Extraction of Knowledge Models from Textbooks

Abstract

Many adaptive educational systems and other artificial intelligence applications rely on high-quality knowledge representations. Still, knowledge acquisition remains the primary bottleneck hindering large-scale deployment and adoption of knowledge-based systems. One path to scalable knowledge extraction is using digital textbooks, given their domain-oriented content, structure, and availability. This dissertation presents a unified approach for automatically extracting high-quality and domain-specific knowledge models from digital textbooks. The proposed approach leverages the authors’ knowledge encoded in the textbooks’ elements that facilitate navigation and understanding of the material (table of contents, index, formatting styles) to create knowledge models. The proposed workflow first extracts initial information elements from the textbooks: the structure of chapters and subchapters using the Table of Content, the content of each section, and domain terminology from the back-of-the-book index. Then, new information is added: domain terms are linked to external entities in a knowledge graph (DBpedia) and are enriched with semantic content (e.g., abstracts and categories). Finally, the knowledge about the domain is refined by identifying the relevance of concepts to the target domain. The extracted knowledge is represented in a model using the Text Encoding Initiative. Multiple evaluations show that the extracted knowledge models have high levels of quality across several properties: accuracy, semantics, coverage, specificity, cognitive validity, and granularity. Additionally, the approach is effective in multiple domains—for example, statistics, ancient philosophy, and Python programming. Finally, there are many potential applications for the extracted knowledge models. This dissertation presents three different educational systems supported by the knowledge models.

A hybrid extraction level layout design for block caving

“…The roominess increased in the Hybrid layout because of the LHD load ore from the production drift. The triangular configuration of the extraction drift decreased the span between the production and extraction drift; this is also observed in the 'offset' herringbone layout (Chacon 1980).…”

“…The layouts were compared in terms of development and support requirements and according to the comparison criteria proposed by Chacon (1980), which include the layout density, utilization area, sustenance, distortion, anisotropy, and roominess. Table 2 shows the input variables used for the El Teniente and the proposed layouts.…”

“…On the other hand, Table 4 shows the result of the comparison criteria (Chacon 1980). Here, it can be observed that the utilization of the area over the drawpoint increases in the Hybrid layout because of the location of the drawpoint that also decreases the layout distortion and anisotropy.…”

“…The comparison criteria used in this study are based on design aspects of extraction layouts in block caving defined by Chacon (1980) as the following:…”

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

“…Este artículo hace un resumen de una tesis doctoral [5] enfocada en abordar el problema descrito. El enfoque presentado extrae automáticamente modelos de conocimiento a partir de libros de texto digitales.…”