Knowledge Discovery 25.4
Knowledge Discovery Expert

# Glossary

A
- ACI
  Autonomy Content Infrastructure. ACI is the method that Autonomy components use to communicate with each other.
- ACI Server
  A server component that runs on the Autonomy Content Infrastructure (ACI).
- action
  A request sent to an ACI Server.
- agent
  A process that searches for information about a specific topic, according to a training query or text.
- APCM
  Adaptive Probabilistic Concept Modeling. A statistical method, used by Knowledge Discovery to calculate query result weights and ranks.
C
- category
  A set of criteria that define a particular topic, which you can use to categorize documents that contain content relevant to the topic.
- cluster
  An automatically identified set of related documents.
- community
  A group of users with related interests or expertise.
- Connector
  Autonomy Connectors extract content from source repositories, and send them to CFS for processing and indexing.
- Connector Framework Server (CFS)
  CFS processes data from connectors and sends it to the Content component for indexing.
D
- database
  A Content component database is a data pool that stores indexed information. You can restrict queries to a particular database.
- Distributed Action Handler (DAH)
  DAH distributes actions to multiple versions of a Knowledge Discovery component. It allows you to use failover, load balancing, or distributed content.
- Distributed Index Handler (DIH)
  DIH distributes index actions to multiple versions of the Content component. It allows you to copy or distribute your content.
E
- entities
  A word, phrase, or block of information that the Named Entity Recognition component can match and extract from documents.
- entity
  In Named Entity Recognition, an entity is a word, phrase, or block of information. An entity can be a specific text string, such as a name, or it can be a pattern of text such as an address or phone number. You define the pattern in a grammar, which Named Entity Recognition uses to find the entities in documents.
- extraction
  The process of extracting text, metadata, and subfiles from documents. File Content Extraction performs this extraction process in Knowledge Discovery.
F
- fetch task
  A group of settings that instruct a connector how to retrieve data from a repository. Connectors can run fetch tasks automatically, or in response to an action.
- field
  Fields define different parts of content in Knowledge Discovery documents, such as the title, content, and metadata information.
- File Content Extraction
  A product that extracts data, including text, metadata, and subfiles from over 1,000 different file types.
G
- grammar
  In Named Entity Recognition, a grammar is a pattern that defines an entity.
I
- Identifier
  An encoded value that identifies the source of a document in Knowledge Discovery. Connectors and CFS add identifiers to every document that they create for index into the Content component. They store this value in the AUTN_IDENTIFIER field.
- IDX
  A format of documents that the Content component uses for indexing.
- Import
  Importing is the process where CFS, using File Content Extraction, extracts metadata, content, and sub-files from items retrieved by a connector. CFS adds the information to documents so that it is indexed into the Content component. Importing allows Content to use the information in a repository, without needing to process the information in its native format.
- import task
  A processing task run by CFS on new documents before they are indexed into to the Content component. Import tasks can run before or after (pre- or post-) File Content Extraction filtering.
- index
  The data index contains document content and field information for analysis and retrieval.
- index task
  A processing task run by CFS on documents. Update-index tasks run when a document's metadata (but not its content) is updated. Delete-index tasks run when a document is deleted from a repository.
- indexing
  The process of adding information to the Content component index. This process includes all linguistic processing, storing information for optimized retrieval, and storing document content.
- Ingest
  Ingestion converts information that exists in a repository into documents that can be indexed into the Content component. Ingestion starts when a connector finds new documents in a repository, or documents that have been updated or deleted, and sends this information to CFS. Ingestion includes the import process, and processing tasks that can modify and enrich the information in a document.
K
- Knowledge Discovery
  The Knowledge Discovery data platform allows you to convert your source content to an index of useful data that you can search and analyze.
L
- Lua
  An embedded scripting language that you can use to write custom scripts to expand certain Knowledge Discovery functionality.
N
- Named Entity Recognition
  The process of extracting entities (patterns of text) from documents.
P
- profile
  Information about a user, based on the concepts in documents that they access. The Community component automatically creates profiles for users, according to their interests.
Q
- query
  A search string that you can use to retrieve information from the Content component that matches your syntax. Queries include simple conceptual queries, and complicated strings with Boolean, proximity, and field restriction expressions.
- Query Manipulation Server
  A server that manipulates incoming searches to modify the query, modify the results set, or return promotions.
R
- reference
  A string that is used to identify a document. This might be a title or a URL, and allows the Content component to identify documents for retrieval, indexing, and deduplication.
S
- security
  Security includes anything that makes sure that only authorized users can access or perform actions on data. It includes making sure that only permitted users can view and retrieve documents, user authentication, and secure communications.
- seed
  In clustering with snapshots, a seed is a potential cluster. It contains a document, and suggested conceptually similar documents from the Content component index.
- sentiment analysis
  A form of Named Entity Recognition that identifies positive and negative sentiment in text.
- stemming
  The process of finding a common root for related words. The Content component uses this common root to search, so it finds the concept rather than the particular term.
- stop list
  A list of stop words, which the Content component uses to discard these terms at index and query time, which can improve performance.
- stop word
  A word in a language that occurs frequently and does not add much meaning to text.
- subfile
  A file that has been extracted from a container (such as a .ZIP archive).
- summary
  A few sentences or paragraphs that describe what a document is about. The Content component can automatically create summaries from document content.
T
- taxonomy
  A hierarchical structure of categories, or other information, which gives you an overview of your data.
- term
  The basic entity that the Content component indexes; for example, a word after stemming.
- TNW
  Terms and Weights. These are used in categorization to define the most important terms that define a category topic.
- training
  Text, documents, and query syntax used to define the topic that an agent or category must match.
U
- Unstemmed index
  Wildcard searches (and some advanced search techniques) use the index of unstemmed terms. This index contains all the exact terms that occur in documents.
V
- View
  A Knowledge Discovery component that converts files in a repository to HTML formats for viewing in a Web browser.

Copyright 2025 Open Text
Version 25.4 | Last updated October 2025

Send documentation feedback

Close

Send documentation feedback

To send feedback using your default email client, open an email window.

Otherwise, send your feedback and the information below to MFI-swpdl.idoldocsfeedback@opentext.com.

We appreciate your feedback!

Product: Knowledge Discovery 25.4

Topic Title: Glossary