default Webstart mode: 'webstart' uses the client launcher, 'download' requires the user to download the .jar file manually Search hits: default number of hits returned by the search Web cont. Folders: list of folder ids that will be used by the web...
panel, you can retrieve the last events on folders and documents and the last user session activities. You can perform a search to enlist the activities performed on the defined date range and regarding a specific and exact User, Session ID (SID) or...
lists Tag cloud elements: Maximum number of tags displayed in the tag cloud Vocabulary: The set of symbols to show in the search widgets Used Tags This panel is useful to perform maintenance among the tags used in your system, most of the time you wish...
remote email accounts. You can configure a number of email accounts so that they will be regularly inspected by the system, searching for new posts to be imported as documents. In this panel, you can see the currently existing accounts. To add a new...
the plus icon to add this in the participants list. At runtime, LogicalDOC will inspect the currently involved documents, searching for the attributes you specified here as participants and will add the referenced users as possible owners of the task....
these tags ( and ) teach the system how to recognize similar structures and values in new, unseen text. Examples: I am searching for the document with id 12356897 , please send it to me. All employees are encouraged to find doc with id 0023 on the HR...
the Internet. In any case, the scheduled task Docusign Poller will try to periodically connect with your DocuSign account searching for closed envelopes to update the documents' repository. [/alert] List envelopes You can access the list of current and...
in days) the system must create the archives. You can select in which folder, within the documents archive, will be searched for documents and can define the templates to which these documents will be associated. [alert style="uk-alert"][heading...
This facilitates efficient comparison and manipulation of textual data in natural language processing (NLP) like semantic searches. How the Embedder Works The transformation of a document's content into a vector is realized through the Doc2Vec...
it continues to exist in the system, but it is stored in a different area no more available during folder browsing or searches, this optimizes the performances. If you are granted the Archive permission in a current folder, just right click on it,...
it continues to exist in the system, but it is stored in a different area no more available during folder browsing or searches, this optimizes the performances. If you are granted the Archive permission in the current folder, just right-click on a...
Tags This section shows you the most used tags and their occurrence in the repository. It provides you with tools to search documents by tags. Messages LogicalDOC has an internal messaging system. Each row in the list is a message that has been sent to...
you browse the folders tree. Each time you open a folder, the list of all contained documents is presented for selection. A search box is also available on the top to help you in finding the right document. Select the desired document, then press [Open]...
in this article. On your ADFS installation, open the ADFS console. Select Service, then select Endpoints. In the Type column, search for SAML 2.0/WS-Federation and note down the value of URL Path column. This is also known as the SAML SSO URL Endpoint...
vector store indexes and stores vector embeddings (the vectorial representation of documents) for fast retrieval and semantic search. Embeddings are generated by AI models, in the context of machine learning these features represent different dimensions...
representation of is required to efficiently infer similitudes between documents and implement features like Semantic Search. This means that LogicalDOC must calculate all these embeddings for the documents in your repository and save them into the...
(This setting must reference a previously configured model) Semantic Similarity (Retrieval-based) Uses vector similarity search over embeddings to retrieve the most relevant content Embedding Scheme: for the selection of a specific embedding scheme...
of the most common file types including: MS Office documents, OpenOffice/LibreOffice, PDF, HTML, XML, JPEG, etc. Its powerful search engine indexes all types of documents which makes it easy to find any type of information.
