DATA SHEET

Magellan Text Mining
Leverage powerful natural language processing to analyze unstructured content
and unlock the insights held within
OpenText Magellan Text Mining enables enterprises with an

Reduce manual
effort with
automateddocument review
and capture ofsemantic metadata

all-in-one solution that combines data and entity extraction,text analytics, natural language processing, and semantic
analytics to garner powerful knowledge from theirunstructured content, and leverage it to better manage andgrow their businesses. Unstructured content, such as articles,
documents, abstracts, emails, reports, captions, customer
chat logs and social media content, store invaluable data that

Improve thecontent discovery
process withbespoke indexing
and classification
Extract meaningful
data and insightsfrom complex
unstructured
sources quickly andconsistently

is typically inaccessible to the organization or requires tediousand time-consuming manual analysis.
Magellan Text Mining empowers organizations to extract meaningful informationfrom each textual asset, and automatically tag and enrich it with semantic
metadata. This deepens an organization’s ability to gather insights and improves
the findability of content by better connecting individuals to more relevant pieces ofcontent. The platform provides robust metadata relationship retrieval and building
capabilities, and the semantic metadata provided by Magellan Text Mining can
be blended with other metadata types (e.g. system, editorial). This capability also
extends to Enterprise Content Management systems and analytical resources, such
as Magellan dashboards, to enhance business insights processes and deliver an
extensive content intelligence and analysis experience.

Built using outof-the-box
machine learning
capabilities throughpre-trained andcustom models fortext categorizationand text mining
Magellan Text Mining insights can be displayed in an easy-to-use dashboard whenused with the Magellan BI & Reporting.
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Magellan Text Mining modules

Associated OpenTextproducts• Magellan Content
Analytics Suite• Magellan Platform• Magellan AI-powered
augmented Capture

Magellan Text Mining is comprised of six modules that provide an end-to-end
process to extract, analyze, and process specific types of semantic metadata:
FeatureDescription

Concept extraction Identifies meaningful keywords and key phrases, extracts
core concepts following grammatical patterns of a noun,verb phrase or statistical tokens, and can be configured to
specifications for unique use cases such as large or short texts• Magellan AI-augmented
Voice of the Customer

Concept extraction operates in four steps:
1. Text parsing and word cropping: Analyze and distinguishkeyword candidates from abbreviations, delimiters, etc.

• Magellan AI-driven
Content Advisor

2. Part of speech tagging: Assign a grammatical role toeach keyword
3. Extraction of part of speech patterns: Identify andexpose relevant grammatical patterns such as simple
nouns and complex noun phrases
4. Expose metadata: Concepts are exposed along with
the information regarding their frequency, relevancy
and position.
Named entity
recognition (NER)& information
extraction

Locates and identifies terms or sequences of terms thatcan be referred to with a name, such as organizations,geographic locations, trademarks, events, people names,
and diseases. For example, “Open Text Corporation” would
be an organization entity, “North America” a geographic
entity and “Albert Einstein” a person name entity. Throughadvanced machine learning and authority files, Magellan
Text Mining can also recognize and associate different
names for the same entity to improve content findability.
Magellan’s Named Entity Extractor includes normalization
algorithms to ensure standardized entity assignments
across all content. Named entities are exposed alongwith relevancy and confidence scores, sub-term / parent
positions and their length. These entities can be also
exposed in a context showing subjectivity and tonality
information around each entity sub-term.

Text classification

Indexes and sorts documents by classification alongwith the classification weight and relevancy ranking.
Classifications are topics inferred from the body ofa document; they are identified and associated withdocuments even if the category name is not explicitly statedin the text.

Text summarization Identifies key sentences in a document and uses them tocreate a brief overview according to topics of interest.

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Magellan Text Mining modules (Cont'd)Out-of-the-box
Categorizer
Knowledge Bases• Business and Finance• General BusinessFeature

Description

Sentiment andemotion analysis Subjectivity, tone,and emotion

Determines the subjectivity (fact or opinion), tone (positive,negative, or neutral), and emotions (anger, anticipation,distrust, fear, joy, sadness, surprise, and trust) of thedocument. Sentiment Analysis is performed first on asentence level, then on the document level and around
named entities. The Sentiment Analyzer module canalso perform emotion analysis to determine the emotion(anticipation, anger, disgust, fear, joy, sadness, surprise,trust) within text, along with their variations depending on
the weight shown for each.

Languagedetection

Recognizes the language(s) used throughout the document
and automatically categorizes the document accordingly.

• International Press
Telecommunications
Council (IPTC)• Industry Classification
Benchmark (ICB)• Library of Congress
Thesaurus for Graphic
Materials (LCTGM)• Energy Technology Data
Exchange and International
Nuclear Information System(ETDE-INIS)• Generally Accepted
Accounting Principles forCommerce and Industry(GAAP-CI)• Records Management• Resumes• Retention• Personal Information

With the Magellan Text Mining Studio it’s easy to manage and edit existingknowledge bases, or import new ones.

