1. Corpus-based Terminology Extraction applied to Information Access Anselmo Peñas, Felisa Verdejo and Julio Gonzalo NLP Group, Dpto. Lenguajes y Sistemas Informáticos, UNED, Spain Corpus Linguistics 2001, Lancaster, UK

2. Content Introduction Resources, Tools and Corpora Terminology Extraction (TE) Evaluation of the TE procedure Terminology-based Information Access Conclusions

3. Introduction: Framework The European Treasury Browser (ETB) project Web site of Educational Resources (primary and secondary school) Context of New Technologies Objective: to build the structures to organise and retrieve educational resources Similar systems The Educational Resources Information Centre The British Education Index

6. Introduction: use of Thesauri Thesauri Definition: controlled vocabulary, structured in relations Structure: descriptors and relations (NT, BT, RT) Existing educational thesauri Don’t cover primary and secondary school vocabulary within the new technologies context Construction of a multilingual thesaurus is needed for the ETB project purposes Terminology Lists

7. Objectives of the work To build the Spanish list of candidate terms for the ETB multilingual thesaurus. To develop a general procedure to obtain terminology lists In an automatic way Independently of the application domain To explore effective ways of Information Retrieval using the terminology lists instead of thesaurus to bridge the gap between users’ and collection languages

8. Content Introduction Resources, Tools and Corpora Terminology Extraction (TE) Evaluation of the TE procedure Terminology based Information Access Conclusions

9. Resources and Tools Resources Semantic network: EuroWordNet Monolingual dictionary (VOX) Bilingual dictionary (VOX) Tools Tokeniser Morphological analyser POS tagger Shallow parser (based on syntactic patterns)

10. Corpora Corpus of educational resources 1,075 documents (670,646 words) from –Programa de Nuevas Tecnologías (http://www.pntic.mec.es/main_recursos.html) –Aldea Global (http://sauce.pntic.mec.es/~alglobal) Corpus of international news 7,364 documents (2.9 million words) –(http://www.elpais.es/internac) Pre-processing (html tags treatment, language detection, detection of repeated pages and chunks, etc.)

11. Content Introduction Resources, Tools and Corpora Terminology Extraction (TE) Evaluation of the TE procedure Terminology based Information Access Conclusions

12. Terminology Extraction (TE) Terminology List: List of mono-lexical and poly-lexical terms which are usual in a specific domain Steps of Terminology Extraction 1. Term detection 2. Term weighting 3. Term selection

13. 1. Term Detection (mono-lexical) (Over both corpora, Educational Resources and International News) Processing Tokenising Lemmatising,Tagging Removal of erroneous strings, abbreviations and words from other languages Extraction of nouns, verbs and adjectives Result List of candidate lemmas with its: Term frequency (any form) in both collections Document frequency in both collections

14. 1. Term Detection (poly-lexical) (Over Educational Resources corpus) Processing Tokenising, Lemmatising,Tagging Shallow parsing (Syntactic pattern recognition) Result List of candidate terminological phrases: Term frequency in the collection Document frequency in the collection... como/CS en/Prep la/Art educación/N a/Prep distancia/N,/Punc el/Art ministerio/N... Pattern: N Prep N Detected term: educación a distancia Syntactic Patterns for Spanish terminological phrases N NN A N [A] Prep N [A] N [A] Prep Art N [A] N [A] Prep V N [A] Prep V N [A]

15. 2. Term weighting Empirical measure Proportional to –term frequency –document frequency Inversely proportional to –term frequency in other domain Normalisation in the domain corpus

16. 3. Term Selection Removal of unfrequent terms in the study domain Removal of very frequent terms in other domains Ranking of terms according to their weight Selection of top terms in the terminology list (thresholds to obtain 2,000 / 3,000 terms from the  75,000 detected terms) Addition of phrases with relevant components

17. Content Introduction Resources, Tools and Corpora Terminology Extraction (TE) Evaluation of the TE procedure Terminology based Information Access Conclusions

18. Evaluation: Visual exploration Automatic generation of result pages in HTML Purpose To help in the decisions of the prototype development To evaluate the measures and techniques and to suggest improvements or modifications To give further information to documentalists in order to assist final decisions in thesaurus construction

21. Evaluation: Visual exploration

22. Evaluation: Precision Manual classification of the 2,856 selected terms Proyecto curricularCiencias socialesSistema operativo Proyectos curriculares (Proyecto curricular) Profesorado materiales ¿?Alumnos inglesesBiblioteca nacional With a low effort, a large number of accurate terms is proposed to documentalists

23. Evaluation: Precision precision number of selected candidates Precision, % of selected terms which are appropriate terms Higher precision on the top of the ranking With a lower number of candidates, the precision increases

24. Content Introduction Resources, Tools and Corpora Terminology Extraction (TE) Evaluation of the TE procedure Terminology-based Information Access Conclusions

25. Terminology-based Information Access Terminology Extraction in Information Retrieval provides: At Indexing: to add poly-lexical terms to the indexes without the explosion of n-grams Term browsing: to navigate through the terminology and access the documents from the terms (without the use of thesauri)

26. Terminology-based Information Access A difference with TE: terminology list truncation (as query gives the relevant terms, now the task is concerned with recall rather than precision of terms) A new task: to retrieve terminology Poly-lexical terms are retrieved from mono-lexical ones

29. Terminology-based Information Access Terminology retrieval To bridge the gap between Collection terminology Query terms Requires Query expansion Query translation But produces noise in the retrieval However phrases provides an excellent way for ambiguity reduction (Ballesteros & Croft, 1998)

31. Terminology-based Information Access Tratados acuerdo capitulación concertación convenio cuidar, pacto manejar procesar accord discourse handle manage pact process treat treatise treaty Prohibición embargo entredicho interdicción interdicto proscripción ban interdiction prohibition proscription Pruebas cata, catadura degustación ensayo escandallo experimento gustación muestreo, tanteo demonstrate establish, exhibit experiment experimentation fall, fitting indicate, point present, proof prove, run sample, sampling shew,show, taste test, trial, try de Nucleares nuclear de Nuclear test ban treaty? Nuclear fitting interdiction manage? Nuclear taste proscription process? Expansion Translation

33. Content Introduction Resources, Tools and Corpora Terminology Extraction (TE) Evaluation of the TE procedure Terminology based Information Access Conclusions

34. Conclusions Extraction of relevant terms in Spanish for the ETB project domain (primary and secondary school / new technologies) –Automatic process from free resources as web pages –Exploring contexts and statistical data via Internet Development of a search engine based on terminology extraction –Using terminology lists in an intermediate way between free-searching and thesaurus-guided searching –Without needing of thesaurus construction –Bridging the distance between the terms used in the query and the terminology used in the collection (even in different languages)

35. Thanks for your attention