Automatic Extraction of Topic Maps based Argumentation Trails Text Mining Services Conference Leipzig, 2009/03/25 Marco Büchler, Lutz Maicher, Frederik Baumgardt, Benjamin Bock Natural Language Processing Group Department of Computer Science University of Leipzig

Starting Point: Panionion ‏

Computation of argumentation trails on fragmentary texts Surplus and relation between Topic Maps and argumentation trails Results Further work / conclusion Agenda

Computation of argumentation trails on fragmentary texts

Surplus and relation between Topic Maps and argumentation trails

Results

Further work / conclusion

Technical details

Text source

Co-occurrence as underlying graph - de Saussure (1898/1916 ): Structuralism assumes that meaning is the result of structural relations between word forms The fundamental structural relations are syntagmatic and paradigmatic relations [Heyer & Bordag 2007] Argumentation trails vs. Lexical Chaining - fragmentary texts Underlying graph

Co-occurrence as underlying graph

- de Saussure (1898/1916 ):

Structuralism assumes that meaning is the result of structural relations between word forms

The fundamental structural relations are syntagmatic and paradigmatic relations [Heyer & Bordag 2007]

Argumentation trails vs.

Lexical Chaining

- fragmentary texts

“ Definition/Motivation”: What's the average path length in a graph? Average path length is typically not larger than7. Simple proof of concept (Using XING): Every person of my contacts has in average about 73 contacts (1. and 2. level) log 73 (6,800,000,000)= 5,28 Small World

“ Definition/Motivation”:

What's the average path length in a graph?

Average path length is typically not larger than7.

Simple proof of concept (Using XING):

Every person of my contacts has in

average about 73 contacts (1. and 2.

level)

log 73 (6,800,000,000)= 5,28

Methodology

Topic Maps ‏

Data model of Topic Maps (Topics) Nikolaikirche variant St. Nicholas Church St. Nikolai name English scope 1165 occurrence www.nikolaikirche -leipzig.de/ occurrence foundation type website type

Data model of Topic Maps (Associations) St. Nikolai Leipzig association container-containee ass. role role player container containee role type

Data model of Topic Maps (Summary) ‏ one topic represents one subject in a data source names represent the names of the subject names might have variants occurrences represent properties of the subject associations represent relationships between subjects flexibility through roles n-ary associations all types and scopes are (set of) Topics in a topic map everything is a topic

one topic represents one subject in a data source

names represent the names of the subject

names might have variants

occurrences represent properties of the subject

associations represent relationships between subjects

flexibility through roles

n-ary associations

all types and scopes are (set of) Topics

in a topic map everything is a topic

What are Topic Maps (ISO 13250)? Topic Maps are highly-networked data sources one topic for each subject relationships of subjects are associations between topics Topic Maps have a human-centric data model vocabulary for documenting information fits human cognition network resembles human cognition Topic Maps have an integration model whenever two topics represent the same subject, they have to be merged always one information access hub for each subject high terminological flexibility and schema-free use in knowledge federation and sensemaking Topic Maps is an international industry standard (ISO 13250) ‏

Topic Maps are highly-networked data sources

one topic for each subject

relationships of subjects are associations between topics

Topic Maps have a human-centric data model

vocabulary for documenting information fits human cognition

network resembles human cognition

Topic Maps have an integration model

whenever two topics represent the same subject, they have to be merged

always one information access hub for each subject

high terminological flexibility and schema-free

use in knowledge federation and sensemaking

Topic Maps is an international industry standard (ISO 13250) ‏

Extraction of typed significant terms Corpus is categorized in several classification schemas. Split corpus into several sub corpora Medusa age gender geography .... Categorized co-occurrences/terms Tomcat/ Prefuse Age gender geography (Source:Taken from bachelor thesis slides of Marcus Puchalla.) ‏

Results

Several graph properties

Visualisation of two argumentation trails

Marco Büchler onotoa.topicmapslab.de Topic-Maps-Ontologie for the Argumentation Trails Topic Maps and Argumentation Trails

- Reduction of graph comlexity - e. g. by semantic pre-clustering or - authors restrictions - Weighting of argumentation trails - e. g. Trails containing hubs should be weighted lower - Improvements in visualisation - Clustering of similar trails to a bunch of semanitic similar trails - Improvements in typing nodes and especially edges Further work / conclusion