Relativity Analytics 9.1 Exam Questions and Answers 100% Pass

Relativity Analytics 9.1 Exam Questions and Answers 100% Pass Relativity Analytics - 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): - 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. - Analytics provides accelerates document review through conceptual search of unstructured text. - 2100% Pass Guarantee Sophia Bennett, All Rights Reserved © 2025 The Analytics engine uses mathematically-based technology called Latent Semantic Indexing (LSI) to discover the text for the data to be queried. - 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). - Analytics indexes are always in memory when being worked with, so response time is very fast. - 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. - Analytics learns term correlations (interrelationships) and conceptuality based on the documents being indexed. It is always up-to-date in its linguistic understand. - Concept Space - 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. - 3100% Pass Guarantee Sophia Bennett, All Rights Reserved © 2025 Because Analytics builds a spacial index, every document has a spacial relationship to every other document. - 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. - 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. - Before creating a Structured Analytics set for email thre