Order out of Chaos

Alpizar-Chacon, Isaac; Sosnovsky, Sergey

doi:10.1145/3395027.3419585

Cited by 9 publications

(5 citation statements)

References 25 publications

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“…Precisión: La información del libro de texto se representa adecuadamente en los modelos de conocimiento. En general, el contenido, los elementos de la Tabla de Contenidos y los términos en el índice se extraen de forma precisa [11,12].…”

Section: Resultsunclassified

Extracción de modelos de conocimiento a partir de libros de texto y su aplicación en los negocios

Alpizar-Chacon

2024

ITEC

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Este artículo describe un enfoque innovador para la extracción de modelos de conocimiento a partir de libros de texto y su aplicación en los negocios. A través de un proceso detallado, que incluye la extracción, vinculación, enriquecimiento, análisis y formalización, se crean modelos de conocimiento de alta calidad. Este proceso es el resultado de una investigación doctoral, y en este artículo se ofreceun resumen ejecutivo de la misma. Los modelos creados tienen aplicaciones en la educación, pero también pueden ser usados potencialmente en el ámbito empresarial. En ese sentido, este artículo explora también las posibilidades de adaptar este proceso para interpretar y procesar documentos empresariales esenciales.

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Section: Resultsunclassified

Extracción de modelos de conocimiento a partir de libros de texto y su aplicación en los negocios

Alpizar-Chacon

2024

ITEC

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“…Section 2 briefly outlines the approach developed to produce such a model. The quality of the DMs extracted from textbooks with this approach has been evaluated before in terms of accuracy [2], semantic completeness [1], coverage [1], and domain specificity [4]. This paper explores the quality of the concepts extracted from textbooks as Knowledge Components (KCs) assessing their cognitive validity and applicability for knowledge modeling and assessment.…”

Section: Introductionmentioning

confidence: 99%

“…Additionally, textbooks provide both fine-and coarse-grained concepts; smaller concepts are shown to support more accurate student modeling. We have developed a workflow for the automated extraction of DMs from textbooks [1][2][3][4]. Figure 1 shows the main stages of this approach.…”

Section: Introductionmentioning

confidence: 99%

Measuring the Quality of Domain Models Extracted from Textbooks with Learning Curves Analysis

Alpizar-Chacon

Sosnovsky

Brusilovsky

2023

Lecture Notes in Computer Science

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This paper evaluates an automatically extracted domain model from textbooks and applies learning curve analysis to assess its ability to represent students' knowledge and learning. Results show that extracted concepts are meaningful knowledge components with varying granularity, depending on textbook authors' perspectives. The evaluation demonstrates the acceptable quality of the extracted domain model in knowledge modeling.

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“…Multiple books (e.g., [6,9,30]) and guidelines (e.g., [1,2]) are written to direct the index creation process. Dedicated associations (e.g., The American Society for Indexing 3 and The Society of Indexers 4 ) develop and disseminate book-indexing methods and practices. Methodologies for indexing stipulate index length and style, good and bad candidates for index terms, how to maintain consistency when creating hierarchical indices, interrelationships among terms, etc.…”

Section: Introductionmentioning

confidence: 99%

“…In our recent work [4], we have described a procedure for automated extraction of knowledge models from PDF textbooks, based on their structure, formatting and organization patterns. We have paid special attention to the index sections of the processed textbooks as the source of fine-grained domain terminology and text annotations.…”

Section: Introductionmentioning

confidence: 99%

What’s in an Index: Extracting Domain-specific Knowledge Graphs from Textbooks

Alpizar-Chacon

Sosnovsky

2022

Proceedings of the ACM Web Conference 2022

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A typical index at the end of a textbook contains a manuallyprovided vocabulary of terms related to the content of the textbook. In this paper, we extend our previous work on extraction of knowledge models from digital textbooks. We are taking a more critical look at the content of a textbook index and present a mechanism for classifying index terms according to their domain specificity: a core domain concept, an in-domain concept, a concept from a related domain, and a concept from a foreign domain. We link the extracted models to DBpedia and leverage the aggregated linguistic and structural information from textbooks and DBpedia to construct and prune the domain-specific knowledge graphs. The evaluation experiments demonstrate (1) the ability of the approach to identify (with high accuracy) different levels of domain specificity for automatically extracted concepts, (2) its cross-domain robustness, and (3) the added value of the domain specificity information. These results clearly indicate the improved quality of the refined knowledge graphs and widen their potential applicability.

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Order out of Chaos

Cited by 9 publications

References 25 publications

Extracción de modelos de conocimiento a partir de libros de texto y su aplicación en los negocios

Extracción de modelos de conocimiento a partir de libros de texto y su aplicación en los negocios

Measuring the Quality of Domain Models Extracted from Textbooks with Learning Curves Analysis

What’s in an Index: Extracting Domain-specific Knowledge Graphs from Textbooks

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