Organizations are faced with increasing amounts of information from more and more sources. The search for the right desired information from all these sources becomes more important and simultaneously takes more time.

One of the problems is that the search engine itself is usually separated from other systems and processes. When an employee uses a search engine and the results cannot be saved or cannot be linked with what he needs (e.g. a file), sharing and collaborating with colleagues is difficult because they have to repeat the search to get the same result. A search-result can be saved in a document to send it to colleagues, but the search-process must be performed again or it is shared as a static document. The information facility itself is not improved this way.

The search process will only improve if you can save the search, organize and classify it and link it to other information. You want to store your search results in a classification system, so that your results are not only stored but is linked to metadata and various relevant topics.

Combine Topic Maps with SOLR

With Topic Maps and the Open Source SOLR search engine your information facility can be improved because classifying and searching are united. Morpheus has years of experience with Topic Maps and the Ontopia framework, in which Lucene as a search engine was used. In combination with our own tool Kamala it is possible to model your own Knowledge in the Cloud. Using Topic Maps, it is easy to capture facets (attributes of information elements) and to associate them with other important Topics such as persons, places, articles and organizations.

SOLR indexes documents and analyzes fields so that you can search full-text. Topic Maps ensures the optimal visualization of the results. In addition, with the Topic Maps-based web pages it is possible to directly display the desired (filtered) information. This information can also be easily edited and supplemented. This creates a circular process in which the search and classifying parts keep improving.

Technical requirements

To work with Topic Maps and SOLR, the following technical steps needs to be taken:

  1. Creating an indexer that indexes the topic map data in which one wants to search. This includes the selection and choice of domain-specific aspects.
    1. The indexer must update the index in case of changes in the topic map.
  2. Run the indexer (at least 1 time on the full data, then again only when one makes changes).
  3. Create a search-page for the application that uses the SOLR web application, and combines the results of topic map data.

In the screenshots below you find our example Customer Relationship Management map with SOLR facets. The left panel shows three facets: Source, Status and Organizations involved and the right panel shows all the topics.

The user can make his own choices of what he would like to see as facets

What does Morpheus Kennistechnologie BV offer with SOLR/Topic Maps?

  • Ontology development
  • Expertise in creating a single indexer
  • Expertise in creating and activating a dynamic indexer to changes in the topic map
  • Expertise in creating a faceted search page in an application that uses SOLR as search-indexer.

The final result is that data from different systems can be linked easily, your information facility will be improved and knowledge can be truly shared because it is now easier:

  • to find and combine terms from different resources
  • to interpret results by strengthening or weakening in groups
  • to maintain the appropriate classification structures (such as thesauri and taxonomies)

Contact us now to learn more.

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