Relativity Analytics 9.1 UPDATED ACTUAL Exam Questions and CORRECT Answers

Relativity Analytics 9.1 UPDATED ACTUAL
Exam Questions and CORRECT Answers
Relativity Analytics - CORRECT ANSWER - categorizes topics into clusters of
conceptually similar material using a technology called Latent Semantic Indexing. Once the
documents are categorized, you can batch the clusters that include the materials most relevant to
your case to pass on to reviewers.


Analytics helps reveal the facts of the case by (4): - CORRECT ANSWER - 1. Giving
users an overview of the document collection through clustering.
2. Helping users find similar documents with right click.
3. Allowing users to build example sets of key issues.
4. Running advanced keyword analysis.


You can configure the physical location of the analytics indexes and structures analytics sets. -
CORRECT ANSWER -


Analytics provides accelerates document review through conceptual search of unstructured text. -
CORRECT ANSWER -


The Analytics engine uses mathematically-based technology called Latent Semantic Indexing
(LSI) to discover the text for the data to be queried. - CORRECT ANSWER -


Latent Semantic Indexing (LSI) allows Analytics to identify relationship patterns between terms
and concepts WITHOUT using pre-established word lists, dictionaries, or linguistic techniques
(such as sentence structures). - CORRECT ANSWER -


Analytics indexes are always in memory when being worked with, so response time is very fast.
- CORRECT ANSWER -

, Analytics is inherently language agnostic. It can index most languages and accommodate
searches in those same languages without additional training. We recommend creating separate
indexes for populations of different language documents. - CORRECT ANSWER -


Analytics learns term correlations (interrelationships) and conceptuality based on the documents
being indexed. It is always up-to-date in its linguistic understand. - CORRECT
ANSWER -



Concept Space - CORRECT ANSWER - When you create an Analytics index, Relativity
uses the training set of documents to build a mathematical model called a Concept Space.


Throughout Analytics, we measure the similarity of items using a rank value. Depending on the
feature, the rank may be referred to as a coherence score, rank, or threshold. - CORRECT
ANSWER -


Because Analytics builds a spacial index, every document has a spacial relationship to every
other document. - CORRECT ANSWER -


Concept Rank is an indication of distance between two items. In Categorization, it indicates the
distance between the sample document and the resulting document. In Keyword Expansion, it
indicates the distance between the two words. The rank does not indicate a % of relevance. -
CORRECT ANSWER -


Before creating a new Analytics search index, you can create an Analytics profile to specify
values for the index's dimensions, concept words, dtSearch noise words, and filter
configurations. - CORRECT ANSWER -


Before creating a Structured Analytics set for email threading, create an Analytics profile to map
applicable email fields. - CORRECT ANSWER -


Analytics profiles are reusable and transferable. There is a default Analytics profile. - CORRECT
ANSWER -