Reveal Help Center

Document Viewer

Concept Topics
Metadata Features

Metadata features are described by two element JSON arrays. JSON is a format for transmitting data between software applications.

Note

Metadata feature descriptions have an indirect relationship to the field names of the original metadata fields in the source dataset. Brainspace strongly encourages using an exported portable model file as a starting point when creating a new portable model file that will use metadata features. Begin by using CMML to train a portable model from some examples on the source dataset (or one with the same metadata structure and import configuration), and then export the model. You can then modify the feature descriptions in that exported file to produce documents that will be useful for your classification task.

Below are some example feature descriptions for metadata match features:

  • “[“”cc””,””fred jimes <jimes@foo.org (jimes@foo.org)>””]”

  • “[“”created””,””20011204″”]”

  • “[“”emailclient””,””outlook””]”

  • “[“”sent-hour-of-day””,””12″”]”

  • “[“”received-day-of-week””,””thursday””]”

  • “[“”created-year-month-day-hour””,””2001120412″”]”

The first element of the description specifies the field name of a metadata field. Because of mapping and feature extraction operations, the field names in metadata features are not necessarily the same as the field names in the source data.

In the examples above, the field names are:

  • cc

  • created

  • emailclient

  • sent-hour-of-day

  • received-day-of-week

  • created-year-month-day-hour.

The second element is the field value to be matched. The metadata feature will contribute to the score of a document when the field value matches the contents of the specified field for the document.

In the examples above, the field values are:

  • “fred jimes <jimes@foo.org (jimes@foo.org)>”

  • “20011204”

  • “outlook”

  • “12”

  • “thursday”

  • “2001120412”

The process of determining whether a field value matches the contents of the corresponding field depends on the nature of the particular field.

Two factors play into this:

  • The values for some metadata fields (e.g., emailclient) correspond directly to raw values in the source field in the original data. Other metadata fields have values that are the output of some computation. For example, received-day-of-week has a value that is derived mathematically from the date.

  • Some metadata fields always take on a single value, (which might be missing) for a document (e.g., emailclient above), while others (e.g., cc) can take on zero, one, or several values.

Document Viewer Features

After doing a search for documents in Analytics, you can view each document and its metadata in the Document Viewer. The Document Viewer includes the following features:

Document_Viewer_Features.jpg

Callout 1: View the Results pane.

Callout 2: Open a specific document in the Document Viewer.

Callout 3: View the Hit Relevance pane to display a document’s metadata and manage tags.

Hit Relevance Pane (Metadata Tab)

When reviewing documents in the Document Viewer, you can view metadata and view and manage tags associated with a document. The Metadata tab includes the following features:

Hit_Relevance_Pane__Metadata_.jpg

Callout 1: View the search elements that are true for the selected document. In this example, the user searched for near-duplicate documents, and the example document was included in the search results because it is a near-original (pivot of the near-duplicate set) document.

Callout 2: View document metadata.

Callout 3: View and manage document tags.

Callout 4: Filter to find specific fields associated with the document.

Callout 5: Manage pinned metadata fields.

Callout 6: View metadata fields associated with the document.

Callout 7: Unpin the metadata field.

Callout 8: Pin the metadata field.

Hit Relevance Pane (Tags Tab)

When reviewing documents in the Document Viewer, you can view and manage tags associated with a document. The Tags tab includes the following features:

Hit_Relevance_Pane__Tags_.jpg

Callout 1: View the search elements that are true for the selected document. In this example, the user searched for near-duplicate documents, and the example document was included in the search results because it is a near-original (pivot of the near-duplicate set) document.

Callout 2: View and manage document tags.

Callout 3: Add an existing tag to the document.

Callout 4: View and delete tags associated with the document.

Focus

To include a specific subset of documents in a dataset when training a CMML classifier, you can create a focus and then use it as a training round. All training examples must come from this subset of documents. Predictive ranks will only be applied to documents from the same subset of documents.

For example, a dataset called English Wikipedia contains 4.3 million documents, but only 21,000 of those documents are related to the concept “Apollo.” Given that the rest of the documents in the dataset are unrelated to Apollo, there is no need to consider them for training or assign predictive ranks to them. When using a focus with the Relativity integration, scores for the 21,000 documents will be overlaid in Relativity each time the model is updated instead of the entire corpus of 4.3 million documents.

