Important Update: Cohesity Products Documentation


All Cohesity product documentation are now managed via the Cohesity Docs Portal: https://docs.cohesity.com/HomePage/Content/home.htm. Some documentation available here may not reflect the latest information or may no longer be accessible.

Arctera™ Insight Surveillance Web Client Reviewer's Guide

Last Published:
Product(s): Veritas Alta Surveillance (1.0)
  1. Introducing Arctera Insight Surveillance
    1.  
      About Insight Surveillance
    2.  
      Key features of Insight Surveillance
    3.  
      Feature comparison: Enterprise Vault Compliance Accelerator Desktop Client Vs Insight Surveillance web client
    4.  
      About Insight Surveillance system security
    5.  
      Insight Surveillance multi-tier architecture
    6.  
      System requirements
  2. Getting started
    1.  
      Signing in to Insight Surveillance
    2.  
      Signing out from Insight Surveillance
  3. Working with dashboard widgets
    1.  
      Understanding the Dashboard page
    2.  
      Viewing status summary of recently reviewed departments
    3.  
      Pinning and unpinning departments to view review status
    4.  
      Changing the order of pinned departments
    5.  
      Viewing the review status summary of escalated items
    6.  
      Viewing a summary of searches and exports
  4. Managing department-level searches
    1.  
      About department-level searches
    2.  
      Guidelines for effective searches
    3.  
      Creating and running department-level searches
    4.  
      Pausing and resuming searches
    5.  
      Downloading search details for archives
    6.  
      Disabling scheduled searches
    7.  
      Previewing search results
    8.  
      Accepting search results
    9.  
      Rejecting a search result
    10.  
      Resubmitting a search
  5. Managing reviews
    1.  
      About reviewing with Insight Surveillance
    2.  
      Understanding the Review page
    3.  
      Rearranging columns in the item list pane
    4.  
      Changing the Preview pane position
    5.  
      Filtering the items in the Review pane
    6.  
      Reviewing the Audio-Video Transcript type items
    7.  
      Reviewing searched items
    8.  
      Reviewing research folder items
    9.  
      Reviewing department items
    10.  
      Viewing Intelligent Review Details
    11.  
      Adding or removing text for machine learning
    12.  
      Assigning review status to items
    13.  
      Viewing hotwords highlighting
    14.  
      Viewing hotwords in collaboration message
    15.  
      Viewing tags highlighting
    16.  
      Viewing tags in collaboration message
    17.  
      Viewing the full content in a new window
    18.  
      Adding comments to items
    19.  
      Escalating the review items
    20.  
      Applying labels to items
    21.  
      Viewing history of items
    22.  
      Printing the original versions of items
    23.  
      Printing and downloading the items and attachments

Viewing Intelligent Review Details

The Intelligent Review Details section provides the facts of why the item is classified as Unreviewed Relevant or Unreviewed Irrelevant. It shows the Relevant and Irrelevant labels (links) and the respective contribution.

During review, the Intelligent Review Details section appears on the Preview tab only if the departments you want to review are enabled for Intelligent Review, and the Show Intelligent Review Details in Review permission is enabled for the logged-in user. This permission is by default enabled for the Department Reviewer, Escalation Reviewer, Compliance Supervisor, Exception Reviewer, and Passive Reviewer roles, where either the Review Messages or the Review Escalations permissions are enabled. By default, Intelligent Review Details section is collapsed. Users can expand and collapse it as required.

The total relevant and irrelevant contribution value is shown besides the respective labels. These values (between 0 to 100) are factor of relevant and irrelevant contributions found inside the item. When you click the Relevant and Irrelevant labels, the corresponding details appear which shows the factors that have contributed towards relevant or irrelevant. The calculated values of a contribution of each factor are mentioned so that a reviewer can understand the reason behind the item being relevant or irrelevant.

If the contribution value of the relevant factors is more than the contribution value of the irrelevant factors, the item will have higher relevance score (greater than 50). If the contribution value of the irrelevant factors is more than the contribution value of the relevant factors, the item will have lower relevance score (less than 50). If the contribution values of the relevant and irrelevant factors are almost similar, the item will have the relevance score around 50.

The factors that contribute are Author, Recipient, Subject, Content, Direction, Tags, and Department influence. Department Influence shows the extent to which prediction is inclined in favor of or against the marking based on the department's learning. If reviewers in a department favor marking items as irrelevant, then Department Influence will contribute towards irrelevance and vice versa. If factors do not have values, they can still contribute as relevant or irrelevant. It happens when the algorithm weighs the lack of details (such as the presence of zero tags or absence of content) as a contributing factor to its learning.

If the contribution of any factor is insignificant, but not absolutely zero (0), then value can be rounded to and displayed as zero (0). If the factor does not contribute at all, then this factor is not displayed. The amount of contribution of each factor is also shown with the color legend.

Refer to the sample images below.

Figure: Preview pane showing the IR details, hit highlighting, and managing text for learning

Preview pane showing the IR details, hit highlighting, and managing text for learning

Figure: Contributing factors and their contribution

Contributing factors and their contribution

Following are some circumstances when the Intelligent Review Details are not available, and the application displays different messages for users.

Circumstance

Displayed message

Item is not processed by the Intelligent Review engine

Details not available

Data for machine learning is inadequate

Intelligent Review is still learning. Details are not yet available.

Technical problem during loading Intelligent Review Details

Error loading Intelligent Review Details