1. ©2003 Paula Matuszek CSC 9010: AeroText, Ontologies, AeroDAML Dr. Paula Matuszek Paula_A_Matuszek@glaxosmithkline.com (610) 270-6851

2. ©2003 Paula Matuszek AeroText l Information Extraction tool marketed by Lockheed Martin l Capabilities similar to GATE l Much better developed IDE l Less open to extensions of the system itself. l Equally steep learning curve for effective use! Lockheed AeroText General Overview Lockheed AeroText White Paper

3. ©2003 Paula Matuszek AeroText Demo

4. ©2003 Paula Matuszek Ontologies l Information Extraction requires modeling extensive domain knowledge l Other applications of text mining, such as document categorization, can also use domain information l In modeling such knowledge we often create an ontology: An explicit formal specification of how to represent the objects, concepts, and other entities that are assumed to exist in some area of interest and the relationships that hold among them.

5. ©2003 Paula Matuszek A Simple Ontology: Birthdates l Objects, concepts, entities: –Months, days, years –dates –first names –last names –persons –birthdates l Relationships between them –a date has exactly one month, day, year –a birthdate is a date –a person has at least 1 first name and exactly 1 last name –a person has a birthdate –a birthdate has a person

6. ©2003 Paula Matuszek Who and Why? l Many groups are developing ontologies: –standardize terms and vocabulary –facilitate the semantic web –improve information integration –interested in the domain itself l Some ontologies under development –Cyc –GO (Gene ontology) –UMLS (Unified Medical Language System) –CIA World Factbook

7. ©2003 Paula Matuszek DAML l DARPA Agent Markup Language l A language for describing ontologies l Example: an ontology for dates Example: an ontology for dates l Extensive information available at www.daml.org.

8. ©2003 Paula Matuszek UBOT l UML Based Ontology Toolkit l Part of a DARPA project to automatically mark up web pages to make them l The purpose of DAML is to annotate information on the web to make it machine-readable so that software agents can interpret it and reason with it: the semantic web l http://ubot.lockheedmartin.com/ubot/intro/index.html http://ubot.lockheedmartin.com/ubot/intro/index.html

9. ©2003 Paula Matuszek AeroDAML l AeroDAML is a web service that takes a web page as an input and generates DAML markup. l Uses AeroText as the underlying extraction tool. l Works with various ontologies. l Paper describing system Paper describing system

10. ©2003 Paula Matuszek Lab: try out AeroDAML l AeroDAML page AeroDAML page Choose a news page (www.phillynews.com, Google News,...) and tag it with the Cyc and CIA ontologies. How well did each ontology do at picking up content? Did they miss things they should have found? Was anything tagged incorrectly? Repeat for one of your domain-specific documents, or a web page in a specific area. Try a different ontology if you think one of the others might be more interesting. How was the annotation different? Are we enabling the semantic web?