices.
The IntraFind Tagging Service includes an automated generation of metadata / tags based on the processed content. The generated tags can be either inserted into a leading system or can be incorporated into a workflow of any customer-specific use case. The Tagging Service can be provided as an on-premise or cloud solution.
The service consists of different standardized tagging-types that can also be configured if needed: uncontrolled tagging, controlled tagging, the extraction of named entities and the generation of topic metadata.
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