Task Topics
Sort Documents by Metadata Fields

After creating a search, the documents will display in the Results pane sorted by relevance to the search terms. You can also choose to sort documents by specific metadata fields.

To sort documents by specific metadata fields:

  1. With a search active and the Results pane visible, hover over the SORT BY Relevancy field, and then click a metadata field:

    Sort_by_Relevancy.jpg

    The Results pane will refresh to display the highest ranking document for the specified metadata field at the top of the document card list and the lowest scoring document at the bottom of the card list. You can click the Sort arrow to view the results in ascending order:

    Sort_Results.jpg

After sorting document cards by a metadata field, you can use the results to create a focus or a notebook. You can also tag the documents and download a report for the results.

Pin and Unpin Metadata Fields

After opening a document in the Document Viewer, you can pin a document’s metadata fields to view specific metadata fields while reviewing documents.

To pin and unpin metadata fields:

  1. In the Results pane, click a Document Card:

    Pin_Document_Card.jpg

    The Document Viewer will open.

  2. In the fields list, find the metadata field of interest (perhaps by filtering field names) by hovering over a field, and then click the Pin icon:

    Pin_Metadata_Field.jpg

    The field will be pinned to the top of the metadata fields list, and the Pin icon will change to an Unpin icon.

Fields will remain pinned from session to session even after you log out of Brainspace. After pinning the field, you can pin additional fields, clear all pins, show only pinned fields in the metadata fields list, or continue reviewing documents.

Show Only Pinned Metadata Fields

After pinning metadata fields, you can hide unpinned metadata fields to view only pinned fields in the Metadata tab.

To show only pinned metadata fields:

  1. In the Results pane, click a document card:

    Pin_Document_Card.jpg

    The Document Viewer will open.

    Note

    If you have pinned metadata fields, the pinned fields will display at the top of the Fields pane followed by unpinned metadata fields.

  2. Toggle the Show Only Pinned Fields switch to the On position:

    Show_only_Pinned.jpg

    The Fields pane will refresh and display only pinned fields.

Your decision to show only pinned metadata fields is preserved from session to session even after you log out of Brainspace. After showing only pinned fields, you can clear all pins or continue reviewing documents.

Clear All Pinned Metadata Fields

You can clear all pins to view all metadata fields in the search results. To clear all pinned metadata fields:

  1. Click the Supervised Learning tab.

    Supervised_Learning.jpg

    The Supervised Learning screen will open.

  2. Click a Classifier card.

    The Classifier screen will open.

  3. In the Results pane, click a Document Card:

    Pin_Document_Card.jpg

    The Document Viewer will open with pinned fields at the top of the Fields pane.

  4. Click the Clear Pins link:

    Clear_Pins.jpg

    The Fields pane will clear all pinned fields refresh to display all metadata fields.

After clearing unpinning the field, you can pin additional fields or continue reviewing documents.

Create a Focus

After searching for documents in a dataset, you can create a focus from the search results to use when creating a CMML classifier.

  1. Open a dataset in the Analytics Dashboard.

  2. Search for documents.

    The Document Viewer will open.

  3. Click the Focus icon:

    Click_FOCUS.jpg

    The Manage Focus dialog will open.

  4. In the Name text field, type a name for the focus.

  5. Click the Private/Public switch to make the focus public.

    Note

    If you choose to make the focus public, you will not be able to make it private in the future.

  6. Click the Threads, Families, Related Documents, or Exact Duplicates check boxes to include additional documents in the focus.

  7. Click the Save Focus button.

    The Manage Focus dialog will close.

After creating a focus, you can use it to create a CMML classifier.

Manage a Focus

After creating a focus, you make a private focus public and delete a focus.

To manage a focus:

  1. Open a dataset in the Analytics Dashboard.

  2. Click the Select a Focus dropdown menu, and then click the Edit Focus icon :

    Select_a_Focus.jpg

    The Manage Focus dialog will open.

  3. Edit the settings and then click Save Focus, or click the Delete icon.

Manage Documents in a Focus

After creating a focus, you can open the focus in the Analytics Dashboard to view its documents, tag documents.

To manage documents in a focus:

  1. Open a dataset in the Analytics Dashboard.

  2. Click the Select a Focus dropdown menu, and then click the Focus entry in the list:

    Select_Focus_Entry.jpg

    The focus will open in the Analytics Dashboard, and the Select a Focus dropdown menu will display the name of the focus.

All further searches with this focus active will be constrained to the documents in this focus.