INDEX: The statistical basis for an automatic conceptual phrase-indexing system

Jones, Leslie C.; Gassie, Edward W.; Radhakrishnan, Sridhar

doi:10.1002/(sici)1097-4571(199003)41:2<87::aid-asi2>3.0.co;2-8

Cited by 26 publications

(12 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Salton 1988;Salton, Zhao, and Buckley 1990;Cherry 1990), especially for information retrieval (e.g. Hamill and Zamora 1980;Jones, Gassie, and Radhakrishnan 1990) and for natural language database query systems (e.g. Damerau 1993).…”

Section: Related Workmentioning

confidence: 99%

Technical terminology: some linguistic properties and an algorithm for identification in text

1995

View full text Add to dashboard Cite

This paper identifies some linguistic properties of technical terminology, and uses them to formulate an algorithm for identifying technical terms in running text. The grammatical properties discussed are preferred phrase structures: technical terms consist mostly of noun phrases containing adjectives, nouns, and occasionally prepositions; rerely do terms contain verbs, adverbs, or conjunctions. The discourse properties are patterns of repetition that distinguish noun phrases that are technical terms, especially those multi-word phrases that constitute a substantial majority of all technical vocabulary, from other types of noun phrase.The paper presents a terminology indentification algorithm that is motivated by these linguistic properties. An implementation of the algorithm is described; it recovers a high proportion of the technical terms in a text, and a high proportaion of the recovered strings are vaild technical terms. The algorithm proves to be effective regardless of the domain of the text to which it is applied.

show abstract

Section: Related Workmentioning

confidence: 99%

Technical terminology: some linguistic properties and an algorithm for identification in text

1995

View full text Add to dashboard Cite

show abstract

“…Use of the linguistic approaches or statistical approach alone does not provide an effective result (Pazienza et al, 2005). There are only a few works that use only the statistical method without touching any of the linguistic approaches (Jones et al, 1990;Salton et al, 1975) . In this research, we therefore chose to use a hybrid approach for the lecture slide materials.…”

Section: Linguistic and Statistic Approaches For Term Extractionmentioning

confidence: 99%

Analysing Features of Lecture Slides and past Exam Paper Materials - Towards Automatic Associating E-materials for Self-revision

Sajjacholapunt

Joy

2015

Proceedings of the 7th International Conference on Computer Supported Education

View full text Add to dashboard Cite

Abstract:Digital materials not only provide opportunities as enablers of e-learning development, but also create a new challenge. The current e-materials provided on a course website are individually designed for learning in classrooms rather than for revision. In order to enable the capability of e-materials to support a students revision, we need an efficient system to associate related pieces of different e-materials. In this case, the features of each item of e-material, including the structure and the technical terms they contain, need to be studied and applied in order to calculate the similarity between relevant e-materials. Even though difficulties regarding technical term extraction and the similarities between two text documents have been widely discussed, empirical experiments for particular types of e-learning materials (for instance, lecture slides and past exam papers) are still rare. In this paper, we propose a framework and relatedness model for associating lecture slides and past exam paper materials to support revision based on Natural Language Processing (NLP) techniques. We compare and evaluate the efficiency of different combinations of three weighted schemes, term frequency (TF), inverse document frequency (IDF), and term location (TL), for calculating the relatedness score. The experiments were conducted on 30 lectures (∼ 900 slides) and 3 past exam papers (12 pages) of a data structures course at the authors' institution. The findings indicate the appropriate features for calculating the relatedness score between lecture slides and past exam papers.

show abstract

“…We evaluated the APAT terminology using a validation approach (as in [1,7]) for calculating Precision, and a reference list (see [1]) for calculating Recall. As high Precision is a key issue for the overall application, we evaluated the 917 terms extracted by the system with the threshold set to τ=5.…”

Section: Terminology Evaluation and Analysismentioning

confidence: 99%

Ontological support to knowledge management in a hydrogeological information system

Pazienza¹,

Pennacchiotti²,

Stellato³

2006

WIT Transactions on Information and Communication Technologies, Vol 37

View full text Add to dashboard Cite

In this work we report our experience in realizing an Information System for the Italian APAT agency (Azienda per la Protezione Ambiente e Territorio) with the aim of supporting analysis of the hydrogeological situation of the Italian territory. Objective of the system is to provide a structured environment for knowledge management and report production, to support the complex activity of APAT officers in charge of retrieving, organizing and managing data originating from distributed APAT agencies (one for each Italian region) and of those involved in the production of synthesis documentation over the collected information.

show abstract

INDEX: The statistical basis for an automatic conceptual phrase-indexing system

Cited by 26 publications

References 11 publications

Technical terminology: some linguistic properties and an algorithm for identification in text

Technical terminology: some linguistic properties and an algorithm for identification in text

Analysing Features of Lecture Slides and past Exam Paper Materials - Towards Automatic Associating E-materials for Self-revision

Ontological support to knowledge management in a hydrogeological information system

Contact Info

Product

Resources

About