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Search has become a more and more important functionality in most information management systems. Learning from web search engines, most intranet searches have already introduced some useful assistance functions like auto-complete. Semantic search can go far beyond those rather simple features and can help to reduce search times to a minimum while user experience will improve noticeably. Looking at digital assistants like Apple’s Siri, it becomes obvious that the role of search systems will become more and more important for the next generations of knowledge bases. Semantic search and search in general is still very focused on the idea of retrieving a list of relevant documents whilst in reality knowledge workers have to find and link information from a huge variety of sources including statistical databases, videos or personnel databases.
Our solution approach
Semantic search in the context of linked data means to search over a knowledge graph including document search. This approach makes complex queries possible, e.g.: show me all business news which mention at least one of our suppliers of components used in product ABC. The basis for such complex queries is made up by an enterprise linked data store containing a ‘semantic index’ of various legacy data sources combined with the knowledge graph plus enrichments from other linked data sources, taxonomies and ontologies.
- search engine which provides means for complex queries
- queries over various kinds of information (documents, relational databases, taxonomies, etc.)
- personalized search
Benefits from creating and using vocabularies still seem to be below the invested effort. Whereas controlled vocabularies can build the basis for a richer metadata management system, it remains still unclear how thesauri or ontologies can also be used as a valuable information source on its own. Vocabulary management can help to overcome the Babylonian language confusion. A thesaurus can be used by knowledge workers as an encyclopedia to better understand unclear, unintelligible or ambiguous terms and phrases which occur in a large proportion of the documents, mails or protocols they have to deal with on a daily basis.
Our solution approach
In order to get (enterprise) vocabularies widely accepted the costs for the creation and development of such thesauri and vocabularies have to stay as low as possible. This can be achieved if thesaurus managers get support by appropriate methods and software tools to produce high-quality semantic metadata built upon open standards. In case the enterprise (or domain-specific) thesaurus is built upon W3C’s Simple Knowledge Organization System (SKOS) it can also build the core of an organization’s knowledge graph to be reused by many other applications. In addition, built-in text analytics, several importers (like Excel) and linked data enrichment tools help to extend the enterprise vocabulary further and further while keeping the efforts as low as possible. A comprehensive library of quality- and validity checks makes sure that the outcome will meet the highest demands for quality. Putting an enterprise vocabulary to the right place means, that it should be reused by other applications as often as possible. Several standard APIs allow quick integration as well as complex queries over the resulting knowledge graph.
- Enterprise vocabularies fully compatible with W3C’s semantic web standards (SPARQL, RDF, SKOS)
- Ready to be used within a linked data enterprise architecture
- Highly comfortable thesaurus editor, fully web-based with hundreds of features
- Importers for legacy data sources
- Integrations with frequently used enterprise systems like SharePoint, Confluence or Drupal
- Facilities to enrich thesauri with terms from document collections and linked open data
Transforming a simple document server into a collaborative knowledge base which serves as a valuable source for knowledge workers in their daily work is not as simple as it seems to be. On the one hand collaboration platforms like enterprise wikis most often are the right choice to encourage people to collect ideas for new content or to make knowledge about products and services better accessible. On the other hand knowledge bases tend to get tattered over time.
Our solution approach
In order to make specific knowledge about business processes, methods or technologies available for as many employees as possible, we combine the best of three worlds: enterprise collaboration software, text mining and controlled vocabularies. This results in solutions which fulfill the demand for highly dynamic and flexible knowledge bases, still stable (technical and content-wise) enough to be used in professional environments. Since the knowledge base is generated around a controlled vocabulary acting as a meta-layer, traditional navigation structures like trees no longer act as a rigid corset which makes traversing of graph-like structures impossible. Semi-automatic tools for linking, categorizing and content indexing is key to overcome this problem. Putting a controlled vocabulary in place which grows in parallel to the content base demands new and more agile patterns of taxonomy or thesaurus management than ‘traditional’ approaches would provide.