Using a domain-ontology and semantic search in an eLearning

environmentLothar Lemnitzer, Kiril Simov, Petya Osenova, Eelco Mossel and Paola

Monachesi

International Conference on Engineering Education, Instructional Technology,

Assessment, and E-learning(EIAE 07), December 2007

Outline of the Talk• Introductory notes

• LT4eL Domain Ontology

• Ontology-based Lexicon Model

• Semantic annotation of learning objects

• Semantic Search

• Evaluation

• Conclusions

Introductory notes (1)• LT4eL European project aims at

demonstrating the relevance of language technology and ontologies for improving learning management systems (LMS)

• Multilingual approach

Lexikon

CZ

CZCZEN

ENCONVERTOR 1

Documents SCORM

Pseudo-Struct.

Basic XML LING. PROCESSOR

Lemmatizer, POS, Partial Parser

CROSSLINGUAL RETRIEVAL

LMS User Profile

Documents SCORM

Pseudo-Struct

Metadata (Keywords)

Ling. Annot XML

Ontology

CONVERTOR 2

Documents HTML

Lexikon

PT

Lexikon

RO

Lexikon

PL

Lexicon

GE

Lexikon

MT

Lexikon

BG

Lexikon

DT

Lexicon

EN

PLPL

GEGE

BGBG

PTPT

MTMT

DTDT

RORO

ENDocuments User

(PDF, DOC, HTML,

SCORM,XML)

REPOSITORY

Glossary

Introductory notes (2)

We created and use

• A domain ontology

• Lexicons for several languages

• (Linguistically, semantically) annotated learning objects

for semantic search

LT4eL Domain Ontology: general issues

• The domain: Computer Science for Non-Computer Scientists

• The role of the ontology: indexing of the Los, semantic search

LT4eL Domain Ontology: creation

Keywordsannotation

BG

EN

PT

NL

MT

CZ

PO

RO

Translationinto EN

DefinitionCollection

Conceptcreation

Current state of the ontology

• about 750 domain concepts,

• about 50 concepts from DOLCE

• about 250 intermediate concepts from OntoWordNet

• about 200 new concepts extracted from LOs

Ontology-Based Lexicon Model (1)

• The lexicons represent the main interface between the user's query and the ontology

• Lexicons for all languages of the project have been created

Ontology-Based Lexicon Model (2)

• all the important concepts within a domain should be included

• we allow the lexicons to contain also non-lexicalized phrases (e.g. mapping variety)

Example from the Dutch lexicon

<entry id="id60"> <owl:Class rdf:about="lt4el:BarWithButtons"> <rdfs:subClassOf> <owl:Class rdf:about="lt4el:Window"/> </rdfs:subClassOf> </owl:Class> <def>A horizontal or vertical bar as a part of a window, that contains buttons, icons.</def> <termg lang="nl"> <term shead="1">werkbalk</term> <term>balk</term> <term type="nonlex">balk met knoppen</term> <term>menubalk</term> </termg> </entry>

Semantic Annotation of Learning Objects

• Within the project we performed both types of annotation,:– inline– through metadata

• The inline annotation will be used:

– as a mechanism to validate the coverage of the ontology;

– for semantic retrieval

Semantic Search

Aims at improved retrieval of documents– Find documents that would not be found by simple full

text search; e.g. search for “screen” retrieves documents that contain “monitor”

Crosslingual– Find documents in languages different from

search/interface language; – Advantage: No need to translate search query

Ontology: contains concepts Document

Database

Lexicons: contain

term-concept mappings

Visualisation selec

t conce

pts

Search-Term(s)

Search-Concepts

Retrieved Documents

Search procedure

Search procedure

• Provide a search query in Language L(1)• Find terms in lexicons of L(1) that reflect search

query• Find relevant documents for concepts in L(1),

L(2) etc. • Rank for set of found documents• Create ontology fragment containing necessary

information to present concept neighbourhood

Search with ILIAS

Evaluation of Semantic Search

Aspects:• Does semantic search return correct results, i.e.

appropriate documents?• How easy is it to use semantic search?• Are the results better (precision/recall) than with

keyword search or full text search?• Does semantic search improve learning

processes?

Formal EvaluationProcedure: Search for paragraphs with query

• formed on the basis of Concepts from ontology

#Program* + #Slide

• formed on the basis of Terms in the lexicons

Program, Software, Editor, Slide

For a variety of languages.

Conclusions

Language Full-text search

(F-measure)

Semantic search (F-measure)

Bulgarian 56,25 91,30

Dutch 47,50 94,12

English 27,96 79,42

German 36,00 59.26

Polish 12,50 50,00

Portuguese 28,67 33,33

Conclusions

• Evaluation experiment showed the superiority of semantic search over simple full text search

• Our architecture introduces cross-lingual search into the learning process

Contact

• www.lt4el.eu

• Contact for information: Paola.Monachesi@let.uu.nl