Autonomy Content Infrastructure (ACI)
A technology layer that automates operations on unstructured information for cross enterprise applications, which enables an automated and compatible business-to-business, peer-to-peer infrastructure.
The ACI allows enterprise applications to understand and process content that exists in unstructured formats, such as e-mail, Web pages, office documents, and Lotus Notes.
An IDOL server field that stores Boolean agents (Boolean or Proximity expressions that legacy technologies use to categorize documents). You can then query IDOL server with text and an agentboolean field to return categories whose Boolean agent matches this text.
A process that searches for information about a specific topic. An administrator can create agents for users or allow users to create their own agents.
Adaptive Probabilistic Concept Modeling (APCM)
A technique whereby terms are given a weight according to their statistical importance in IDOL server. Terms can have a weight between 0 and 255.
A hierarchically agglomerated collection of data that has been extracted from snapshots. Each cluster represents a concept area that contains a set of items, which share common properties. Clustering data allows you to make trends and developments in data visible.
All the people in a user network neighborhood. It allows users to find other people in the community who have been looking at similar documents or have agents that are similar to their agents.
A brief summary of each result document that returns for a query. The concept summary displays a few sentences that are typical of the result content (these sentences can be from different parts of the result document).
An Autonomy fetching solution (for example HTTP Connector, Oracle Connector, File System Connector and so on) that allows you to retrieve information from any type of local or remote repository (for example, a database or a Web site). It imports the fetched documents into IDX or XML file format and indexes them into IDOL server from where you can retrieve them (for example by sending queries to IDOL server).
A conceptual summary of the result document that is biased by the terms in the query. A context summary comprises sentences that are particularly relevant to the terms in the query (these sentences can be from different parts of the result document).
An IDOL server index that stores content data. You can customize how to store data in the Data index by configuring appropriate settings in the IDOL server configuration file.
An IDOL server data pool that stores indexed information. The administrator can set up one or more databases, and specifies how data is fed to the databases. By default IDOL server contains the databases Profile, Agent, Activated, Deactivated, News and Archive.
Intellectual Asset Protection System (IAS)
An integrated security solution to protect your data. At the front end, authentication checks that users are allowed to access the system that contains the result data. At the back end, entitlement checking and authentication combine to ensure that query results only include documents that the user is allowed to see, from repositories that the user is allowed to access.
The Autonomy Intelligent Data Operating Layer (IDOL) server, which integrates unstructured, semi-structured and structured information from multiple repositories through an understanding of the content, delivering a real time environment in which operations across applications and content are automated, removing all the manual processes involved in getting the right information to the right people at the right time.
A structured file format that can be indexed into IDOL server. You can use a connector to import files into this format or you can manually create IDX files (see Index Data).
The process of storing data in IDOL server. IDOL server stores data in different field types (such as, index, numeric and ordinary fields). It is important to store data in appropriate field types to ensure optimized performance.
Fields that IDOL server processes linguistically when it stores them. Store fields that contain text which you want to query frequently as Index fields.
IDOL server applies stemming and stop word lists to text in Index fields before it stores them, which allows IDOL server to process queries for these fields more quickly. Typically DRETITLE and DRECONTENT are fields that are set up as Index fields.
Also referred to as “Links”. Terms in query text that are also contained in the result documents that IDOL server returns for this query.
Information about a user that is based on the concepts in documents that the user reads. Every time a user opens a document IDOL server updates their profile. This process allows the administrator to bring new documents to users attention that match the interests in their profiles.
A string that you submit to IDOL server, which analyzes the concept of the query and returns documents that are conceptually similar to it. You can submit queries to IDOL server to perform several kinds of search, such as natural-language, Boolean, bracketed Boolean, and keyword.
A brief summary of each result document that returns for a query. The quick summary displays the first few sentences of the result document.
Fields used to identify documents. At index time IDOL server can use ReferenceType fields to eliminate duplicate copies of documents. It uses them at query time ReferenceType to filter results.
The process used to increase the accuracy of agents by indicating which of the results that return to you are most relevant to your query. The retrained agent then returns more relevant results.
The process of separating a document into sections for indexing. The number of sections that a document is split up into increases proportionally with the size of the document.
This process ensures that when you, for example, query for text that is relevant to a specific part of a book, IDOL server can find the appropriate section and return it (if the book was not indexed in sections, IDOL server might not find the text you search for, as it may not be conceptually relevant to the entire book).
The process of extracting the morphological root of a word. In languages some words have a common morphological root. Autonomy provides stemming algorithms that reduce words to this form. This process allows IDOL server to match concepts regardless of the grammatical use of words. In English for example, the words "help", "helpful", "helping" and "helped" all reduce to their stem "help" without significant loss of meaning.
Autonomy provides as standard a set of stemming algorithms for the most commonly used languages. IDOL server applies stemming after stop words have been discarded both at index time (when content is stored in IDOL server) and at query time (query text is stopped and stemmed before it is matched).
Also called stop list. A list (located in the IDOL server langfiles directory) that contains common words (stop words) that IDOL server does not store. Words such as the or a occur too frequently to carry any significance and IDOL server does not require them to understand the concept of text.
The process of removing the words listed in the stop word list from documents before they are stored in IDOL server and from query text before it is matched against IDOL server content.
A file that allows IDOL server to handle synonym queries. A synonym query returns results which are conceptually similar to the query terms and conceptually similar to the synonyms that are available for the query terms.
A synonym file contains comma separated lists of synonym strings for words. You can specify lists for each language type you have set up in IDOL server within this file.
An automatically created hierarchical structure of clusters or other information. A taxonomy provides you with an overview of the 'information' landscape and an insight into specific areas of the information.