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You can use Concept searching to find information without a precisely phrased query by applying a block of text against the database to find documents of similar conceptual content. This can help prioritize or find important documents.
|Standard Method||Analytics Method|
Finds the presence (or absence) of a query (term or block of text)
|Derives the potential meaning of a query|
Simply looks for matches of query and indexed docs
Attempts to understand semantic meaning and context of terms
|Incorporates Boolean logic||
With standard Keyword Search, people frequently experience “term mismatch,” where they use different terms to describe the same thing.
Using concept searching, you can submit a query of any size and receive documents that contain the concept the query expresses. The match isn't based on any specific term in the query or the document. The query and document may share terms, or they may not, but they share conceptual meaning.
Every term in an Analytics index has a position vector in the concept space. Every searchable document also has a vector in the concept space. These vectors, which are close together, share a correlation or conceptual relationship. Increased distance indicates a decrease in correlation or shared conceptuality. Two items that are close together share conceptuality, regardless of any specific shared terms.
During concept searching, you create text explaining a single concept (called the concept query) and submit it to the index for temporary mapping into the concept space. Analytics uses the same mapping logic to position the query into the concept space as it did the searchable documents.
Once the position of the query is established, Analytics locates documents that are close to it and returns those as conceptual matches. The document that is closest to the query is returned with the highest conceptual score. This indicates distance from the query, not percentage of relevancy—a higher score means the document is closer to the query, thus it is more conceptually related.
In addition, you can use concept searches in conjunction with keyword searches. Since a keyword can have multiple meanings, you can use a concept search to limit keyword search results by returning only documents that contain the keyword used in similar conceptual contexts.
This page contains the following content:
The following are benefits of concept searching:
To run a concept search from the viewer, perform the following steps:
The conceptual hits display in the Search Results Related Items pane. The results are sorted by rank.
Note: The minimum coherence rank used for the right-click concept search is .60. This value is not configurable.
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To run a concept search from the Documents tab, perform the following steps:
This functionality is only available if the Analytics index has been configured to create an integrated dtSearch index. See Creating an Analytics index.
Note: You'll get better results if you enter a block of text, rather than a single word. Single word entries return broad, unreliable results.
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