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Connectivity

ISO/NISO Standard
Authority Files• Organization names• Person names• Geopolitical locations

Straightforward connections that enable your organization to extract, tag, andanalyze unstructured content from a vast range of sources, all managed, controlled,
and operationalized from a single location.
FeatureDescription

OpenText• Archive Center• Content Server• Geophysical names• Documentum• Trademark• eDocs• Events• InfoArchive• Life sciences: Diseases,
Symptoms, Drugs,
Physiology• Features• Currency• Date and time

• Media Manager• Tempo BoxConnectors for3rd party
repositories• CMIS• Dropbox• Google Drive• Computer and internet• Google Gmail• Twitter• Personally Identifiable
Information (PII): SSN,
Passport, Phone Number
Bank Account, Address,
Driver’s License• Box.com• IBM FileNet• Microsoft Exchange• Microsoft SharePoint
Supporteddatabases

Magellan Text Mining Conversion Service• Microsoft SQL Server
Text Mining Pipeline• Apache Hive
• Apache Spark• Microsoft SQL Server• MySQL Enterprise• PostgreSQLECM Crawling Service• Microsoft SQL Server• Oracle• PostgreSQL
Magellan Integration Services• Microsoft SQL Server• Oracle• PostgreSQLECM Repositories• OpenText Content Server• OpenText Tempo Box• Windows file shares

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Methodology & Analysis
Magellan Text Mining uses a variety of carefully chosen methodologies thatcomplement each other, and can be tailored to your specific vocabularies, sothat it can identify and extract the most relevant semantic metadata quickly andaccurately. It also draws upon powerful machine learning capabilities, comes withbuilt-in libraries of terms (including many important business concepts), pre-trained
text categorization models, and can be trained on nearly any other topic across amultitude of languages.
FeatureDescription

Pattern matching• Statistical - Translates segments of text into paragraphs,
sentences, tokens, and n-grams, along with attributes foreach segment• Linguistic – Identification of words and phrases that arelikely to be concepts and patterns and transforms tokens
and n-grams from “sequences of items” to real lexical units

Machine learning• Leverage powerful families of algorithms, including NaïveBayes, Boosting Algorithm, Keywords computing, Decision
trees, to train ML models and improve prediction accuracy.
• Following Magellan’s metadata assignment process,users can apply post-processing algorithms to review themetadata based upon the factors most important to them

Knowledgeengineering• The knowledge engineering functionalities embedded
in Magellan Text Mining empower users to create andmanage their own taxonomies and authority files for theirown business-specific use cases.
• Multiple Text Mining modules use knowledge engineering
to improve ML prediction accuracy through creationof a training set and model, optimize the model basedon statistical observations, and configure it to specificcustomer needs.

Supportedlanguages

Magellan Text Mining supports these languages withdedicated natural language processing and one or moreannotators available out of the box:
• Arabic, Chinese, Dutch, English, French, German, Hebrew,Italian, Japanese, Portuguese, Spanish
Magellan Text Mining supports basic concept and entity
extraction in 25 additional languages
Dedicated Tokenizer• Czech, Persian, Polish, Russian, Turkish
Multilingual Tokenizer• Bulgarian, Catalan, Croatian, Danish, Estonian, Finnish,Greek, Hungarian, Icelandic, Irish, Latvian, Lithuanian,Norwegian, Romanian, Slovak, Slovenian, Swedish,Ukrainian, Vietnamese

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Methodology & Analysis (Cont'd)
FeatureDescription

Text mining –Simple mapping
parameters keys

• Summary• Subjectivity score and its distribution• Tone type (positive/negative/neutral)• Positive/Negative/Neutral tone scores and their distribution• Simple concept• Complex concept• Named entities• Classifications• Emotions (anger, anticipation, disgust, fear, joy, sadness,surprise, trust) and their weight

Text Mining Services
FeatureDescription

Modeling & bench- Provides a growing collection of REST APIs that extract andmarking services
enrich unstructured content with semantic metadata andsupport text classification modeling. Users can create andmanage custom taxonomies and authority files, then train
and benchmark classification models and/or rules for themand use the modeling services to customize the provided
semantic annotations based on business requirements
Crawling services

Enables users to access, extract and process content frommultiple supported content repositories including ECM,Web, and Twitter.

Annotation service Powers the core capabilities of Magellan Text Mining byleveraging taxonomies and authority files. This service
enables summarization, and content enrichment withcategories/classifications, named entities, key concepts,
emotion and sentiment analysis at the document, sentenceor entity level.
Magellan Text Min- Offers a convenient, visually appealing user interface toing Studiocontrol the content analysis process, from content accessthrough semantic enrichment and metadata federation.
Persistence layers

Magellan Text Mining

Includes RDBMS, Hive, Apache Solr and Apache
Spark services.

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About OpenText
Try Magellan Text Mining
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OpenText, The Information Company, enables organizations to gain
insight through market leading information management solutions,on-premises or in the cloud. For more information about OpenText(NASDAQ: OTEX, TSX: OTEX) visit: opentext.com.

Connect with us:• OpenText CEO Mark Barrenechea’s blog
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For more information, visit: https://www.opentext.com/about/copyright-information • 01.22 | 19787EN

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